R/appreci8R_GUI.R
In sandmanns/appreci8R: appreci8R: an R/Bioconductor package for filtering SNVs and short indels with high sensitivity and high PPV
Defines functions
appreci8Rshiny
Documented in
appreci8Rshiny
#Open appreci8R GUI
appreci8Rshiny <- function() {
shinyApp(
ui=shinyUI(navbarPage("appreci8R",
tabPanel("Analysis",
fluidRow(
wellPanel(
navbarPage(
title='',
tabPanel("Important notes",
h4("Important notes:"),
h5("Please make sure that all your files containing variant calling results as well as the corresponding
bam- and bai files start with the sample name (e.g. Sample1.vcf, Sample2_rawCalls.txt or Sample3.bam)."),
h5("Currently, the analysis is just available for variant calling results, target regions and bam files
using \'1\', \'2\' etc. and not \'chr1\', \'chr2\'."),
h5("Currently, the analysis is just available for hg19/GRCh37.")),
tabPanel("0. Preparations",
h3("0. Preparations:"),
uiOutput("output_folderUI"),
hr(),
h3("Variant Caller Input (appreci8R):"),
h4("GATK:"),
actionButton("gatk_add","Add"),
actionButton("gatk_remove","Remove"),
hr(),
uiOutput("gatkUI1"),
uiOutput("gatkUI2"),
uiOutput("gatkUI3"),
uiOutput("gatkUI4"),
uiOutput("gatkUI5"),
uiOutput("gatkUI6"),
uiOutput("gatkUI7"),
uiOutput("gatkUI8"),
h4("Platypus:"),
actionButton("platypus_add","Add"),
actionButton("platypus_remove","Remove"),
hr(),
uiOutput("platypusUI1"),
uiOutput("platypusUI2"),
uiOutput("platypusUI3"),
uiOutput("platypusUI4"),
uiOutput("platypusUI5"),
uiOutput("platypusUI6"),
uiOutput("platypusUI7"),
uiOutput("platypusUI8"),
h4("VarScan:"),
actionButton("varscan_add","Add"),
actionButton("varscan_remove","Remove"),
hr(),
uiOutput("varscanUI1"),
uiOutput("varscanUI2"),
uiOutput("varscanUI3"),
uiOutput("varscanUI4"),
uiOutput("varscanUI5"),
uiOutput("varscanUI6"),
uiOutput("varscanUI7"),
uiOutput("varscanUI8"),
h4("FreeBayes:"),
actionButton("freebayes_add","Add"),
actionButton("freebayes_remove","Remove"),
hr(),
uiOutput("freebayesUI1"),
uiOutput("freebayesUI2"),
uiOutput("freebayesUI3"),
uiOutput("freebayesUI4"),
uiOutput("freebayesUI5"),
uiOutput("freebayesUI6"),
uiOutput("freebayesUI7"),
uiOutput("freebayesUI8"),
h4("LoFreq:"),
actionButton("lofreq_add","Add"),
actionButton("lofreq_remove","Remove"),
hr(),
uiOutput("lofreqUI1"),
uiOutput("lofreqUI2"),
uiOutput("lofreqUI3"),
uiOutput("lofreqUI4"),
uiOutput("lofreqUI5"),
uiOutput("lofreqUI6"),
uiOutput("lofreqUI7"),
uiOutput("lofreqUI8"),
h4("SNVer:"),
actionButton("snver_add","Add"),
actionButton("snver_remove","Remove"),
hr(),
uiOutput("snverUI1"),
uiOutput("snverUI2"),
uiOutput("snverUI3"),
uiOutput("snverUI4"),
uiOutput("snverUI5"),
uiOutput("snverUI6"),
uiOutput("snverUI7"),
uiOutput("snverUI8"),
h4("SamTools:"),
actionButton("samtools_add","Add"),
actionButton("samtools_remove","Remove"),
hr(),
uiOutput("samtoolsUI1"),
uiOutput("samtoolsUI2"),
uiOutput("samtoolsUI3"),
uiOutput("samtoolsUI4"),
uiOutput("samtoolsUI5"),
uiOutput("samtoolsUI6"),
uiOutput("samtoolsUI7"),
uiOutput("samtoolsUI8"),
h4("VarDict:"),
actionButton("vardict_add","Add"),
actionButton("vardict_remove","Remove"),
hr(),
uiOutput("vardictUI1"),
uiOutput("vardictUI2"),
uiOutput("vardictUI3"),
uiOutput("vardictUI4"),
uiOutput("vardictUI5"),
uiOutput("vardictUI6"),
uiOutput("vardictUI7"),
uiOutput("vardictUI8"),
numericInput('nr_additional',"How many additional callers would you like to add? (max 5)",value=0,min=0,max=5),
actionButton("nr_additional_action","Go"),
hr(),
uiOutput("caller1UI0"),
uiOutput("caller1UI0.1"),
uiOutput("caller1UI1"),
uiOutput("caller1UI2"),
uiOutput("caller1UI3"),
uiOutput("caller1UI4"),
uiOutput("caller1UI5"),
uiOutput("caller1UI6"),
uiOutput("caller1UI7"),
uiOutput("caller1UI8"),
uiOutput("caller2UI0"),
uiOutput("caller2UI0.1"),
uiOutput("caller2UI1"),
uiOutput("caller2UI2"),
uiOutput("caller2UI3"),
uiOutput("caller2UI4"),
uiOutput("caller2UI5"),
uiOutput("caller2UI6"),
uiOutput("caller2UI7"),
uiOutput("caller2UI8"),
uiOutput("caller3UI0"),
uiOutput("caller3UI0.1"),
uiOutput("caller3UI1"),
uiOutput("caller3UI2"),
uiOutput("caller3UI3"),
uiOutput("caller3UI4"),
uiOutput("caller3UI5"),
uiOutput("caller3UI6"),
uiOutput("caller3UI7"),
uiOutput("caller3UI8"),
uiOutput("caller4UI0"),
uiOutput("caller4UI0.1"),
uiOutput("caller4UI1"),
uiOutput("caller4UI2"),
uiOutput("caller4UI3"),
uiOutput("caller4UI4"),
uiOutput("caller4UI5"),
uiOutput("caller4UI6"),
uiOutput("caller4UI7"),
uiOutput("caller4UI8"),
uiOutput("caller5UI0"),
uiOutput("caller5UI0.1"),
uiOutput("caller5UI1"),
uiOutput("caller5UI2"),
uiOutput("caller5UI3"),
uiOutput("caller5UI4"),
uiOutput("caller5UI5"),
uiOutput("caller5UI6"),
uiOutput("caller5UI7"),
uiOutput("caller5UI8"),
hr()),
tabPanel("1. Target filtration",
h3("1. Target filtration:"),
fileInput('targetRegions', 'Upload your target region (*.bed)'),
hr()),
tabPanel("2. Normalization",
h3("2. Normalization"),
hr()),
tabPanel("3. Annotation",
h3("3. Annotation:"),
h4("Important note:"),
h5("Currently, only UCSC is available."),
uiOutput("locationsUI"),
uiOutput("consequencesUI"),
hr()),
tabPanel("4. Combine output",
h3("4. Combine output"),
hr()),
tabPanel("5. Evaluate Coverage and BQ",
h3("5. Evaluate Coverage and BQ:"),
uiOutput("bam_folderUI"),
uiOutput("dpUI"),
uiOutput("nr_altUI"),
uiOutput("vafUI"),
uiOutput("bqUI"),
uiOutput("bq_diffUI"),
hr()),
tabPanel("6. Extended Set of Characteristics",
h3("6. Extended Set of Characteristics:"),
h4("What databases would you like to query?"),
uiOutput("dbSNPUI"),
uiOutput("1kgenomesUI"),
uiOutput("exacUI"),
uiOutput("gadUI"),
uiOutput("cosmicUI"),
uiOutput("clinvarUI"),
uiOutput("predictUI"),
hr()),
tabPanel("7. Final Filtration",
h3("7. Final Filtration:"),
fileInput('primerPositions', 'Optional: Upload your primer positions (*.bed)'),
fileInput('hotspots', 'Optional: Upload your hotspot list (*.txt)'),
h5("Please make sure your hotspot list has the following format:"),
h5("3 tab-seperated columns (with header)"),
h5(" 1. Gene (e.g. ASXL1)"),
h5(" 2. Mutation (e.g. V617F or G646fs or R420* or I836ins or P95_R102del or G12)"),
h5(" 3. Minimum expected frequency for that mutation (e.g. 0.1 or NA)"),
uiOutput("stricter_thresholdsUI"),
uiOutput("stricter_thresholdsUI2"),
uiOutput("nr_samplesUI"),
uiOutput("predictionUI1"),
uiOutput("predictionUI2"),
uiOutput("predictionUI3"),
uiOutput("artifact_scoreUI"),
uiOutput("artifact_scoreUI2"),
uiOutput("polymorphism_scoreUI"),
uiOutput("polymorphism_scoreUI2")),
tabPanel("Action",
actionButton("appreci8R", "Start complete analysis"),
actionButton("checkpointCheck","Check for possible checkpoints"),
actionButton("exportConfig","Export current configuration"),
actionButton("importConfig","Import configuration"),
actionButton("done","Done"),
hr(),
uiOutput("checkpointUI1"),
uiOutput("checkpointUI2"),
hr(),
uiOutput("exportconfigUI0"),
uiOutput("exportconfigUI0.1"),
hr(),
uiOutput("exportconfigUI1"),
uiOutput("exportconfigUI2"),
hr(),
uiOutput("messageUI1"),
hr(),
uiOutput("importconfigUI0"),
uiOutput("importconfigUI0.1"),
hr(),
uiOutput("importconfigUI1"),
uiOutput("importconfigUI2"),
hr(),
uiOutput("messageUI2")
))))),
tabPanel("Overview results",
wellPanel(
navbarPage(
title='',
tabPanel("Log",
htmlOutput("log_info")),
tabPanel("Raw Calls",
DT::dataTableOutput('table')),
tabPanel("Calls On Target",
DT::dataTableOutput('table2')),
tabPanel("Annotated Calls",
DT::dataTableOutput('table3')),
tabPanel("Filtered Calls",
DT::dataTableOutput('table4'))
)
)
),
tabPanel("Detailed results",
wellPanel(
navbarPage(
title='',
tabPanel("Mutations",
DT::dataTableOutput('table_mutations')),
tabPanel("Polymorphisms",
DT::dataTableOutput('table_polymorphisms')),
tabPanel("Artifacts",
DT::dataTableOutput('table_artifacts'))
)
)
)
)),
server = function(input, output) {
observeEvent(input$done,{
stopApp()
})
observeEvent(input$gatk_add,{
output$gatkUI1<-renderUI({textInput('gatk_folder',
'Variant calling results',
"/home/gatk/")})
output$gatkUI2<-renderUI({radioButtons('gatk_file_type',
"Output file type",
c(".vcf",".txt"),".vcf",
inline=TRUE)})
output$gatkUI3<-renderUI({
conditionalPanel(
condition="input.gatk_file_type=='.txt'",
numericInput('gatk_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('gatk_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('gatk_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('gatk_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$gatkUI4<-renderUI({textInput('gatk_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',".rawMutations")})
output$gatkUI5<-renderUI({radioButtons('gatk_mnvs',
'MNVs reported?',
c("Yes","No"),"No",
inline = TRUE)})
output$gatkUI6<-renderUI({radioButtons('gatk_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),"Yes",
inline = TRUE)})
output$gatkUI7<-renderUI({conditionalPanel(
condition="input.gatk_snv_indel=='No'",
textInput('gatk_snv_names_add','Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',""),
textInput('gatk_indel_names_add','Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',""))})
output$gatkUI8<-renderUI({radioButtons('gatk_indels',
'How are Indels reported?',
c("CA>C","C>-A","CAAAC>CAAC"),
selected="CA>C",
inline = TRUE)})
})
observeEvent(input$gatk_remove,{
output$gatkUI1<-renderUI({NULL})
output$gatkUI2<-renderUI({NULL})
output$gatkUI3<-renderUI({NULL})
output$gatkUI4<-renderUI({NULL})
output$gatkUI5<-renderUI({NULL})
output$gatkUI6<-renderUI({NULL})
output$gatkUI7<-renderUI({NULL})
output$gatkUI8<-renderUI({NULL})
})
observeEvent(input$platypus_add,{
output$platypusUI1<-renderUI({textInput('platypus_folder',
'Variant calling results',
"/home/platypus/")})
output$platypusUI2<-renderUI({radioButtons('platypus_file_type',
"Output file type",
c(".vcf",".txt"),
".vcf",inline=TRUE)})
output$platypusUI3<-renderUI({
conditionalPanel(
condition="input.platypus_file_type=='.txt'",
numericInput('platypus_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('platypus_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('platypus_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('platypus_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$platypusUI4<-renderUI({textInput('platypus_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$platypusUI5<-renderUI({radioButtons('platypus_mnvs',
'MNVs reported?',
c("Yes","No"),"No",
inline = TRUE)})
output$platypusUI6<-renderUI({radioButtons('platypus_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),"Yes",
inline = TRUE)})
output$platypusUI7<-renderUI({conditionalPanel(
condition="input.platypus_snv_indel=='No'",
textInput('platypus_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',""),
textInput('platypus_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',""))})
output$platypusUI8<-renderUI({radioButtons('platypus_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
"CA>C",
inline = TRUE)})
})
observeEvent(input$platypus_remove,{
output$platypusUI1<-renderUI({NULL})
output$platypusUI2<-renderUI({NULL})
output$platypusUI3<-renderUI({NULL})
output$platypusUI4<-renderUI({NULL})
output$platypusUI5<-renderUI({NULL})
output$platypusUI6<-renderUI({NULL})
output$platypusUI7<-renderUI({NULL})
output$platypusUI8<-renderUI({NULL})
})
observeEvent(input$varscan_add,{
output$varscanUI1<-renderUI({textInput('varscan_folder',
'Variant calling results',
"/home/varscan/")})
output$varscanUI2<-renderUI({radioButtons('varscan_file_type',
"Output file type",
c(".vcf",".txt"),
".txt",inline=TRUE)})
output$varscanUI3<-renderUI({
conditionalPanel(
condition="input.varscan_file_type=='.txt'",
numericInput('varscan_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('varscan_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('varscan_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('varscan_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$varscanUI4<-renderUI({textInput('varscan_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$varscanUI5<-renderUI({radioButtons('varscan_mnvs',
'MNVs reported?',
c("Yes","No"),"No",
inline = TRUE)})
output$varscanUI6<-renderUI({radioButtons('varscan_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),"No",
inline = TRUE)})
output$varscanUI7<-renderUI({conditionalPanel(
condition="input.varscan_snv_indel=='No'",
textInput('varscan_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
"_snvs"),
textInput('varscan_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
"_indels"))})
output$varscanUI8<-renderUI({radioButtons('varscan_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected="C>-A",
inline = TRUE)})
})
observeEvent(input$varscan_remove,{
output$varscanUI1<-renderUI({NULL})
output$varscanUI2<-renderUI({NULL})
output$varscanUI3<-renderUI({NULL})
output$varscanUI4<-renderUI({NULL})
output$varscanUI5<-renderUI({NULL})
output$varscanUI6<-renderUI({NULL})
output$varscanUI7<-renderUI({NULL})
output$varscanUI8<-renderUI({NULL})
})
observeEvent(input$freebayes_add,{
output$freebayesUI1<-renderUI({textInput('freebayes_folder',
'Variant calling results',
"/home/freebayes/")})
output$freebayesUI2<-renderUI({radioButtons('freebayes_file_type',
"Output file type",
c(".vcf",".txt"),
".vcf",inline=TRUE)})
output$freebayesUI3<-renderUI({
conditionalPanel(
condition="input.freebayes_file_type=='.txt'",
numericInput('freebayes_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('freebayes_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('freebayes_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('freebayes_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$freebayesUI4<-renderUI({textInput('freebayes_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$freebayesUI5<-renderUI({radioButtons('freebayes_mnvs',
'MNVs reported?',
c("Yes","No"),"Yes",
inline = TRUE)})
output$freebayesUI6<-renderUI({radioButtons('freebayes_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),"Yes",
inline = TRUE)})
output$freebayesUI7<-renderUI({conditionalPanel(
condition="input.freebayes_snv_indel=='No'",
textInput('freebayes_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',""),
textInput('freebayes_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',""))})
output$freebayesUI8<-renderUI({radioButtons('freebayes_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected="CAAAC>CAAC",
inline = TRUE)})
})
observeEvent(input$freebayes_remove,{
output$freebayesUI1<-renderUI({NULL})
output$freebayesUI2<-renderUI({NULL})
output$freebayesUI3<-renderUI({NULL})
output$freebayesUI4<-renderUI({NULL})
output$freebayesUI5<-renderUI({NULL})
output$freebayesUI6<-renderUI({NULL})
output$freebayesUI7<-renderUI({NULL})
output$freebayesUI8<-renderUI({NULL})
})
observeEvent(input$lofreq_add,{
output$lofreqUI1<-renderUI({textInput('lofreq_folder',
'Variant calling results',
"/home/lofreq/")})
output$lofreqUI2<-renderUI({radioButtons('lofreq_file_type',
"Output file type",
c(".vcf",".txt"),
".vcf",inline=TRUE)})
output$lofreqUI3<-renderUI({
conditionalPanel(
condition="input.lofreq_file_type=='.txt'",
numericInput('lofreq_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('lofreq_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('lofreq_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('lofreq_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$lofreqUI4<-renderUI({textInput('lofreq_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$lofreqUI5<-renderUI({radioButtons('lofreq_mnvs',
'MNVs reported?',
c("Yes","No"),"No",
inline = TRUE)})
output$lofreqUI6<-renderUI({radioButtons('lofreq_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),"Yes",
inline = TRUE)})
output$lofreqUI7<-renderUI({conditionalPanel(
condition="input.lofreq_snv_indel=='No'",
textInput('lofreq_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
""),
textInput('lofreq_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
""))})
output$lofreqUI8<-renderUI({radioButtons('lofreq_indels',
'How are Indels reported?',
c("CA>C","C>-A","CAAAC>CAAC"),
selected="CA>C",
inline = TRUE)})
})
observeEvent(input$lofreq_remove,{
output$lofreqUI1<-renderUI({NULL})
output$lofreqUI2<-renderUI({NULL})
output$lofreqUI3<-renderUI({NULL})
output$lofreqUI4<-renderUI({NULL})
output$lofreqUI5<-renderUI({NULL})
output$lofreqUI6<-renderUI({NULL})
output$lofreqUI7<-renderUI({NULL})
output$lofreqUI8<-renderUI({NULL})
})
observeEvent(input$snver_add,{
output$snverUI1<-renderUI({textInput('snver_folder',
'Variant calling results',
"/home/snver/")})
output$snverUI2<-renderUI({radioButtons('snver_file_type',
"Output file type",
c(".vcf",".txt"),".vcf",
inline=TRUE)})
output$snverUI3<-renderUI({
conditionalPanel(
condition="input.snver_file_type=='.txt'",
numericInput('snver_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('snver_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('snver_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('snver_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$snverUI4<-renderUI({textInput('snver_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$snverUI5<-renderUI({radioButtons('snver_mnvs',
'MNVs reported?',
c("Yes","No"),"No",
inline = TRUE)})
output$snverUI6<-renderUI({radioButtons('snver_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),"No",
inline = TRUE)})
output$snverUI7<-renderUI({conditionalPanel(
condition="input.snver_snv_indel=='No'",
textInput('snver_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
".snv.filter"),
textInput('snver_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
".indel.filter"))})
output$snverUI8<-renderUI({radioButtons('snver_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected="CA>C",
inline = TRUE)})
})
observeEvent(input$snver_remove,{
output$snverUI1<-renderUI({NULL})
output$snverUI2<-renderUI({NULL})
output$snverUI3<-renderUI({NULL})
output$snverUI4<-renderUI({NULL})
output$snverUI5<-renderUI({NULL})
output$snverUI6<-renderUI({NULL})
output$snverUI7<-renderUI({NULL})
output$snverUI8<-renderUI({NULL})
})
observeEvent(input$samtools_add,{
output$samtoolsUI1<-renderUI({textInput('samtools_folder',
'Variant calling results',
"/home/samtools/")})
output$samtoolsUI2<-renderUI({radioButtons('samtools_file_type',
"Output file type",
c(".vcf",".txt"),
".vcf",
inline=TRUE)})
output$samtoolsUI3<-renderUI({
conditionalPanel(
condition="input.samtools_file_type=='.txt'",
numericInput('samtools_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('samtools_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('samtools_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('samtools_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$samtoolsUI4<-renderUI({textInput('samtools_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$samtoolsUI5<-renderUI({radioButtons('samtools_mnvs',
'MNVs reported?',
c("Yes","No"),"No",
inline = TRUE)})
output$samtoolsUI6<-renderUI({radioButtons('samtools_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),"Yes",
inline = TRUE)})
output$samtoolsUI7<-renderUI({conditionalPanel(
condition="input.samtools_snv_indel=='No'",
textInput('samtools_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
""),
textInput('samtools_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
""))})
output$samtoolsUI8<-renderUI({radioButtons('samtools_indels',
'How are Indels reported?',
c("CA>C","C>-A","CAAAC>CAAC"),
selected="CAAAC>CAAC",
inline = TRUE)})
})
observeEvent(input$samtools_remove,{
output$samtoolsUI1<-renderUI({NULL})
output$samtoolsUI2<-renderUI({NULL})
output$samtoolsUI3<-renderUI({NULL})
output$samtoolsUI4<-renderUI({NULL})
output$samtoolsUI5<-renderUI({NULL})
output$samtoolsUI6<-renderUI({NULL})
output$samtoolsUI7<-renderUI({NULL})
output$samtoolsUI8<-renderUI({NULL})
})
observeEvent(input$vardict_add,{
output$vardictUI1<-renderUI({textInput('vardict_folder',
'Variant calling results',
"/home/vardict/")})
output$vardictUI2<-renderUI({radioButtons('vardict_file_type',
"Output file type",
c(".vcf",".txt"),
".txt",inline=TRUE)})
output$vardictUI3<-renderUI({
conditionalPanel(
condition="input.vardict_file_type=='.txt'",
numericInput('vardict_chr',
"In which column do you find Chr?",
min = 1,max=20,value=3),
numericInput('vardict_pos',
"In which column do you find Pos?",
min = 1,max=20,value=4),
numericInput('vardict_ref',
"In which column do you find Ref?",
min = 1,max=20,value=6),
numericInput('vardict_alt',
"In which column do you find Alt?",
min = 1,max=20,value=7))})
output$vardictUI4<-renderUI({textInput('vardict_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$vardictUI5<-renderUI({radioButtons('vardict_mnvs',
'MNVs reported?',
c("Yes","No"),"Yes",
inline = TRUE)})
output$vardictUI6<-renderUI({radioButtons('vardict_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),"Yes",
inline = TRUE)})
output$vardictUI7<-renderUI({conditionalPanel(
condition="input.vardict_snv_indel=='No'",
textInput('vardict_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
""),
textInput('vardict_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
""))})
output$vardictUI8<-renderUI({radioButtons('vardict_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected="CA>C",
inline = TRUE)})
})
observeEvent(input$vardict_remove,{
output$vardictUI1<-renderUI({NULL})
output$vardictUI2<-renderUI({NULL})
output$vardictUI3<-renderUI({NULL})
output$vardictUI4<-renderUI({NULL})
output$vardictUI5<-renderUI({NULL})
output$vardictUI6<-renderUI({NULL})
output$vardictUI7<-renderUI({NULL})
output$vardictUI8<-renderUI({NULL})
})
observeEvent(input$nr_additional_action,{
output$caller1UI0<-renderUI({NULL})
output$caller1UI0.1<-renderUI({NULL})
output$caller1UI1<-renderUI({NULL})
output$caller1UI2<-renderUI({NULL})
output$caller1UI3<-renderUI({NULL})
output$caller1UI4<-renderUI({NULL})
output$caller1UI5<-renderUI({NULL})
output$caller1UI6<-renderUI({NULL})
output$caller1UI7<-renderUI({NULL})
output$caller1UI8<-renderUI({NULL})
output$caller2UI0<-renderUI({NULL})
output$caller2UI0.1<-renderUI({NULL})
output$caller2UI1<-renderUI({NULL})
output$caller2UI2<-renderUI({NULL})
output$caller2UI3<-renderUI({NULL})
output$caller2UI4<-renderUI({NULL})
output$caller2UI5<-renderUI({NULL})
output$caller2UI6<-renderUI({NULL})
output$caller2UI7<-renderUI({NULL})
output$caller2UI8<-renderUI({NULL})
output$caller3UI0<-renderUI({NULL})
output$caller3UI0.1<-renderUI({NULL})
output$caller3UI1<-renderUI({NULL})
output$caller3UI2<-renderUI({NULL})
output$caller3UI3<-renderUI({NULL})
output$caller3UI4<-renderUI({NULL})
output$caller3UI5<-renderUI({NULL})
output$caller3UI6<-renderUI({NULL})
output$caller3UI7<-renderUI({NULL})
output$caller3UI8<-renderUI({NULL})
output$caller4UI0<-renderUI({NULL})
output$caller4UI0.1<-renderUI({NULL})
output$caller4UI1<-renderUI({NULL})
output$caller4UI2<-renderUI({NULL})
output$caller4UI3<-renderUI({NULL})
output$caller4UI4<-renderUI({NULL})
output$caller4UI5<-renderUI({NULL})
output$caller4UI6<-renderUI({NULL})
output$caller4UI7<-renderUI({NULL})
output$caller4UI8<-renderUI({NULL})
output$caller5UI0<-renderUI({NULL})
output$caller5UI0.1<-renderUI({NULL})
output$caller5UI1<-renderUI({NULL})
output$caller5UI2<-renderUI({NULL})
output$caller5UI3<-renderUI({NULL})
output$caller5UI4<-renderUI({NULL})
output$caller5UI5<-renderUI({NULL})
output$caller5UI6<-renderUI({NULL})
output$caller5UI7<-renderUI({NULL})
output$caller5UI8<-renderUI({NULL})
if(input$nr_additional>0){
output$caller1UI0<-renderUI({h4("Caller 1:")})
output$caller1UI0.1<-renderUI({textInput('caller1_name',
'Name of caller 1',
"Caller 1")})
output$caller1UI1<-renderUI({textInput('caller1_folder',
'Variant calling results',
"/home/")})
output$caller1UI2<-renderUI({radioButtons('caller1_file_type',
"Output file type",
c(".vcf",".txt"),
".vcf",
inline=TRUE)})
output$caller1UI3<-renderUI({
conditionalPanel(
condition="input.caller1_file_type=='.txt'",
numericInput('caller1_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('caller1_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('caller1_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('caller1_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$caller1UI4<-renderUI({textInput('caller1_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
"")})
output$caller1UI5<-renderUI({radioButtons('caller1_mnvs',
'MNVs reported?',
c("Yes","No"),
"No",
inline = TRUE)})
output$caller1UI6<-renderUI({radioButtons('caller1_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
"Yes",
inline = TRUE)})
output$caller1UI7<-renderUI({conditionalPanel(
condition="input.caller1_snv_indel=='No'",
textInput('caller1_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
""),
textInput('caller1_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
""))})
output$caller1UI8<-renderUI({radioButtons('caller1_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected="CA>C",
inline = TRUE)})
if(input$nr_additional>1){
output$caller2UI0<-renderUI({h4("Caller 2:")})
output$caller2UI0.1<-renderUI({textInput('caller2_name',
'Name of caller 2',
"Caller 2")})
output$caller2UI1<-renderUI({textInput('caller2_folder',
'Variant calling results',
"/home/")})
output$caller2UI2<-renderUI({radioButtons('caller2_file_type',
"Output file type",
c(".vcf",
".txt"),
".vcf",
inline=TRUE)})
output$caller2UI3<-renderUI({
conditionalPanel(
condition="input.caller2_file_type=='.txt'",
numericInput('caller2_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('caller2_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('caller2_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('caller2_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$caller2UI4<-renderUI({textInput('caller2_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$caller2UI5<-renderUI({radioButtons('caller2_mnvs',
'MNVs reported?',
c("Yes","No"),
"No",
inline=TRUE)})
output$caller2UI6<-renderUI({radioButtons('caller2_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
"Yes",
inline=TRUE)})
output$caller2UI7<-renderUI({conditionalPanel(
condition="input.caller2_snv_indel=='No'",
textInput('caller2_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
""),
textInput('caller2_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
""))})
output$caller2UI8<-renderUI({radioButtons('caller2_indels',
'How are Indels reported?',
c("CA>C",
"C>-A",
"CAAAC>CAAC"),
selected="CA>C",
inline=TRUE)})
if(input$nr_additional>2){
output$caller3UI0<-renderUI({h4("Caller 3:")})
output$caller3UI0.1<-renderUI({textInput('caller3_name',
'Name of caller 3',
"Caller 3")})
output$caller3UI1<-renderUI({textInput('caller3_folder',
'Variant calling results',
"/home/")})
output$caller3UI2<-renderUI({radioButtons('caller3_file_type',
"Output file type",
c(".vcf",
".txt"),
".vcf",
inline=TRUE)})
output$caller3UI3<-renderUI({
conditionalPanel(
condition="input.caller3_file_type=='.txt'",
numericInput('caller3_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('caller3_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('caller3_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('caller3_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$caller3UI4<-renderUI({textInput('caller3_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$caller3UI5<-renderUI({radioButtons('caller3_mnvs',
'MNVs reported?',
c("Yes","No"),
"No",
inline = TRUE)})
output$caller3UI6<-renderUI({radioButtons('caller3_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
"Yes",
inline = TRUE)})
output$caller3UI7<-renderUI({conditionalPanel(
condition="input.caller3_snv_indel=='No'",
textInput('caller3_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
""),
textInput('caller3_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
""))})
output$caller3UI8<-renderUI({radioButtons('caller3_indels',
'How are Indels reported?',
c("CA>C","C>-A","CAAAC>CAAC"),
selected="CA>C",
inline = TRUE)})
if(input$nr_additional>3){
output$caller4UI0<-renderUI({h4("Caller 4:")})
output$caller4UI0.1<-renderUI({textInput('caller4_name',
'Name of caller 4',
"Caller 4")})
output$caller4UI1<-renderUI({textInput('caller4_folder',
'Variant calling results',
"/home/")})
output$caller4UI2<-renderUI({radioButtons('caller4_file_type',
"Output file type",
c(".vcf",".txt"),
".vcf",
inline=TRUE)})
output$caller4UI3<-renderUI({
conditionalPanel(
condition="input.caller4_file_type=='.txt'",
numericInput('caller4_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('caller4_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('caller4_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('caller4_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$caller4UI4<-renderUI({textInput('caller4_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$caller4UI5<-renderUI({radioButtons('caller4_mnvs',
'MNVs reported?',
c("Yes","No"),
"No",
inline=TRUE)})
output$caller4UI6<-renderUI({radioButtons('caller4_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
"Yes",
inline=TRUE)})
output$caller4UI7<-renderUI({conditionalPanel(
condition="input.caller4_snv_indel=='No'",
textInput('caller4_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',""),
textInput('caller4_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',""))})
output$caller4UI8<-renderUI({radioButtons('caller4_indels',
'How are Indels reported?',
c("CA>C","C>-A","CAAAC>CAAC"),
selected="CA>C",
inline=TRUE)})
if(input$nr_additional>4){
output$caller5UI0<-renderUI({h4("Caller 5:")})
output$caller5UI0.1<-renderUI({textInput('caller5_name',
'Name of caller 5',
"Caller 5")})
output$caller5UI1<-renderUI({textInput('caller5_folder',
'Variant calling results',
"/home/")})
output$caller5UI2<-renderUI({radioButtons('caller5_file_type',
"Output file type",
c(".vcf",".txt"),
".vcf",
inline=TRUE)})
output$caller5UI3<-renderUI({
conditionalPanel(
condition="input.caller5_file_type=='.txt'",
numericInput('caller5_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=1),
numericInput('caller5_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=2),
numericInput('caller5_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=3),
numericInput('caller5_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=4))})
output$caller5UI4<-renderUI({textInput('caller5_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$caller5UI5<-renderUI({radioButtons('caller5_mnvs',
'MNVs reported?',
c("Yes","No"),
"No",
inline=TRUE)})
output$caller5UI6<-renderUI({radioButtons('caller5_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
"Yes",
inline=TRUE)})
output$caller5UI7<-renderUI({conditionalPanel(
condition="input.caller5_snv_indel=='No'",
textInput('caller5_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
""),
textInput('caller5_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
""))})
output$caller5UI8<-renderUI({radioButtons('caller5_indels',
'How are Indels reported?',
c("CA>C","C>-A","CAAAC>CAAC"),
selected="CA>C",
inline=TRUE)})
}
}
}
}
}
})
observeEvent(input$checkpointCheck,{
output$messageUI1<-renderUI({NULL})
output$messageUI2<-renderUI({NULL})
if(file.exists(paste(input$output_folder,
"/checkpoint.txt",sep=""))){
checkpointFile<-read.table(paste(input$output_folder,
"/checkpoint.txt",sep=""),
header=TRUE,sep="\t",
stringsAsFactors = FALSE)
minimumProgress<-min(checkpointFile[,2:length(checkpointFile[1,])],
na.rm = TRUE)
if(minimumProgress==1){
output$checkpointUI1<-renderUI({selectInput('checkpoint',
"",
choices=c("1: After target filtration"=1))})
}
if(minimumProgress==2){
output$checkpointUI1<-renderUI({selectInput('checkpoint',
"",
choices=c("1: After target filtration"=1,
"2: After normalization"=2))})
}
if(minimumProgress==3){
output$checkpointUI1<-renderUI({selectInput('checkpoint',
"",
choices=c("1: After target filtration"=1,
"2: After normalization"=2,
"3: After annotation"=3))})
}
if(minimumProgress==4){
output$checkpointUI1<-renderUI({selectInput('checkpoint',
"",
choices=c("1: After target filtration"=1,
"2: After normalization"=2,
"3: After annotation"=3,
"4: After combination"=4))})
}
if(minimumProgress==5){
output$checkpointUI1<-renderUI({selectInput('checkpoint',
"",
choices=c("1: After target filtration"=1,
"2: After normalization"=2,
"3: After annotation"=3,
"4: After combination"=4,
"5: After coverage and BQ filtration"=5))})
}
if(minimumProgress==6){
output$checkpointUI1<-renderUI({selectInput('checkpoint',
"",
choices=c("1: After target filtration"=1,
"2: After normalization"=2,
"3: After annotation"=3,
"4: After combination"=4,
"5: After coverage and BQ filtration"=5,
"6: After extended set of characteristics"=6))})
}
if(minimumProgress==7){
output$checkpointUI1<-renderUI({selectInput('checkpoint',
"",
choices=c("1: After target filtration"=1,
"2: After normalization"=2,
"3: After annotation"=3,
"4: After combination"=4,
"5: After coverage and BQ filtration"=5,
"6: After extended set of characteristics"=6,
"7: After final filtration"=7))})
}
output$checkpointUI2<-renderUI({actionButton("appreci8Rcheckpoint",
'Start analysis from selected checkpoint')})
}
if(!file.exists(paste(input$output_folder,"/checkpoint.txt",
sep=""))){
output$checkpointUI1<-renderUI({selectInput('checkpoint',"",
choices=c("Sorry, no checkpoint available"=0),
"Sorry, no checkpoint available")})
output$checkpointUI2<-renderUI({NULL})
}
})
#0. Preparation
output$output_folderUI<-renderUI({textInput('output_folder',
'Define output folder',
"/home/documents")})
#3. Annotate
output$locationsUI<-renderUI({checkboxGroupInput("locations",
"What are the locations you are interested in?",
c("coding",
"intron",
"threeUTR",
"fiveUTR",
"intergenic",
"spliceSite",
"promoter"),
c("coding"),
inline=TRUE)})
output$consequencesUI<-renderUI({checkboxGroupInput("consequences",
"What kind of variants are you interested in? (coding only)",
c("synonymous",
"nonsynonymous",
"frameshift",
"nonsense",
"not translated"),
c("nonsynonymous",
"frameshift",
"nonsense"),
inline=TRUE)})
#5. Coverage and BQ
output$bam_folderUI<-renderUI({textInput('bam_folder',
'Define folder containing bam- and bai files',"/home/alignment/")})
output$dpUI<-renderUI({numericInput("dp",
"Minimum coverage [10;9999]",
value=50,min=10,max=9999)})
output$nr_altUI<-renderUI({numericInput("nr_alt",
"Minimum number of reads carrying the alternate allele [3;9999]",
value=20,min=3,max=9999)})
output$vafUI<-renderUI({sliderInput("vaf",
"Minimum allele frequency [%]",
min=1,max=100,value=1)})
output$bqUI<-renderUI({numericInput("bq",
"Minimum base quality [0;40]",
value=15,min=0,max=40)})
output$bq_diffUI<-renderUI({numericInput("bq_diff",
"Maximum difference between Ref_BQ and Alt_BQ [0;40]",
value=7,min=0,max=40)})
#6. Characteristics
output$dbSNPUI<-renderUI({checkboxInput("dbSNP",
"Consider dbSNP? (Hsapiens.dbSNP144.GRCh37 and XtraSNPlocs.Hsapiens.dbSNP144.GRCh37)",
value=TRUE)})
output$"1kgenomesUI"<-renderUI({checkboxInput("1kgenomes",
"Consider 1000 Genomes? (MafDb.1Kgenomes.phase3.hs37d5)",
value=TRUE)})
output$exacUI<-renderUI({checkboxInput("exac",
"Consider ExAC? (MafDb.ExAC.r1.0.hs37d5)",
value=TRUE)})
output$gadUI<-renderUI({checkboxInput("gad",
"Consider Genome Aggregation Database? (MafDb.gnomADex.r2.1.hs37d5)",
value=TRUE)})
output$cosmicUI<-renderUI({checkboxInput("cosmic",
"Consider COSMIC? (COSMIC.67)",
value=TRUE)})
output$clinvarUI<-renderUI({checkboxInput("clinvar",
"Consider ClinVar? (rentrez)",
value=TRUE)})
output$predictUI<-renderUI({radioButtons("predict",
"What source would you like to use for impact prediction?",
c("SIFT","Provean",
"PolyPhen2"),
"Provean",inline=TRUE)})
#7. Filtration
output$stricter_thresholdsUI<-renderUI({radioButtons('stricter_thresholds',
"Do you want to define stricter thresholds for coverage and base quality?",
c("Yes","No"),
"No",
inline=TRUE)})
output$stricter_thresholdsUI2<-renderUI({conditionalPanel(
condition="input.stricter_thresholds=='Yes'",
numericInput("dp2","Minimum coverage [10;9999]",
value=50,min=10,max=9999),
numericInput("nr_alt2",
"Minimum number of reads carrying the alternate allele [3;9999]",
value=20,min=3,max=9999),
sliderInput("vaf2","Minimum allele frequency [%]",
min=1,max=100,value=1),
numericInput("bq2","Minimum base quality [0;36]",
value=15,min=0,max=36),
numericInput("bq_diff2",
"Maximum difference between Ref_BQ and Alt_BQ [0;36]",
value=7,min=0,max=36)
)})
output$nr_samplesUI<-renderUI({numericInput("nr_samples",
"Detection in more than how many samples makes a call striking?",
value=3,min=1,
max=9999)})
output$predictionUI1<-renderUI({conditionalPanel(
condition="input.predict=='SIFT'",
sliderInput("damaging_safe1",
"SIFT: When is a damaging prediction reliable? (internal threshold <=0.05)",
min=0,max=1.0,value=0.05),
sliderInput("tolerated_safe1",
"SIFT: When is a tolerated prediction reliable? (internal threshold >0.05)",
min=0,max=1.0,value=0.05)
)})
output$predictionUI2<-renderUI({conditionalPanel(
condition="input.predict=='Provean'",
sliderInput("damaging_safe2",
"Provean: When is a damaging prediction reliable? (internal threshold <=-2.5)",
min=-20,max=10,value=-3),
sliderInput("tolerated_safe2",
"Provean: When is a tolerated prediction reliable? (internal threshold >-2.5)",
min=-20,max=10,value=-1.5)
)})
output$predictionUI3<-renderUI({conditionalPanel(
condition="input.predict=='PolyPhen2'",
sliderInput("damaging_safe3",
"PolyPhen2: When is a damaging prediction reliable? (>=0.5)",
min=0,max=1,value=0.5),
sliderInput("tolerated_safe3",
"PolyPhen2: When is a tolerated prediction reliable? (<0.5)",
min=0,max=1,value=0.5)
)})
output$artifact_scoreUI<-renderUI({radioButtons('artifact_score',
"Would you like to change the default scoring for the artifact score?",
c("Yes","No"),"No",
inline=TRUE)})
output$artifact_scoreUI2<-renderUI({conditionalPanel(
condition="input.artifact_score=='Yes'",
h4("Important note:"),
h5("High score -> artifact"),
h5("Low score -> probably true"),
sliderInput("PolymorphismVAF10",
"Polymorphism (based on polymorphism score) AND VAF<10%",
min=-5,max=5,value=5),
sliderInput("BQ_AltMean","BQ_Alt<(mean(BQ_Alt)-3*sd(BQ_Alt))",
min=-5,max=5,value=4),
sliderInput("detectedHigh","Detected in >50% of all samples",
min=-5,max=5,value=2),
sliderInput("detectedLow",
"Detected in a striking number of samples",
min=-5,max=5,value=2),
sliderInput("detectedLowVAF",
"Detected in a striking number of samples AND VAF>85%",
min=-5,max=5,value=2),
sliderInput("vafLow","VAF<2%",min=-5,max=5,value=2),
sliderInput("PolymorphismVAF20",
"Polymorphism (based on polymorphism score) AND VAF<20%",
min=-5,max=5,value=2),
sliderInput("PolymorphismFrame",
"Polymorphism (based on polymorphism score) AND frameshift",
min=-5,max=5,value=2),
sliderInput("isIndel","Indel",min=-5,max=5,value=1),
sliderInput("isIndelVAF","Indel AND VAF<5%",
min=-5,max=5,value=1),
sliderInput("noPrimerP","No primer (information) AND p<0.001",
min=-5,max=5,value=1),
sliderInput("noPrimerPFwd",
"No primer (information) AND p>=0.001 AND Nr_Ref_fwd>=(Min_DP-Min_Alt)/2 AND Nr_Alt_fwd<=2",
min=-5,max=5,value=1),
sliderInput("noPrimerPRev",
"No primer (information) AND p>=0.001 AND Nr_Ref_rev>=(Min_DP-Min_Alt)/2 AND Nr_Alt_rev<=2",
min=-5,max=5,value=1),
sliderInput("databaseVAF","No database AND VAF<10%",
min=-5,max=5,value=1),
sliderInput("databaseHigh",
"No database AND detected in >50% of all samples",
min=-5,max=5,value=1),
sliderInput("predictionVAF",
"Reliable tolerated prediction AND (VAF<35% OR 65%<VAF<85%)",
min=-5,max=5,value=1),
sliderInput("oneCaller","Reported by only 1 caller",
min=-5,max=5,value=1),
sliderInput("primerLocation","Primer-location",
min=-5,max=5,value=-1),
sliderInput("primerPAlt",
"No primer (information) AND p<0.001 AND Nr_Alt_fwd>=Min_Alt/2 AND Nr_Alt_rev>=Min_Alt/2",
min=-5,max=5,value=-1),
sliderInput("primerPFwd",
"No primer (information) AND p<0.001 AND Nr_Ref_fwd<(Min_DP-Min_Alt)/2 AND Nr_Alt_fwd<=2",
min=-5,max=5,value=-1),
sliderInput("primerPRev",
"No primer (information) AND p<0.001 AND Nr_Ref_rev<(Min_DP-Min_Alt)/2 AND Nr_Alt_rev<=2",
min=-5,max=5,value=-1),
sliderInput("predictionSafe","Reliable damaging prediction",
min=-5,max=5,value=-1),
numericInput("nrcaller4",
"Intermediate number of callers to report the same variant [1;14]",
min=1,max=14,value=4),
sliderInput("reward4","Score",min=-5,max=5,value=-1),
numericInput("nrcaller5",
"High number of callers to report the same variant [1;14]",
min=1,max=14,value=5),
sliderInput("reward5","Score",min=-5,max=5,value=-1),
numericInput("nrcaller6",
"Very high number of callers to report the same variant [1;14]",
min=1,max=14,value=6),
sliderInput("reward6","Score",min=-5,max=5,value=-1),
sliderInput("knownHotspot","Known hotspot",
min=-5,max=5,value=-3),
checkboxGroupInput("overlapTools",
"Overlapping output by which tools shall be rewarded?",
choices=c("GATK","Platypus","VarScan",
"LoFreq","FreeBayes","SNVer",
"SamTools","VarDict","Caller1",
"Caller2","Caller3","Caller4",
"Caller5"),
selected=c("LoFreq","FreeBayes","VarDict"),
inline=TRUE),
sliderInput("overlapReward","Score",min=-5,max=5,value=-3),
hr(),
sliderInput("artifactThreshold",
"Threshold artifact score (still artifact)",
min=-10,max=10,value=0)
)})
output$polymorphism_scoreUI<-renderUI({radioButtons('polymorphism_score',
"Would you like to change the default scoring for the polymorphism score?",
c("Yes","No"),
"No",
inline=TRUE)})
output$polymorphism_scoreUI2<-renderUI({conditionalPanel(
condition="input.polymorphism_score=='Yes'",
h4("Important note:"),
h5("High score -> polymorphism"),
h5("Low score -> no polymorphism"),
sliderInput("polyDetected",
"Detected in a striking number of samples",
min=-5,max=5,value=1),
numericInput("polyDatabases",
"High number of databases to have information on a variant [1;8]",
min=1,max=8,value=6),
sliderInput("polyDatabasesReward","Score",min=-5,max=5,value=1),
numericInput("polyDatabasesPolyLow",
"Intermediate number of polymorphism databases to have information on a variant [1;8]",
min=1,max=8,value=2),
sliderInput("polyDatabasesPolyLowReward","Score",
min=-5,max=5,value=1),
numericInput("polyDatabasesPolyHigh",
"High number of polymorphism databases to have information on a variant [1;8]",
min=1,max=8,value=4),
sliderInput("polyDatabasesPolyHighReward","Score",
min=-5,max=5,value=1),
sliderInput("polyVAF","35%<=VAF>=65% OR 85%<=VAF",
min=-5,max=5,value=1),
sliderInput("polyPrediction","Reliable tolerated prediction",
min=-5,max=5,value=1),
sliderInput("polyEffect",
"No frameshift AND no stop gained AND no stop lost",
min=-5,max=5,value=1),
sliderInput("polyDetectedOnce","Reported in only 1 sample",
min=-5,max=5,value=-1),
numericInput("polyDatabasesMut",
"Critical number of mutation databases to have information on a variant [1;8]",
min=1,max=8,value=2),
sliderInput("polyDatabasesMutReward","Score",
min=-5,max=5,value=-1),
sliderInput("polyNoDatabase",
"Not detected in any polymorphism database",
min=-5,max=5,value=-1),
sliderInput("polyPredictionEffect",
"Reliable damaging prediction OR stop gained OR stop lost",
min=-5,max=5,value=-1),
numericInput("polyCosmic",
"Critical number of Cosmic entries [1;1000]",
min=1,max=1000,value=100),
hr(),
sliderInput("polyThresholdCritical",
"Threshold polymorphism score if number of Cosmic entries is not critical (still polymorphism)",
min=-10,max=10,value=2),
sliderInput("polyThreshold",
"Threshold polymorphism score if number of Cosmic entries is critical (still polymorphism)",
min=-10,max=10,value=3)
)})
observeEvent(input$exportConfig,{
output$exportconfigUI0<-renderUI({h4('Important note:')})
output$exportconfigUI0.1<-renderUI({h5('Information on uploaded files (target region, primer positions or hotspot list) cannot be exported/imported.')})
output$exportconfigUI1<-renderUI({textInput('configFileOut',
'Define file name for your configuration file (will be safed as *.txt file in your output folder)',
"Config1")})
output$exportconfigUI2<-renderUI({actionButton("safeConfig",
'Safe configuration')})
output$messageUI1<-renderUI({NULL})
output$messageUI2<-renderUI({NULL})
output$importconfigUI0<-renderUI({NULL})
output$importconfigUI0.1<-renderUI({NULL})
output$importconfigUI1<-renderUI({NULL})
output$importconfigUI2<-renderUI({NULL})
})
observeEvent(input$importConfig,{
output$importconfigUI0<-renderUI({h4('Important note:')})
output$importconfigUI0.1<-renderUI({h5('Information on uploaded files (target region, primer positions or hotspot list) cannot be exported/imported.')})
output$importconfigUI1<-renderUI({fileInput('configFileIn',
'Upload your configuration file')})
output$importconfigUI2<-renderUI({actionButton("applyConfig",
'Apply configuration')})
output$messageUI2<-renderUI({NULL})
output$messageUI1<-renderUI({NULL})
output$exportconfigUI0<-renderUI({NULL})
output$exportconfigUI0.1<-renderUI({NULL})
output$exportconfigUI1<-renderUI({NULL})
output$exportconfigUI2<-renderUI({NULL})
})
observeEvent(input$safeConfig,{
#check if output-folder really exists
if(file.exists(input$output_folder)==FALSE){
log_info<-c("Your output folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(file.exists(input$output_folder)==TRUE){
log_info<-paste("Saving your current setting as ",
input$configFileOut,".txt<br><br>",sep="")
output$log_info<-renderUI({HTML(log_info)})
config<-data.frame(Variable=NA,Value=NA)
#GATK
config[1,1]<-"gatk_folder"
config[1,2]<-ifelse(!is.null(input$gatk_folder),
input$gatk_folder,NA)
config[2,1]<-"gatk_file_type"
config[2,2]<-ifelse(!is.null(input$gatk_file_type),
input$gatk_file_type,NA)
config[3,1]<-"gatk_chr"
config[3,2]<-ifelse(!is.null(input$gatk_chr),
input$gatk_chr,NA)
config[4,1]<-"gatk_pos"
config[4,2]<-ifelse(!is.null(input$gatk_pos),
input$gatk_pos,NA)
config[5,1]<-"gatk_ref"
config[5,2]<-ifelse(!is.null(input$gatk_ref),
input$gatk_ref,NA)
config[6,1]<-"gatk_alt"
config[6,2]<-ifelse(!is.null(input$gatk_alt),
input$gatk_alt,NA)
config[7,1]<-"gatk_file_names_add"
config[7,2]<-ifelse(!is.null(input$gatk_file_names_add),
input$gatk_file_names_add,NA)
config[8,1]<-"gatk_mnvs"
config[8,2]<-ifelse(!is.null(input$gatk_mnvs),
input$gatk_mnvs,NA)
config[9,1]<-"gatk_snv_indel"
config[9,2]<-ifelse(!is.null(input$gatk_snv_indel),
input$gatk_snv_indel,NA)
config[10,1]<-"gatk_snv_names_add"
config[10,2]<-ifelse(!is.null(input$gatk_snv_names_add),
input$gatk_snv_names_add,NA)
config[11,1]<-"gatk_indel_names_add"
config[11,2]<-ifelse(!is.null(input$gatk_indel_names_add),
input$gatk_indel_names_add,NA)
config[12,1]<-"gatk_indels"
config[12,2]<-ifelse(!is.null(input$gatk_indels),
input$gatk_indels,NA)
#Platypus
config[13,1]<-"platypus_folder"
config[13,2]<-ifelse(!is.null(input$platypus_folder),
input$platypus_folder,NA)
config[14,1]<-"platypus_file_type"
config[14,2]<-ifelse(!is.null(input$platypus_file_type),
input$platypus_file_type,NA)
config[15,1]<-"platypus_chr"
config[15,2]<-ifelse(!is.null(input$platypus_chr),
input$platypus_chr,NA)
config[16,1]<-"platypus_pos"
config[16,2]<-ifelse(!is.null(input$platypus_pos),
input$platypus_pos,NA)
config[17,1]<-"platypus_ref"
config[17,2]<-ifelse(!is.null(input$platypus_ref),
input$platypus_ref,NA)
config[18,1]<-"platypus_alt"
config[18,2]<-ifelse(!is.null(input$platypus_alt),
input$platypus_alt,NA)
config[19,1]<-"platypus_file_names_add"
config[19,2]<-ifelse(!is.null(input$platypus_file_names_add),
input$platypus_file_names_add,NA)
config[20,1]<-"platypus_mnvs"
config[20,2]<-ifelse(!is.null(input$platypus_mnvs),
input$platypus_mnvs,NA)
config[21,1]<-"platypus_snv_indel"
config[21,2]<-ifelse(!is.null(input$platypus_snv_indel),
input$platypus_snv_indel,NA)
config[22,1]<-"platypus_snv_names_add"
config[22,2]<-ifelse(!is.null(input$platypus_snv_names_add),
input$platypus_snv_names_add,NA)
config[23,1]<-"platypus_indel_names_add"
config[23,2]<-ifelse(!is.null(input$platypus_indel_names_add),
input$platypus_indel_names_add,NA)
config[24,1]<-"platypus_indels"
config[24,2]<-ifelse(!is.null(input$platypus_indels),
input$platypus_indels,NA)
#VarScan
config[25,1]<-"varscan_folder"
config[25,2]<-ifelse(!is.null(input$varscan_folder),
input$varscan_folder,NA)
config[26,1]<-"varscan_file_type"
config[26,2]<-ifelse(!is.null(input$varscan_file_type),
input$varscan_file_type,NA)
config[27,1]<-"varscan_chr"
config[27,2]<-ifelse(!is.null(input$varscan_chr),
input$varscan_chr,NA)
config[28,1]<-"varscan_pos"
config[28,2]<-ifelse(!is.null(input$varscan_pos),
input$varscan_pos,NA)
config[29,1]<-"varscan_ref"
config[29,2]<-ifelse(!is.null(input$varscan_ref),
input$varscan_ref,NA)
config[30,1]<-"varscan_alt"
config[30,2]<-ifelse(!is.null(input$varscan_alt),
input$varscan_alt,NA)
config[31,1]<-"varscan_file_names_add"
config[31,2]<-ifelse(!is.null(input$varscan_file_names_add),
input$varscan_file_names_add,NA)
config[32,1]<-"varscan_mnvs"
config[32,2]<-ifelse(!is.null(input$varscan_mnvs),
input$varscan_mnvs,NA)
config[33,1]<-"varscan_snv_indel"
config[33,2]<-ifelse(!is.null(input$varscan_snv_indel),
input$varscan_snv_indel,NA)
config[34,1]<-"varscan_snv_names_add"
config[34,2]<-ifelse(!is.null(input$varscan_snv_names_add),
input$varscan_snv_names_add,NA)
config[35,1]<-"varscan_indel_names_add"
config[35,2]<-ifelse(!is.null(input$varscan_indel_names_add),
input$varscan_indel_names_add,NA)
config[36,1]<-"varscan_indels"
config[36,2]<-ifelse(!is.null(input$varscan_indels),
input$varscan_indels,NA)
#FreeBayes
config[37,1]<-"freebayes_folder"
config[37,2]<-ifelse(!is.null(input$freebayes_folder),
input$freebayes_folder,NA)
config[38,1]<-"freebayes_file_type"
config[38,2]<-ifelse(!is.null(input$freebayes_file_type),
input$freebayes_file_type,NA)
config[39,1]<-"freebayes_chr"
config[39,2]<-ifelse(!is.null(input$freebayes_chr),
input$freebayes_chr,NA)
config[40,1]<-"freebayes_pos"
config[40,2]<-ifelse(!is.null(input$freebayes_pos),
input$freebayes_pos,NA)
config[41,1]<-"freebayes_ref"
config[41,2]<-ifelse(!is.null(input$freebayes_ref),
input$freebayes_ref,NA)
config[42,1]<-"freebayes_alt"
config[42,2]<-ifelse(!is.null(input$freebayes_alt),
input$freebayes_alt,NA)
config[43,1]<-"freebayes_file_names_add"
config[43,2]<-ifelse(!is.null(input$freebayes_file_names_add),
input$freebayes_file_names_add,NA)
config[44,1]<-"freebayes_mnvs"
config[44,2]<-ifelse(!is.null(input$freebayes_mnvs),
input$freebayes_mnvs,NA)
config[45,1]<-"freebayes_snv_indel"
config[45,2]<-ifelse(!is.null(input$freebayes_snv_indel),
input$freebayes_snv_indel,NA)
config[46,1]<-"freebayes_snv_names_add"
config[46,2]<-ifelse(!is.null(input$freebayes_snv_names_add),
input$freebayes_snv_names_add,NA)
config[47,1]<-"freebayes_indel_names_add"
config[47,2]<-ifelse(!is.null(input$freebayes_indel_names_add),
input$freebayes_indel_names_add,NA)
config[48,1]<-"freebayes_indels"
config[48,2]<-ifelse(!is.null(input$freebayes_indels),
input$freebayes_indels,NA)
#LoFreq
config[49,1]<-"lofreq_folder"
config[49,2]<-ifelse(!is.null(input$lofreq_folder),
input$lofreq_folder,NA)
config[50,1]<-"lofreq_file_type"
config[50,2]<-ifelse(!is.null(input$lofreq_file_type),
input$lofreq_file_type,NA)
config[51,1]<-"lofreq_chr"
config[51,2]<-ifelse(!is.null(input$lofreq_chr),
input$lofreq_chr,NA)
config[52,1]<-"lofreq_pos"
config[52,2]<-ifelse(!is.null(input$lofreq_pos),
input$lofreq_pos,NA)
config[53,1]<-"lofreq_ref"
config[53,2]<-ifelse(!is.null(input$lofreq_ref),
input$lofreq_ref,NA)
config[54,1]<-"lofreq_alt"
config[54,2]<-ifelse(!is.null(input$lofreq_alt),
input$lofreq_alt,NA)
config[55,1]<-"lofreq_file_names_add"
config[55,2]<-ifelse(!is.null(input$lofreq_file_names_add),
input$lofreq_file_names_add,NA)
config[56,1]<-"lofreq_mnvs"
config[56,2]<-ifelse(!is.null(input$lofreq_mnvs),
input$lofreq_mnvs,NA)
config[57,1]<-"lofreq_snv_indel"
config[57,2]<-ifelse(!is.null(input$lofreq_snv_indel),
input$lofreq_snv_indel,NA)
config[58,1]<-"lofreq_snv_names_add"
config[58,2]<-ifelse(!is.null(input$lofreq_snv_names_add),
input$lofreq_snv_names_add,NA)
config[59,1]<-"lofreq_indel_names_add"
config[59,2]<-ifelse(!is.null(input$lofreq_indel_names_add),
input$lofreq_indel_names_add,NA)
config[60,1]<-"lofreq_indels"
config[60,2]<-ifelse(!is.null(input$lofreq_indels),
input$lofreq_indels,NA)
#SNVer
config[61,1]<-"snver_folder"
config[61,2]<-ifelse(!is.null(input$snver_folder),
input$snver_folder,NA)
config[62,1]<-"snver_file_type"
config[62,2]<-ifelse(!is.null(input$snver_file_type),
input$snver_file_type,NA)
config[63,1]<-"snver_chr"
config[63,2]<-ifelse(!is.null(input$snver_chr),
input$snver_chr,NA)
config[64,1]<-"snver_pos"
config[64,2]<-ifelse(!is.null(input$snver_pos),
input$snver_pos,NA)
config[65,1]<-"snver_ref"
config[65,2]<-ifelse(!is.null(input$snver_ref),
input$snver_ref,NA)
config[66,1]<-"snver_alt"
config[66,2]<-ifelse(!is.null(input$snver_alt),
input$snver_alt,NA)
config[67,1]<-"snver_file_names_add"
config[67,2]<-ifelse(!is.null(input$snver_file_names_add),
input$snver_file_names_add,NA)
config[68,1]<-"snver_mnvs"
config[68,2]<-ifelse(!is.null(input$snver_mnvs),
input$snver_mnvs,NA)
config[69,1]<-"snver_snv_indel"
config[69,2]<-ifelse(!is.null(input$snver_snv_indel),
input$snver_snv_indel,NA)
config[70,1]<-"snver_snv_names_add"
config[70,2]<-ifelse(!is.null(input$snver_snv_names_add),
input$snver_snv_names_add,NA)
config[71,1]<-"snver_indel_names_add"
config[71,2]<-ifelse(!is.null(input$snver_indel_names_add),
input$snver_indel_names_add,NA)
config[72,1]<-"snver_indels"
config[72,2]<-ifelse(!is.null(input$snver_indels),
input$snver_indels,NA)
#SamTools
config[73,1]<-"samtools_folder"
config[73,2]<-ifelse(!is.null(input$samtools_folder),
input$samtools_folder,NA)
config[74,1]<-"samtools_file_type"
config[74,2]<-ifelse(!is.null(input$samtools_file_type),
input$samtools_file_type,NA)
config[75,1]<-"samtools_chr"
config[75,2]<-ifelse(!is.null(input$samtools_chr),
input$samtools_chr,NA)
config[76,1]<-"samtools_pos"
config[76,2]<-ifelse(!is.null(input$samtools_pos),
input$samtools_pos,NA)
config[77,1]<-"samtools_ref"
config[77,2]<-ifelse(!is.null(input$samtools_ref),
input$samtools_ref,NA)
config[78,1]<-"samtools_alt"
config[78,2]<-ifelse(!is.null(input$samtools_alt),
input$samtools_alt,NA)
config[79,1]<-"samtools_file_names_add"
config[79,2]<-ifelse(!is.null(input$samtools_file_names_add),
input$samtools_file_names_add,NA)
config[80,1]<-"samtools_mnvs"
config[80,2]<-ifelse(!is.null(input$samtools_mnvs),
input$samtools_mnvs,NA)
config[81,1]<-"samtools_snv_indel"
config[81,2]<-ifelse(!is.null(input$samtools_snv_indel),
input$samtools_snv_indel,NA)
config[82,1]<-"samtools_snv_names_add"
config[82,2]<-ifelse(!is.null(input$samtools_snv_names_add),
input$samtools_snv_names_add,NA)
config[83,1]<-"samtools_indel_names_add"
config[83,2]<-ifelse(!is.null(input$samtools_indel_names_add),
input$samtools_indel_names_add,NA)
config[84,1]<-"samtools_indels"
config[84,2]<-ifelse(!is.null(input$samtools_indels),
input$samtools_indels,NA)
#VarDict
config[85,1]<-"vardict_folder"
config[85,2]<-ifelse(!is.null(input$vardict_folder),
input$vardict_folder,NA)
config[86,1]<-"vardict_file_type"
config[86,2]<-ifelse(!is.null(input$vardict_file_type),
input$vardict_file_type,NA)
config[87,1]<-"vardict_chr"
config[87,2]<-ifelse(!is.null(input$vardict_chr),
input$vardict_chr,NA)
config[88,1]<-"vardict_pos"
config[88,2]<-ifelse(!is.null(input$vardict_pos),
input$vardict_pos,NA)
config[89,1]<-"vardict_ref"
config[89,2]<-ifelse(!is.null(input$vardict_ref),
input$vardict_ref,NA)
config[90,1]<-"vardict_alt"
config[90,2]<-ifelse(!is.null(input$vardict_alt),
input$vardict_alt,NA)
config[91,1]<-"vardict_file_names_add"
config[91,2]<-ifelse(!is.null(input$vardict_file_names_add),
input$vardict_file_names_add,NA)
config[92,1]<-"vardict_mnvs"
config[92,2]<-ifelse(!is.null(input$vardict_mnvs),
input$vardict_mnvs,NA)
config[93,1]<-"vardict_snv_indel"
config[93,2]<-ifelse(!is.null(input$vardict_snv_indel),
input$vardict_snv_indel,NA)
config[94,1]<-"vardict_snv_names_add"
config[94,2]<-ifelse(!is.null(input$vardict_snv_names_add),
input$vardict_snv_names_add,NA)
config[95,1]<-"vardict_indel_names_add"
config[95,2]<-ifelse(!is.null(input$vardict_indel_names_add),
input$vardict_indel_names_add,NA)
config[96,1]<-"vardict_indels"
config[96,2]<-ifelse(!is.null(input$vardict_indels),
input$vardict_indels,NA)
#additional callers
#caller1
config[97,1]<-"caller1_h4"
config[97,2]<-ifelse(input$nr_additional>0,"Caller 1:",NA)
config[98,1]<-"caller1_name"
config[98,2]<-ifelse(!is.null(input$caller1_name),
input$caller1_name,NA)
config[99,1]<-"caller1_folder"
config[99,2]<-ifelse(!is.null(input$caller1_folder),
input$caller1_folder,NA)
config[100,1]<-"caller1_file_type"
config[100,2]<-ifelse(!is.null(input$caller1_file_type),
input$caller1_file_type,NA)
config[101,1]<-"caller1_chr"
config[101,2]<-ifelse(!is.null(input$caller1_chr),
input$caller1_chr,NA)
config[102,1]<-"caller1_pos"
config[102,2]<-ifelse(!is.null(input$caller1_pos),
input$caller1_pos,NA)
config[103,1]<-"caller1_ref"
config[103,2]<-ifelse(!is.null(input$caller1_ref),
input$caller1_ref,NA)
config[104,1]<-"caller1_alt"
config[104,2]<-ifelse(!is.null(input$caller1_alt),
input$caller1_alt,NA)
config[105,1]<-"caller1_file_names_add"
config[105,2]<-ifelse(!is.null(input$caller1_file_names_add),
input$caller1_file_names_add,NA)
config[106,1]<-"caller1_mnvs"
config[106,2]<-ifelse(!is.null(input$caller1_mnvs),
input$caller1_mnvs,NA)
config[107,1]<-"caller1_snv_indel"
config[107,2]<-ifelse(!is.null(input$caller1_snv_indel),
input$caller1_snv_indel,NA)
config[108,1]<-"caller1_snv_names_add"
config[108,2]<-ifelse(!is.null(input$caller1_snv_names_add),
input$caller1_snv_names_add,NA)
config[109,1]<-"caller1_indel_names_add"
config[109,2]<-ifelse(!is.null(input$caller1_indel_names_add),
input$caller1_indel_names_add,NA)
config[110,1]<-"caller1_indels"
config[110,2]<-ifelse(!is.null(input$caller1_indels),
input$caller1_indels,NA)
#caller2
config[111,1]<-"caller2_h4"
config[111,2]<-ifelse(input$nr_additional>1,"Caller 2:",NA)
config[112,1]<-"caller2_name"
config[112,2]<-ifelse(!is.null(input$caller2_name),
input$caller2_name,NA)
config[113,1]<-"caller2_folder"
config[113,2]<-ifelse(!is.null(input$caller2_folder),
input$caller2_folder,NA)
config[114,1]<-"caller2_file_type"
config[114,2]<-ifelse(!is.null(input$caller2_file_type),
input$caller2_file_type,NA)
config[115,1]<-"caller2_chr"
config[115,2]<-ifelse(!is.null(input$caller2_chr),
input$caller2_chr,NA)
config[116,1]<-"caller2_pos"
config[116,2]<-ifelse(!is.null(input$caller2_pos),
input$caller2_pos,NA)
config[117,1]<-"caller2_ref"
config[117,2]<-ifelse(!is.null(input$caller2_ref),
input$caller2_ref,NA)
config[118,1]<-"caller2_alt"
config[118,2]<-ifelse(!is.null(input$caller2_alt),
input$caller2_alt,NA)
config[119,1]<-"caller2_file_names_add"
config[119,2]<-ifelse(!is.null(input$caller2_file_names_add),
input$caller2_file_names_add,NA)
config[120,1]<-"caller2_mnvs"
config[120,2]<-ifelse(!is.null(input$caller2_mnvs),
input$caller2_mnvs,NA)
config[121,1]<-"caller2_snv_indel"
config[121,2]<-ifelse(!is.null(input$caller2_snv_indel),
input$caller2_snv_indel,NA)
config[122,1]<-"caller2_snv_names_add"
config[122,2]<-ifelse(!is.null(input$caller2_snv_names_add),
input$caller2_snv_names_add,NA)
config[123,1]<-"caller2_indel_names_add"
config[123,2]<-ifelse(!is.null(input$caller2_indel_names_add),
input$caller2_indel_names_add,NA)
config[124,1]<-"caller2_indels"
config[124,2]<-ifelse(!is.null(input$caller2_indels),
input$caller2_indels,NA)
#caller3
config[125,1]<-"caller3_h4"
config[125,2]<-ifelse(input$nr_additional>2,"Caller 3:",NA)
config[126,1]<-"caller3_name"
config[126,2]<-ifelse(!is.null(input$caller3_name),
input$caller3_name,NA)
config[127,1]<-"caller3_folder"
config[127,2]<-ifelse(!is.null(input$caller3_folder),
input$caller3_folder,NA)
config[128,1]<-"caller3_file_type"
config[128,2]<-ifelse(!is.null(input$caller3_file_type),
input$caller3_file_type,NA)
config[129,1]<-"caller3_chr"
config[129,2]<-ifelse(!is.null(input$caller3_chr),
input$caller3_chr,NA)
config[130,1]<-"caller3_pos"
config[130,2]<-ifelse(!is.null(input$caller3_pos),
input$caller3_pos,NA)
config[131,1]<-"caller3_ref"
config[131,2]<-ifelse(!is.null(input$caller3_ref),
input$caller3_ref,NA)
config[132,1]<-"caller3_alt"
config[132,2]<-ifelse(!is.null(input$caller3_alt),
input$caller3_alt,NA)
config[133,1]<-"caller3_file_names_add"
config[133,2]<-ifelse(!is.null(input$caller3_file_names_add),
input$caller3_file_names_add,NA)
config[134,1]<-"caller3_mnvs"
config[134,2]<-ifelse(!is.null(input$caller3_mnvs),
input$caller3_mnvs,NA)
config[135,1]<-"caller3_snv_indel"
config[135,2]<-ifelse(!is.null(input$caller3_snv_indel),
input$caller3_snv_indel,NA)
config[136,1]<-"caller3_snv_names_add"
config[136,2]<-ifelse(!is.null(input$caller3_snv_names_add),
input$caller3_snv_names_add,NA)
config[137,1]<-"caller3_indel_names_add"
config[137,2]<-ifelse(!is.null(input$caller3_indel_names_add),
input$caller3_indel_names_add,NA)
config[138,1]<-"caller3_indels"
config[138,2]<-ifelse(!is.null(input$caller3_indels),
input$caller3_indels,NA)
#caller4
config[139,1]<-"caller4_h4"
config[139,2]<-ifelse(input$nr_additional>3,"Caller 4:",NA)
config[140,1]<-"caller4_name"
config[140,2]<-ifelse(!is.null(input$caller4_name),
input$caller4_name,NA)
config[141,1]<-"caller4_folder"
config[141,2]<-ifelse(!is.null(input$caller4_folder),
input$caller4_folder,NA)
config[142,1]<-"caller4_file_type"
config[142,2]<-ifelse(!is.null(input$caller4_file_type),
input$caller4_file_type,NA)
config[143,1]<-"caller4_chr"
config[143,2]<-ifelse(!is.null(input$caller4_chr),
input$caller4_chr,NA)
config[144,1]<-"caller4_pos"
config[144,2]<-ifelse(!is.null(input$caller4_pos),
input$caller4_pos,NA)
config[145,1]<-"caller4_ref"
config[145,2]<-ifelse(!is.null(input$caller4_ref),
input$caller4_ref,NA)
config[146,1]<-"caller4_alt"
config[146,2]<-ifelse(!is.null(input$caller4_alt),
input$caller4_alt,NA)
config[147,1]<-"caller4_file_names_add"
config[147,2]<-ifelse(!is.null(input$caller4_file_names_add),
input$caller4_file_names_add,NA)
config[148,1]<-"caller4_mnvs"
config[148,2]<-ifelse(!is.null(input$caller4_mnvs),
input$caller4_mnvs,NA)
config[149,1]<-"caller4_snv_indel"
config[149,2]<-ifelse(!is.null(input$caller4_snv_indel),
input$caller4_snv_indel,NA)
config[150,1]<-"caller4_snv_names_add"
config[150,2]<-ifelse(!is.null(input$caller4_snv_names_add),
input$caller4_snv_names_add,NA)
config[151,1]<-"caller4_indel_names_add"
config[151,2]<-ifelse(!is.null(input$caller4_indel_names_add),
input$caller4_indel_names_add,NA)
config[152,1]<-"caller4_indels"
config[152,2]<-ifelse(!is.null(input$caller4_indels),
input$caller4_indels,NA)
#caller5
config[153,1]<-"caller5_h4"
config[153,2]<-ifelse(input$nr_additional>4,"Caller 5:",NA)
config[154,1]<-"caller5_name"
config[154,2]<-ifelse(!is.null(input$caller5_name),
input$caller5_name,NA)
config[155,1]<-"caller5_folder"
config[155,2]<-ifelse(!is.null(input$caller5_folder),
input$caller5_folder,NA)
config[156,1]<-"caller5_file_type"
config[156,2]<-ifelse(!is.null(input$caller5_file_type),
input$caller5_file_type,NA)
config[157,1]<-"caller5_chr"
config[157,2]<-ifelse(!is.null(input$caller5_chr),
input$caller5_chr,NA)
config[158,1]<-"caller5_pos"
config[158,2]<-ifelse(!is.null(input$caller5_pos),
input$caller5_pos,NA)
config[159,1]<-"caller5_ref"
config[159,2]<-ifelse(!is.null(input$caller5_ref),
input$caller5_ref,NA)
config[160,1]<-"caller5_alt"
config[160,2]<-ifelse(!is.null(input$caller5_alt),
input$caller5_alt,NA)
config[161,1]<-"caller5_file_names_add"
config[161,2]<-ifelse(!is.null(input$caller5_file_names_add),
input$caller5_file_names_add,NA)
config[162,1]<-"caller5_mnvs"
config[162,2]<-ifelse(!is.null(input$caller5_mnvs),
input$caller5_mnvs,NA)
config[163,1]<-"caller5_snv_indel"
config[163,2]<-ifelse(!is.null(input$caller5_snv_indel),
input$caller5_snv_indel,NA)
config[164,1]<-"caller5_snv_names_add"
config[164,2]<-ifelse(!is.null(input$caller5_snv_names_add),
input$caller5_snv_names_add,NA)
config[165,1]<-"caller5_indel_names_add"
config[165,2]<-ifelse(!is.null(input$caller5_indel_names_add),
input$caller5_indel_names_add,NA)
config[166,1]<-"caller5_indels"
config[166,2]<-ifelse(!is.null(input$caller5_indels),
input$caller5_indels,NA)
#3. Annotation
config[167,1]<-"locations"
config[167,2]<-paste(input$locations,collapse=",")
config[168,1]<-"consequences"
config[168,2]<-paste(input$consequences,collapse=",")
#5. Coverage and BQ
config[169,1]<-"bam_folder"
config[169,2]<-input$bam_folder
config[170,1]<-"dp"
config[170,2]<-input$dp
config[171,1]<-"nr_alt"
config[171,2]<-input$nr_alt
config[172,1]<-"vaf"
config[172,2]<-input$vaf
config[173,1]<-"bq"
config[173,2]<-input$bq
config[174,1]<-"bq_diff"
config[174,2]<-input$bq_diff
#6. Characteristics
config[175,1]<-"dbSNP"
config[175,2]<-ifelse(!is.null(input$dbSNP),input$dbSNP,NA)
config[176,1]<-"1kgenomes"
config[176,2]<-ifelse(!is.null(input$"1kgenomes"),
input$"1kgenomes",NA)
config[177,1]<-"exac"
config[177,2]<-ifelse(!is.null(input$exac),input$exac,NA)
config[178,1]<-"esp"
config[178,2]<-NA
config[179,1]<-"gad"
config[179,2]<-ifelse(!is.null(input$gad),input$gad,NA)
config[180,1]<-"cosmic"
config[180,2]<-ifelse(!is.null(input$cosmic),
input$cosmic,NA)
config[181,1]<-"clinvar"
config[181,2]<-ifelse(!is.null(input$clinvar),
input$clinvar,NA)
config[182,1]<-"predict"
config[182,2]<-ifelse(!is.null(input$predict),
input$predict,NA)
#7. Filtration
config[183,1]<-"stricter_thresholds"
config[183,2]<-input$stricter_thresholds
config[184,1]<-"dp2"
config[184,2]<-ifelse(input$stricter_thresholds=="Yes",
input$dp2,NA)
config[185,1]<-"nr_alt2"
config[185,2]<-ifelse(input$stricter_thresholds=="Yes",
input$nr_alt2,NA)
config[186,1]<-"vaf2"
config[186,2]<-ifelse(input$stricter_thresholds=="Yes",
input$vaf2,NA)
config[187,1]<-"bq2"
config[187,2]<-ifelse(input$stricter_thresholds=="Yes",
input$bq2,NA)
config[188,1]<-"bq_diff2"
config[188,2]<-ifelse(input$stricter_thresholds=="Yes",
input$bq_diff2,NA)
config[189,1]<-"nr_samples"
config[189,2]<-input$nr_samples
config[190,1]<-"damaging_safe1"
config[190,2]<-ifelse(!is.null(input$damaging_safe1),
as.character(input$damaging_safe1),
NA)
config[191,1]<-"tolerated_safe1"
config[191,2]<-ifelse(!is.null(input$tolerated_safe1),
as.character(input$tolerated_safe1),
NA)
config[192,1]<-"damaging_safe2"
config[192,2]<-ifelse(!is.null(input$damaging_safe2),
as.character(input$damaging_safe2),
NA)
config[193,1]<-"tolerated_safe2"
config[193,2]<-ifelse(!is.null(input$tolerated_safe2),
as.character(input$tolerated_safe2),
NA)
config[194,1]<-"damaging_safe3"
config[194,2]<-ifelse(!is.null(input$damaging_safe3),
as.character(input$damaging_safe3),
NA)
config[195,1]<-"tolerated_safe3"
config[195,2]<-ifelse(!is.null(input$tolerated_safe3),
as.character(input$tolerated_safe3),
NA)
config[196,1]<-"artifact_score"
config[196,2]<-input$artifact_score
config[197,1]<-"header1"
config[197,2]<-ifelse(input$artifact_score=="Yes",
"Important note:",NA)
config[198,1]<-"header2"
config[198,2]<-ifelse(input$artifact_score=="Yes",
"High score -> artifact",NA)
config[199,1]<-"header3"
config[199,2]<-ifelse(input$artifact_score=="Yes",
"Low score -> probably true",NA)
config[200,1]<-"PolymorphismVAF10"
config[200,2]<-ifelse(input$artifact_score=="Yes",
input$PolymorphismVAF10,NA)
config[201,1]<-"BQ_AltMean"
config[201,2]<-ifelse(input$artifact_score=="Yes",
input$BQ_AltMean,NA)
config[202,1]<-"detectedHigh"
config[202,2]<-ifelse(input$artifact_score=="Yes",
input$detectedHigh,NA)
config[203,1]<-"detectedLow"
config[203,2]<-ifelse(input$artifact_score=="Yes",
input$detectedLow,NA)
config[204,1]<-"detectedLowVAF"
config[204,2]<-ifelse(input$artifact_score=="Yes",
input$detectedLowVAF,NA)
config[205,1]<-"vafLow"
config[205,2]<-ifelse(input$artifact_score=="Yes",
input$vafLow,NA)
config[206,1]<-"PolymorphismVAF20"
config[206,2]<-ifelse(input$artifact_score=="Yes",
input$PolymorphismVAF20,NA)
config[207,1]<-"PolymorphismFrame"
config[207,2]<-ifelse(input$artifact_score=="Yes",
input$PolymorphismFrame,NA)
config[208,1]<-"isIndel"
config[208,2]<-ifelse(input$artifact_score=="Yes",
input$isIndel,NA)
config[209,1]<-"isIndelVAF"
config[209,2]<-ifelse(input$artifact_score=="Yes",
input$isIndelVAF,NA)
config[210,1]<-"noPrimerP"
config[210,2]<-ifelse(input$artifact_score=="Yes",
input$noPrimerP,NA)
config[211,1]<-"noPrimerPFwd"
config[211,2]<-ifelse(input$artifact_score=="Yes",
input$noPrimerPFwd,NA)
config[212,1]<-"noPrimerPRev"
config[212,2]<-ifelse(input$artifact_score=="Yes",
input$noPrimerPRev,NA)
config[213,1]<-"databaseVAF"
config[213,2]<-ifelse(input$artifact_score=="Yes",
input$databaseVAF,NA)
config[214,1]<-"databaseHigh"
config[214,2]<-ifelse(input$artifact_score=="Yes",
input$databaseHigh,NA)
config[215,1]<-"predictionVAF"
config[215,2]<-ifelse(input$artifact_score=="Yes",
input$predictionVAF,NA)
config[216,1]<-"oneCaller"
config[216,2]<-ifelse(input$artifact_score=="Yes",
input$oneCaller,NA)
config[217,1]<-"primerLocation"
config[217,2]<-ifelse(input$artifact_score=="Yes",
input$primerLocation,NA)
config[218,1]<-"primerPAlt"
config[218,2]<-ifelse(input$artifact_score=="Yes",
input$primerPAlt,NA)
config[219,1]<-"primerPFwd"
config[219,2]<-ifelse(input$artifact_score=="Yes",
input$primerPFwd,NA)
config[220,1]<-"primerPRev"
config[220,2]<-ifelse(input$artifact_score=="Yes",
input$primerPRev,NA)
config[221,1]<-"predictionSafe"
config[221,2]<-ifelse(input$artifact_score=="Yes",
input$predictionSafe,NA)
config[222,1]<-"nrcaller4"
config[222,2]<-ifelse(input$artifact_score=="Yes",
input$nrcaller4,NA)
config[223,1]<-"reward4"
config[223,2]<-ifelse(input$artifact_score=="Yes",
input$reward4,NA)
config[224,1]<-"nrcaller5"
config[224,2]<-ifelse(input$artifact_score=="Yes",
input$nrcaller5,NA)
config[225,1]<-"reward5"
config[225,2]<-ifelse(input$artifact_score=="Yes",
input$reward5,NA)
config[226,1]<-"nrcaller6"
config[226,2]<-ifelse(input$artifact_score=="Yes",
input$nrcaller6,NA)
config[227,1]<-"reward6"
config[227,2]<-ifelse(input$artifact_score=="Yes",
input$reward6,NA)
config[228,1]<-"knownHotspot"
config[228,2]<-ifelse(input$artifact_score=="Yes",
input$knownHotspot,NA)
config[229,1]<-"overlapTools"
config[229,2]<-paste(input$overlapTools,collapse=",")
config[230,1]<-"overlapReward"
config[230,2]<-ifelse(input$artifact_score=="Yes",
input$overlapReward,NA)
config[231,1]<-"artifactThreshold"
config[231,2]<-ifelse(input$artifact_score=="Yes",
input$artifactThreshold,NA)
config[232,1]<-"polymorphism_score"
config[232,2]<-input$polymorphism_score
config[233,1]<-"header1"
config[233,2]<-ifelse(input$artifact_score=="Yes",
"Important note:",NA)
config[234,1]<-"header2"
config[234,2]<-ifelse(input$artifact_score=="Yes",
"High score -> polymorphism",NA)
config[235,1]<-"header3"
config[235,2]<-ifelse(input$artifact_score=="Yes",
"Low score -> no polymorphism",NA)
config[236,1]<-"polyDetected"
config[236,2]<-ifelse(input$artifact_score=="Yes",
input$polyDetected,NA)
config[237,1]<-"polyDatabases"
config[237,2]<-ifelse(input$artifact_score=="Yes",
input$polyDatabases,NA)
config[238,1]<-"polyDatabasesReward"
config[238,2]<-ifelse(input$artifact_score=="Yes",
input$polyDatabasesReward,NA)
config[239,1]<-"polyDatabasesPolyLow"
config[239,2]<-ifelse(input$artifact_score=="Yes",
input$polyDatabasesPolyLow,NA)
config[240,1]<-"polyDatabasesPolyLowReward"
config[240,2]<-ifelse(input$artifact_score=="Yes",
input$polyDatabasesPolyLowReward,NA)
config[241,1]<-"polyDatabasesPolyHigh"
config[241,2]<-ifelse(input$artifact_score=="Yes",
input$polyDatabasesPolyHigh,NA)
config[242,1]<-"polyDatabasesPolyHighReward"
config[242,2]<-ifelse(input$artifact_score=="Yes",
input$polyDatabasesPolyHighReward,NA)
config[243,1]<-"polyVAF"
config[243,2]<-ifelse(input$artifact_score=="Yes",
input$polyVAF,NA)
config[244,1]<-"polyPrediction"
config[244,2]<-ifelse(input$artifact_score=="Yes",
input$polyPrediction,NA)
config[245,1]<-"polyEffect"
config[245,2]<-ifelse(input$artifact_score=="Yes",
input$polyEffect,NA)
config[246,1]<-"polyDetectedOnce"
config[246,2]<-ifelse(input$artifact_score=="Yes",
input$polyDetectedOnce,NA)
config[247,1]<-"polyDatabasesMut"
config[247,2]<-ifelse(input$artifact_score=="Yes",
input$polyDatabasesMut,NA)
config[248,1]<-"PolyDatabasesMutReward"
config[248,2]<-ifelse(input$artifact_score=="Yes",
input$polyDatabasesMutReward,NA)
config[249,1]<-"polyNoDatabase"
config[249,2]<-ifelse(input$artifact_score=="Yes",
input$polyNoDatabase,NA)
config[250,1]<-"polyPredictionEffect"
config[250,2]<-ifelse(input$artifact_score=="Yes",
input$polyPredictionEffect,NA)
config[251,1]<-"polyCosmic"
config[251,2]<-ifelse(input$artifact_score=="Yes",
input$polyCosmic,NA)
config[252,1]<-"polyThresholdCritical"
config[252,2]<-ifelse(input$artifact_score=="Yes",
input$polyThresholdCritical,NA)
config[253,1]<-"polyThreshold"
config[253,2]<-ifelse(input$artifact_score=="Yes",
input$polyThreshold,NA)
config[254,1]<-"output_folder"
config[254,2]<-input$output_folder
write.table(config,paste(input$output_folder,"/",
input$configFileOut,".txt",sep=""),
quote=FALSE,row.names=FALSE,sep="\t")
output$messageUI1<-renderUI({h5("Done.")})
return()
}
})
observeEvent(input$applyConfig,{
#check if a file was uploaded
if(is.null(input$configFileIn)){
log_info<-c("Please provide a configuration file<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
config_temp<-input$configFileIn
config<-read.table(config_temp$datapath,header=TRUE,sep="\t",
stringsAsFactors=FALSE)
output$output_folderUI<-renderUI({textInput('output_folder',
'Define output folder',
as.character(config[254,2]))})
if(!is.na(as.character(config[1,2]))){
output$gatkUI1<-renderUI({textInput('gatk_folder',
'Variant calling results',
as.character(config[1,2]))})
output$gatkUI2<-renderUI({radioButtons('gatk_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[2,2]),
inline=TRUE)})
output$gatkUI3<-renderUI({
conditionalPanel(
condition="input.gatk_file_type=='.txt'",
numericInput('gatk_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[3,2])),
numericInput('gatk_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[4,2])),
numericInput('gatk_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[5,2])),
numericInput('gatk_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[6,2])))})
output$gatkUI4<-renderUI({textInput('gatk_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[7,2]))})
output$gatkUI5<-renderUI({radioButtons('gatk_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[8,2]),
inline = TRUE)})
output$gatkUI6<-renderUI({radioButtons('gatk_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[9,2]),
inline = TRUE)})
output$gatkUI7<-renderUI({conditionalPanel(
condition="input.gatk_snv_indel=='No'",
textInput('gatk_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[10,2])),
textInput('gatk_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[11,2])))})
output$gatkUI8<-renderUI({radioButtons('gatk_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[12,2]),
inline = TRUE)})
}
if(is.na(as.character(config[1,2]))){
output$gatkUI1<-renderUI({NULL})
output$gatkUI2<-renderUI({NULL})
output$gatkUI3<-renderUI({NULL})
output$gatkUI4<-renderUI({NULL})
output$gatkUI5<-renderUI({NULL})
output$gatkUI6<-renderUI({NULL})
output$gatkUI7<-renderUI({NULL})
output$gatkUI8<-renderUI({NULL})
}
if(!is.na(as.character(config[13,2]))){
output$platypusUI1<-renderUI({textInput('platypus_folder',
'Variant calling results',
as.character(config[13,2]))})
output$platypusUI2<-renderUI({radioButtons('platypus_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[14,2]),
inline=TRUE)})
output$platypusUI3<-renderUI({
conditionalPanel(
condition="input.platypus_file_type=='.txt'",
numericInput('platypus_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[15,2])),
numericInput('platypus_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[16,2])),
numericInput('platypus_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[17,2])),
numericInput('platypus_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[18,2])))})
output$platypusUI4<-renderUI({textInput('platypus_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[19,2]))})
output$platypusUI5<-renderUI({radioButtons('platypus_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[20,2]),
inline = TRUE)})
output$platypusUI6<-renderUI({radioButtons('platypus_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[21,2]),
inline = TRUE)})
output$platypusUI7<-renderUI({conditionalPanel(
condition="input.platypus_snv_indel=='No'",
textInput('platypus_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[22,2])),
textInput('platypus_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[23,2])))})
output$platypusUI8<-renderUI({radioButtons('platypus_indels',
'How are Indels reported?',
c("CA>C","C>-A","CAAAC>CAAC"),
selected=as.character(config[24,2]),
inline = TRUE)})
}
if(is.na(as.character(config[13,2]))){
output$platypusUI1<-renderUI({NULL})
output$platypusUI2<-renderUI({NULL})
output$platypusUI3<-renderUI({NULL})
output$platypusUI4<-renderUI({NULL})
output$platypusUI5<-renderUI({NULL})
output$platypusUI6<-renderUI({NULL})
output$platypusUI7<-renderUI({NULL})
output$platypusUI8<-renderUI({NULL})
}
if(!is.na(as.character(config[25,2]))){
output$varscanUI1<-renderUI({textInput('varscan_folder',
'Variant calling results',
as.character(config[25,2]))})
output$varscanUI2<-renderUI({radioButtons('varscan_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[26,2]),
inline=TRUE)})
output$varscanUI3<-renderUI({
conditionalPanel(
condition="input.varscan_file_type=='.txt'",
numericInput('varscan_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[27,2])),
numericInput('varscan_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[28,2])),
numericInput('varscan_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[29,2])),
numericInput('varscan_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[30,2])))})
output$varscanUI4<-renderUI({textInput('varscan_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[31,2]))})
output$varscanUI5<-renderUI({radioButtons('varscan_mnvs','MNVs reported?',
c("Yes","No"),
as.character(config[32,2]),
inline = TRUE)})
output$varscanUI6<-renderUI({radioButtons('varscan_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[33,2]),
inline = TRUE)})
output$varscanUI7<-renderUI({conditionalPanel(
condition="input.varscan_snv_indel=='No'",
textInput('varscan_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[34,2])),
textInput('varscan_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[35,2])))})
output$varscanUI8<-renderUI({radioButtons('varscan_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[36,2]),
inline = TRUE)})
}
if(is.na(as.character(config[25,2]))){
output$varscanUI1<-renderUI({NULL})
output$varscanUI2<-renderUI({NULL})
output$varscanUI3<-renderUI({NULL})
output$varscanUI4<-renderUI({NULL})
output$varscanUI5<-renderUI({NULL})
output$varscanUI6<-renderUI({NULL})
output$varscanUI7<-renderUI({NULL})
output$varscanUI8<-renderUI({NULL})
}
if(!is.na(as.character(config[37,2]))){
output$freebayesUI1<-renderUI({textInput('freebayes_folder',
'Variant calling results',
as.character(config[37,2]))})
output$freebayesUI2<-renderUI({radioButtons('freebayes_file_type',
"Output file type",
c(".vcf",
".txt"),
as.character(config[38,2]),
inline=TRUE)})
output$freebayesUI3<-renderUI({
conditionalPanel(
condition="input.freebayes_file_type=='.txt'",
numericInput('freebayes_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[39,2])),
numericInput('freebayes_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[40,2])),
numericInput('freebayes_ref'
,"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[41,2])),
numericInput('freebayes_alt'
,"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[42,2])))})
output$freebayesUI4<-renderUI({textInput('freebayes_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[43,2]))})
output$freebayesUI5<-renderUI({radioButtons('freebayes_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[44,2]),
inline = TRUE)})
output$freebayesUI6<-renderUI({radioButtons('freebayes_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[45,2]),
inline = TRUE)})
output$freebayesUI7<-renderUI({conditionalPanel(
condition="input.freebayes_snv_indel=='No'",
textInput('freebayes_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[46,2])),
textInput('freebayes_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[47,2])))})
output$freebayesUI8<-renderUI({radioButtons('freebayes_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[48,2]),
inline=TRUE)})
}
if(is.na(as.character(config[37,2]))){
output$freebayesUI1<-renderUI({NULL})
output$freebayesUI2<-renderUI({NULL})
output$freebayesUI3<-renderUI({NULL})
output$freebayesUI4<-renderUI({NULL})
output$freebayesUI5<-renderUI({NULL})
output$freebayesUI6<-renderUI({NULL})
output$freebayesUI7<-renderUI({NULL})
output$freebayesUI8<-renderUI({NULL})
}
if(!is.na(as.character(config[49,2]))){
output$lofreqUI1<-renderUI({textInput('lofreq_folder',
'Variant calling results',
as.character(config[49,2]))})
output$lofreqUI2<-renderUI({radioButtons('lofreq_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[50,2]),
inline=TRUE)})
output$lofreqUI3<-renderUI({
conditionalPanel(
condition="input.lofreq_file_type=='.txt'",
numericInput('lofreq_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[51,2])),
numericInput('lofreq_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[52,2])),
numericInput('lofreq_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[53,2])),
numericInput('lofreq_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[54,2])))})
output$lofreqUI4<-renderUI({textInput('lofreq_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[55,2]))})
output$lofreqUI5<-renderUI({radioButtons('lofreq_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[56,2]),
inline = TRUE)})
output$lofreqUI6<-renderUI({radioButtons('lofreq_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[57,2]),
inline = TRUE)})
output$lofreqUI7<-renderUI({conditionalPanel(
condition="input.lofreq_snv_indel=='No'",
textInput('lofreq_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[58,2])),
textInput('lofreq_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[59,2])))})
output$lofreqUI8<-renderUI({radioButtons('lofreq_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[60,2]),
inline = TRUE)})
}
if(is.na(as.character(config[49,2]))){
output$lofreqUI1<-renderUI({NULL})
output$lofreqUI2<-renderUI({NULL})
output$lofreqUI3<-renderUI({NULL})
output$lofreqUI4<-renderUI({NULL})
output$lofreqUI5<-renderUI({NULL})
output$lofreqUI6<-renderUI({NULL})
output$lofreqUI7<-renderUI({NULL})
output$lofreqUI8<-renderUI({NULL})
}
if(!is.na(as.character(config[61,2]))){
output$snverUI1<-renderUI({textInput('snver_folder',
'Variant calling results',
as.character(config[61,2]))})
output$snverUI2<-renderUI({radioButtons('snver_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[62,2]),
inline=TRUE)})
output$snverUI3<-renderUI({
conditionalPanel(
condition="input.snver_file_type=='.txt'",
numericInput('snver_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[63,2])),
numericInput('snver_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[64,2])),
numericInput('snver_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[65,2])),
numericInput('snver_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[66,2])))})
output$snverUI4<-renderUI({textInput('snver_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[67,2]))})
output$snverUI5<-renderUI({radioButtons('snver_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[68,2]),
inline = TRUE)})
output$snverUI6<-renderUI({radioButtons('snver_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[69,2]),
inline = TRUE)})
output$snverUI7<-renderUI({conditionalPanel(
condition="input.snver_snv_indel=='No'",
textInput('snver_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[70,2])),
textInput('snver_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[71,2])))})
output$snverUI8<-renderUI({radioButtons('snver_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[72,2]),
inline = TRUE)})
}
if(is.na(as.character(config[61,2]))){
output$snverUI1<-renderUI({NULL})
output$snverUI2<-renderUI({NULL})
output$snverUI3<-renderUI({NULL})
output$snverUI4<-renderUI({NULL})
output$snverUI5<-renderUI({NULL})
output$snverUI6<-renderUI({NULL})
output$snverUI7<-renderUI({NULL})
output$snverUI8<-renderUI({NULL})
}
if(!is.na(as.character(config[73,2]))){
output$samtoolsUI1<-renderUI({textInput('samtools_folder',
'Variant calling results',
as.character(config[73,2]))})
output$samtoolsUI2<-renderUI({radioButtons('samtools_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[74,2]),
inline=TRUE)})
output$samtoolsUI3<-renderUI({
conditionalPanel(
condition="input.samtools_file_type=='.txt'",
numericInput('samtools_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[75,2])),
numericInput('samtools_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[76,2])),
numericInput('samtools_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[77,2])),
numericInput('samtools_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[78,2])))})
output$samtoolsUI4<-renderUI({textInput('samtools_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[79,2]))})
output$samtoolsUI5<-renderUI({radioButtons('samtools_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[80,2]),
inline = TRUE)})
output$samtoolsUI6<-renderUI({radioButtons('samtools_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[81,2]),
inline = TRUE)})
output$samtoolsUI7<-renderUI({conditionalPanel(
condition="input.samtools_snv_indel=='No'",
textInput('samtools_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[82,2])),
textInput('samtools_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[83,2])))})
output$samtoolsUI8<-renderUI({radioButtons('samtools_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[84,2]),
inline = TRUE)})
}
if(is.na(as.character(config[73,2]))){
output$samtoolsUI1<-renderUI({NULL})
output$samtoolsUI2<-renderUI({NULL})
output$samtoolsUI3<-renderUI({NULL})
output$samtoolsUI4<-renderUI({NULL})
output$samtoolsUI5<-renderUI({NULL})
output$samtoolsUI6<-renderUI({NULL})
output$samtoolsUI7<-renderUI({NULL})
output$samtoolsUI8<-renderUI({NULL})
}
if(!is.na(as.character(config[85,2]))){
output$vardictUI1<-renderUI({textInput('vardict_folder',
'Variant calling results',
as.character(config[85,2]))})
output$vardictUI2<-renderUI({radioButtons('vardict_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[86,2]),
inline=TRUE)})
output$vardictUI3<-renderUI({
conditionalPanel(
condition="input.vardict_file_type=='.txt'",
numericInput('vardict_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[87,2])),
numericInput('vardict_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[88,2])),
numericInput('vardict_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[89,2])),
numericInput('vardict_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[90,2])))})
output$vardictUI4<-renderUI({textInput('vardict_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[91,2]))})
output$vardictUI5<-renderUI({radioButtons('vardict_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[92,2]),
inline = TRUE)})
output$vardictUI6<-renderUI({radioButtons('vardict_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[93,2]),
inline = TRUE)})
output$vardictUI7<-renderUI({conditionalPanel(
condition="input.vardict_snv_indel=='No'",
textInput('vardict_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[94,2])),
textInput('vardict_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[95,2])))})
output$vardictUI8<-renderUI({radioButtons('vardict_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[96,2]),
inline = TRUE)})
}
if(is.na(as.character(config[85,2]))){
output$vardictUI1<-renderUI({NULL})
output$vardictUI2<-renderUI({NULL})
output$vardictUI3<-renderUI({NULL})
output$vardictUI4<-renderUI({NULL})
output$vardictUI5<-renderUI({NULL})
output$vardictUI6<-renderUI({NULL})
output$vardictUI7<-renderUI({NULL})
output$vardictUI8<-renderUI({NULL})
}
if(!is.na(as.character(config[97,2]))){
output$caller1UI0<-renderUI({h4(as.character(config[97,2]))})
output$caller1UI0.1<-renderUI({textInput('caller1_name',
'Name of caller 1',
as.character(config[98,2]))})
output$caller1UI1<-renderUI({textInput('caller1_folder',
'Variant calling results',
as.character(config[99,2]))})
output$caller1UI2<-renderUI({radioButtons('caller1_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[100,2]),
inline=TRUE)})
output$caller1UI3<-renderUI({
conditionalPanel(
condition="input.caller1_file_type=='.txt'",
numericInput('caller1_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[101,2])),
numericInput('caller1_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[102,2])),
numericInput('caller1_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[103,2])),
numericInput('caller1_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[104,2])))})
output$caller1UI4<-renderUI({textInput('caller1_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[105,2]))})
output$caller1UI5<-renderUI({radioButtons('caller1_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[106,2]),
inline = TRUE)})
output$caller1UI6<-renderUI({radioButtons('caller1_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[107,2]),
inline = TRUE)})
output$caller1UI7<-renderUI({conditionalPanel(
condition="input.caller1_snv_indel=='No'",
textInput('caller1_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[108,2])),
textInput('caller1_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[109,2])))})
output$caller1UI8<-renderUI({radioButtons('caller1_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[110,2]),
inline = TRUE)})
}
if(is.na(as.character(config[97,2]))){
output$caller1UI0<-renderUI({NULL})
output$caller1UI0.1<-renderUI({NULL})
output$caller1UI1<-renderUI({NULL})
output$caller1UI2<-renderUI({NULL})
output$caller1UI3<-renderUI({NULL})
output$caller1UI4<-renderUI({NULL})
output$caller1UI5<-renderUI({NULL})
output$caller1UI6<-renderUI({NULL})
output$caller1UI7<-renderUI({NULL})
output$caller1UI8<-renderUI({NULL})
}
if(!is.na(as.character(config[111,2]))){
output$caller2UI0<-renderUI({h4(as.character(config[111,2]))})
output$caller2UI0.1<-renderUI({textInput('caller2_name',
'Name of caller 1',
as.character(config[112,2]))})
output$caller2UI1<-renderUI({textInput('caller2_folder',
'Variant calling results',
as.character(config[113,2]))})
output$caller2UI2<-renderUI({radioButtons('caller2_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[114,2]),
inline=TRUE)})
output$caller2UI3<-renderUI({
conditionalPanel(
condition="input.caller2_file_type=='.txt'",
numericInput('caller2_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[115,2])),
numericInput('caller2_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[116,2])),
numericInput('caller2_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[117,2])),
numericInput('caller2_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[118,2])))})
output$caller2UI4<-renderUI({textInput('caller2_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[119,2]))})
output$caller2UI5<-renderUI({radioButtons('caller2_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[120,2]),
inline = TRUE)})
output$caller2UI6<-renderUI({radioButtons('caller2_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[121,2]),
inline = TRUE)})
output$caller2UI7<-renderUI({conditionalPanel(
condition="input.caller2_snv_indel=='No'",
textInput('caller2_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[122,2])),
textInput('caller2_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[123,2])))})
output$caller2UI8<-renderUI({radioButtons('caller2_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[124,2]),
inline = TRUE)})
}
if(is.na(as.character(config[111,2]))){
output$caller2UI0<-renderUI({NULL})
output$caller2UI0.1<-renderUI({NULL})
output$caller2UI1<-renderUI({NULL})
output$caller2UI2<-renderUI({NULL})
output$caller2UI3<-renderUI({NULL})
output$caller2UI4<-renderUI({NULL})
output$caller2UI5<-renderUI({NULL})
output$caller2UI6<-renderUI({NULL})
output$caller2UI7<-renderUI({NULL})
output$caller2UI8<-renderUI({NULL})
}
if(!is.na(as.character(config[125,2]))){
output$caller3UI0<-renderUI({h4(as.character(config[125,2]))})
output$caller3UI0.1<-renderUI({textInput('caller3_name',
'Name of caller 1',
as.character(config[126,2]))})
output$caller3UI1<-renderUI({textInput('caller3_folder',
'Variant calling results',
as.character(config[127,2]))})
output$caller3UI2<-renderUI({radioButtons('caller3_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[128,2]),
inline=TRUE)})
output$caller3UI3<-renderUI({
conditionalPanel(
condition="input.caller3_file_type=='.txt'",
numericInput('caller3_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[129,2])),
numericInput('caller3_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[130,2])),
numericInput('caller3_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[131,2])),
numericInput('caller3_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[132,2])))})
output$caller3UI4<-renderUI({textInput('caller3_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[133,2]))})
output$caller3UI5<-renderUI({radioButtons('caller3_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[134,2]),
inline = TRUE)})
output$caller3UI6<-renderUI({radioButtons('caller3_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[135,2]),
inline = TRUE)})
output$caller3UI7<-renderUI({conditionalPanel(
condition="input.caller3_snv_indel=='No'",
textInput('caller3_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[136,2])),
textInput('caller3_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[137,2])))})
output$caller3UI8<-renderUI({radioButtons('caller3_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[138,2]),
inline = TRUE)})
}
if(is.na(as.character(config[125,2]))){
output$caller3UI0<-renderUI({NULL})
output$caller3UI0.1<-renderUI({NULL})
output$caller3UI1<-renderUI({NULL})
output$caller3UI2<-renderUI({NULL})
output$caller3UI3<-renderUI({NULL})
output$caller3UI4<-renderUI({NULL})
output$caller3UI5<-renderUI({NULL})
output$caller3UI6<-renderUI({NULL})
output$caller3UI7<-renderUI({NULL})
output$caller3UI8<-renderUI({NULL})
}
if(!is.na(as.character(config[139,2]))){
output$caller4UI0<-renderUI({h4(as.character(config[139,2]))})
output$caller4UI0.1<-renderUI({textInput('caller4_name',
'Name of caller 1',
as.character(config[140,2]))})
output$caller4UI1<-renderUI({textInput('caller4_folder',
'Variant calling results',
as.character(config[141,2]))})
output$caller4UI2<-renderUI({radioButtons('caller4_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[142,2]),
inline=TRUE)})
output$caller4UI3<-renderUI({
conditionalPanel(
condition="input.caller4_file_type=='.txt'",
numericInput('caller4_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[143,2])),
numericInput('caller4_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[144,2])),
numericInput('caller4_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[145,2])),
numericInput('caller4_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[146,2])))})
output$caller4UI4<-renderUI({textInput('caller4_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[147,2]))})
output$caller4UI5<-renderUI({radioButtons('caller4_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[148,2]),
inline = TRUE)})
output$caller4UI6<-renderUI({radioButtons('caller4_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[149,2]),
inline = TRUE)})
output$caller4UI7<-renderUI({conditionalPanel(
condition="input.caller4_snv_indel=='No'",
textInput('caller4_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[150,2])),
textInput('caller4_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[151,2])))})
output$caller4UI8<-renderUI({radioButtons('caller4_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[152,2]),
inline = TRUE)})
}
if(is.na(as.character(config[139,2]))){
output$caller4UI0<-renderUI({NULL})
output$caller4UI0.1<-renderUI({NULL})
output$caller4UI1<-renderUI({NULL})
output$caller4UI2<-renderUI({NULL})
output$caller4UI3<-renderUI({NULL})
output$caller4UI4<-renderUI({NULL})
output$caller4UI5<-renderUI({NULL})
output$caller4UI6<-renderUI({NULL})
output$caller4UI7<-renderUI({NULL})
output$caller4UI8<-renderUI({NULL})
}
if(!is.na(as.character(config[153,2]))){
output$caller5UI0<-renderUI({h4(as.character(config[153,2]))})
output$caller5UI0.1<-renderUI({textInput('caller5_name',
'Name of caller 1',
as.character(config[154,2]))})
output$caller5UI1<-renderUI({textInput('caller5_folder',
'Variant calling results',
as.character(config[155,2]))})
output$caller5UI2<-renderUI({radioButtons('caller5_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[156,2]),
inline=TRUE)})
output$caller5UI3<-renderUI({
conditionalPanel(
condition="input.caller5_file_type=='.txt'",
numericInput('caller5_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[157,2])),
numericInput('caller5_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[158,2])),
numericInput('caller5_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[159,2])),
numericInput('caller5_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[160,2])))})
output$caller5UI4<-renderUI({textInput('caller5_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[161,2]))})
output$caller5UI5<-renderUI({radioButtons('caller5_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[162,2]),
inline = TRUE)})
output$caller5UI6<-renderUI({radioButtons('caller5_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[163,2]),
inline = TRUE)})
output$caller5UI7<-renderUI({conditionalPanel(
condition="input.caller5_snv_indel=='No'",
textInput('caller5_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[164,2])),
textInput('caller5_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[165,2])))})
output$caller5UI8<-renderUI({radioButtons('caller5_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[166,2]),
inline = TRUE)})
}
if(is.na(as.character(config[153,2]))){
output$caller5UI0<-renderUI({NULL})
output$caller5UI0.1<-renderUI({NULL})
output$caller5UI1<-renderUI({NULL})
output$caller5UI2<-renderUI({NULL})
output$caller5UI3<-renderUI({NULL})
output$caller5UI4<-renderUI({NULL})
output$caller5UI5<-renderUI({NULL})
output$caller5UI6<-renderUI({NULL})
output$caller5UI7<-renderUI({NULL})
output$caller5UI8<-renderUI({NULL})
}
if(!is.na(as.character(config[167,2]))){
output$locationsUI<-renderUI({checkboxGroupInput("locations",
"What are the locations you are interested in?",
c("coding",
"intron",
"threeUTR",
"fiveUTR",
"intergenic",
"spliceSite",
"promoter"),
strsplit(as.character(config[167,2]),split=",")[[1]],
inline=TRUE)})
}
if(is.na(as.character(config[167,2]))){
output$locationsUI<-renderUI({checkboxGroupInput("locations",
"What are the locations you are interested in?",
c("coding",
"intron",
"threeUTR",
"fiveUTR",
"intergenic",
"spliceSite",
"promoter"),
c("coding"),
inline=TRUE)})
}
if(!is.na(as.character(config[168,2]))){
output$consequencesUI<-renderUI({checkboxGroupInput("consequences",
"What kind of variants are you interested in? (coding only)",
c("synonymous",
"nonsynonymous",
"frameshift",
"nonsense",
"not translated"),
strsplit(as.character(config[168,2]),split=",")[[1]],
inline=TRUE)})
}
if(is.na(as.character(config[168,2]))){
output$consequencesUI<-renderUI({checkboxGroupInput("consequences",
"What kind of variants are you interested in? (coding only)",
c("synonymous",
"nonsynonymous",
"frameshift",
"nonsense","not translated"),
c("nonsynonymous",
"frameshift",
"nonsense"),
inline=TRUE)})
}
output$bam_folderUI<-renderUI({textInput('bam_folder',
'Define folder containing bam- and bai files',
as.character(config[169,2]))})
output$dpUI<-renderUI({numericInput("dp",
"Minimum coverage [10;9999]",
value=as.numeric(config[170,2]),
min=10,max=9999)})
output$nr_altUI<-renderUI({numericInput("nr_alt",
"Minimum number of reads carrying the alternate allele [3;9999]",
value=as.numeric(config[171,2]),
min=3,max=9999)})
output$vafUI<-renderUI({sliderInput("vaf",
"Minimum allele frequency [%]",
min=1,max=100,
value=as.numeric(config[172,2]))})
output$bqUI<-renderUI({numericInput("bq",
"Minimum base quality [0;36]",
value=as.numeric(config[173,2]),
min=0,max=36)})
output$bq_diffUI<-renderUI({numericInput("bq_diff",
"Maximum difference between Ref_BQ and Alt_BQ [0;36]",
value=as.numeric(config[174,2]),
min=0,max=36)})
output$dbSNPUI<-renderUI({checkboxInput("dbSNP",
"Consider dbSNP? (Hsapiens.dbSNP144.GRCh37 and XtraSNPlocs.Hsapiens.dbSNP144.GRCh37)",
value=as.character(config[175,2])=="TRUE")})
output$"1kgenomesUI"<-renderUI({checkboxInput("1kgenomes",
"Consider 1000 Genomes? (MafDb.1Kgenomes.phase3.hs37d5)",
value=as.character(config[176,2])=="TRUE")})
output$exacUI<-renderUI({checkboxInput("exac",
"Consider ExAC? (MafDb.ExAC.r1.0.hs37d5)",
value=as.character(config[177,2])=="TRUE")})
output$gadUI<-renderUI({checkboxInput("gad",
"Consider Genome Aggregation Database? (MafDb.gnomADex.r2.1.hs37d5)",
value=as.character(config[179,2])=="TRUE")})
output$cosmicUI<-renderUI({checkboxInput("cosmic",
"Consider COSMIC? (COSMIC.67)",
value=as.character(config[180,2])=="TRUE")})
output$clinvarUI<-renderUI({checkboxInput("clinvar",
"Consider ClinVar? (rentrez)",
value=as.character(config[181,2])=="TRUE")})
output$predictUI<-renderUI({radioButtons("predict",
"What source would you like to use for impact prediction?",
c("SIFT","Provean","PolyPhen2"),
as.character(config[182,2]),
inline=TRUE)})
output$stricter_thresholdsUI<-renderUI({radioButtons('stricter_thresholds',
"Do you want to define stricter thresholds for coverage and base quality?",
c("Yes",
"No"),
as.character(config[183,2]),
inline=TRUE)})
if(as.character(config[183,2])=="Yes"){
output$stricter_thresholdsUI2<-renderUI({conditionalPanel(
condition="input.stricter_thresholds=='Yes'",
numericInput("dp2","Minimum coverage [10;9999]",
value=as.numeric(config[184,2]),
min=10,max=9999),
numericInput("nr_alt2",
"Minimum number of reads carrying the alternate allele [3;9999]",
value=as.numeric(config[185,2]),
min=3,max=9999),
sliderInput("vaf2","Minimum allele frequency [%]",
min=1,max=100,
value=as.numeric(config[186,2])),
numericInput("bq2","Minimum base quality [0;36]",
value=as.numeric(config[187,2]),
min=0,max=36),
numericInput("bq_diff2",
"Maximum difference between Ref_BQ and Alt_BQ [0;36]",
value=as.numeric(config[188,2]),
min=0,max=36)
)})
}
if(as.character(config[183,2]=="No")){
output$stricter_thresholdsUI2<-renderUI({NULL})
}
output$nr_samplesUI<-renderUI({numericInput("nr_samples",
"Detection in more than how many samples makes a call striking?",
value=as.numeric(config[189,2]),
min=1,max=9999)})
if(as.character(config[182,2])=="SIFT"){
output$predictionUI1<-renderUI({conditionalPanel(
condition="input.predict=='SIFT'",
sliderInput("damaging_safe1",
"SIFT: When is a damaging prediction reliable? (internal threshold <=0.05)",
min=0,max=1.0,
value=as.numeric(config[190,2])),
sliderInput("tolerated_safe1",
"SIFT: When is a tolerated prediction reliable? (internal threshold >0.05)",
min=0,max=1.0,
value=as.numeric(config[191,2]))
)})
}
if(as.character(config[182,2])!="SIFT"){
output$predictionUI1<-renderUI({NULL})
}
if(as.character(config[182,2])=="Provean"){
output$predictionUI2<-renderUI({conditionalPanel(
condition="input.predict=='Provean'",
sliderInput("damaging_safe2",
"Provean: When is a damaging prediction reliable? (internal threshold <=-2.5)",
min=-20,max=10,
value=as.numeric(config[192,2])),
sliderInput("tolerated_safe2",
"Provean: When is a tolerated prediction reliable? (internal threshold >-2.5)",
min=-20,max=10,
value=as.numeric(config[193,2]))
)})
}
if(as.character(config[182,2])!="Provean"){
output$predictionUI2<-renderUI({NULL})
}
if(as.character(config[182,2])=="PolyPhen2"){
output$predictionUI1<-renderUI({conditionalPanel(
condition="input.predict=='PolyPhen2'",
sliderInput("damaging_safe3",
"PolyPhen2: When is a damaging prediction reliable? (>=0.5)",
min=0,max=1,
value=as.numeric(config[194,2])),
sliderInput("tolerated_safe3",
"PolyPhen2: When is a tolerated prediction reliable? (<0.5)",
min=0,max=1,
value=as.numeric(config[195,2]))
)})
}
if(as.character(config[182,2])!="PolyPhen2"){
output$predictionUI3<-renderUI({NULL})
}
output$artifact_scoreUI<-renderUI({radioButtons('artifact_score',
"Would you like to change the default scoring for the artifact score?",
c("Yes","No"),
config[196,2],
inline=TRUE)})
if(as.character(config[196,2])=="Yes"){
output$artifact_scoreUI2<-renderUI({conditionalPanel(
condition="input.artifact_score=='Yes'",
h4(as.character(config[197,2])),
h5(as.character(config[198,2])),
h5(as.character(config[199,2])),
sliderInput("PolymorphismVAF10",
"Polymorphism (based on polymorphism score) AND VAF<10%",
min=-5,max=5,
value=as.numeric(config[200,2])),
sliderInput("BQ_AltMean",
"BQ_Alt<(mean(BQ_Alt)-3*sd(BQ_Alt))",
min=-5,max=5,
value=as.numeric(config[201,2])),
sliderInput("detectedHigh",
"Detected in >50% of all samples",
min=-5,max=5,
value=as.numeric(config[202,2])),
sliderInput("detectedLow",
"Detected in a striking number of samples",
min=-5,max=5,
value=as.numeric(config[203,2])),
sliderInput("detectedLowVAF",
"Detected in a striking number of samples AND VAF>85%",
min=-5,max=5,
value=as.numeric(config[204,2])),
sliderInput("vafLow","VAF<2%",min=-5,max=5,
value=as.numeric(config[205,2])),
sliderInput("PolymorphismVAF20",
"Polymorphism (based on polymorphism score) AND VAF<20%",
min=-5,max=5,
value=as.numeric(config[206,2])),
sliderInput("PolymorphismFrame",
"Polymorphism (based on polymorphism score) AND frameshift",
min=-5,max=5,
value=as.numeric(config[207,2])),
sliderInput("isIndel","Indel",min=-5,max=5,
value=as.numeric(config[208,2])),
sliderInput("isIndelVAF",
"Indel AND VAF<5%",min=-5,max=5,
value=as.numeric(config[209,2])),
sliderInput("noPrimerP",
"No primer (information) AND p<0.001",
min=-5,max=5,
value=as.numeric(config[210,2])),
sliderInput("noPrimerPFwd",
"No primer (information) AND p>=0.001 AND Nr_Ref_fwd>=(Min_DP-Min_Alt)/2 AND Nr_Alt_fwd<=2",
min=-5,max=5,
value=as.numeric(config[211,2])),
sliderInput("noPrimerPRev",
"No primer (information) AND p>=0.001 AND Nr_Ref_rev>=(Min_DP-Min_Alt)/2 AND Nr_Alt_rev<=2",
min=-5,max=5,
value=as.numeric(config[212,2])),
sliderInput("databaseVAF",
"No database AND VAF<10%",
min=-5,max=5,
value=as.numeric(config[213,2])),
sliderInput("databaseHigh",
"No database AND detected in >50% of all samples",
min=-5,max=5,
value=as.numeric(config[214,2])),
sliderInput("predictionVAF",
"Reliable tolerated prediction AND (VAF<35% OR 65%<VAF<85%)",
min=-5,max=5,
value=as.numeric(config[215,2])),
sliderInput("oneCaller",
"Reported by only 1 caller",
min=-5,max=5,
value=as.numeric(config[216,2])),
sliderInput("primerLocation",
"Primer-location",
min=-5,max=5,
value=as.numeric(config[217,2])),
sliderInput("primerPAlt",
"No primer (information) AND p<0.001 AND Nr_Alt_rev>=Min_Alt/2 AND Nr_Alt_rev>=Min_Alt/2",
min=-5,max=5,
value=as.numeric(config[218,2])),
sliderInput("primerPFwd",
"No primer (information) AND p<0.001 AND Nr_Ref_fwd<(Min_DP-Min_Alt)/2 AND Nr_Alt_fwd<=2",
min=-5,max=5,
value=as.numeric(config[219,2])),
sliderInput("primerPRev",
"No primer (information) AND p<0.001 AND Nr_Ref_rev<(Min_DP-Min_Alt)/2 AND Nr_Alt_rev<=2",
min=-5,max=5,
value=as.numeric(config[220,2])),
sliderInput("predictionSafe",
"Reliable damaging prediction",
min=-5,max=5,
value=as.numeric(config[221,2])),
numericInput("nrcaller4",
"Intermediate number of callers to report the same variant [1;14]",
min=1,max=14,
value=as.numeric(config[222,2])),
sliderInput("reward4","Score",min=-5,max=5,
value=as.numeric(config[223,2])),
numericInput("nrcaller5",
"High number of callers to report the same variant [1;14]",
min=1,max=14,value=as.numeric(config[224,2])),
sliderInput("reward5","Score",min=-5,max=5,
value=as.numeric(config[225,2])),
numericInput("nrcaller6",
"Very high number of callers to report the same variant [1;14]",
min=1,max=14,
value=as.numeric(config[226,2])),
sliderInput("reward6","Score",min=-5,max=5,
value=as.numeric(config[227,2])),
sliderInput("knownHotspot","Known hotspot",min=-5,max=5,
value=as.numeric(config[228,2])),
checkboxGroupInput("overlapTools","Overlapping output by which tools shall be rewarded?",
choices=c("GATK","Platypus","VarScan","LoFreq","FreeBayes","SNVer","SamTools","VarDict",
"Caller1","Caller2","Caller3","Caller4","Caller5"),
selected=strsplit(as.character(config[229,2]),split=",")[[1]],
inline=TRUE),
sliderInput("overlapReward","Score",min=-5,max=5,
value=as.numeric(config[230,2])),
hr(),
sliderInput("artifactThreshold",
"Threshold artifact score (still artifact)",
min=-10,max=10,
value=as.numeric(config[231,2]))
)})
}
if(as.character(config[196,2])=="No"){
output$artifact_scoreUI2<-renderUI({NULL})
}
output$polymorphism_scoreUI<-renderUI({radioButtons('polymorphism_score',
"Would you like to change the default scoring for the polymorphism score?",
c("Yes","No"),
config[232,2],
inline=TRUE)})
if(as.character(config[232,2])=="Yes"){
output$polymorphism_scoreUI2<-renderUI({conditionalPanel(
condition="input.polymorphism_score=='Yes'",
h4(as.character(config[233,2])),
h5(as.character(config[234,2])),
h5(as.character(config[235,2])),
sliderInput("polyDetected",
"Detected in a striking number of samples",
min=-5,max=5,
value=as.numeric(config[236,2])),
numericInput("polyDatabases",
"High number of databases to have information on a variant [1;8]",
min=1,max=8,
value=as.numeric(config[237,2])),
sliderInput("polyDatabasesReward","Score",
min=-5,max=5,
value=as.numeric(config[238,2])),
numericInput("polyDatabasesPolyLow",
"Intermediate number of polymorphism databases to have information on a variant [1;8]",
min=1,max=8,
value=as.numeric(config[239,2])),
sliderInput("polyDatabasesPolyLowReward",
"Score",min=-5,max=5,
value=as.numeric(config[240,2])),
numericInput("polyDatabasesPolyHigh",
"High number of polymorphism databases to have information on a variant [1;8]",
min=1,max=8,
value=as.numeric(config[241,2])),
sliderInput("polyDatabasesPolyHighReward","Score",
min=-5,max=5,
value=as.numeric(config[242,2])),
sliderInput("polyVAF","35%<=VAF>=65% OR 85%<=VAF",
min=-5,max=5,
value=as.numeric(config[243,2])),
sliderInput("polyPrediction",
"Reliable tolerated prediction",
min=-5,max=5,
value=as.numeric(config[244,2])),
sliderInput("polyEffect",
"No frameshift AND no stop gained AND no stop lost",
min=-5,max=5,
value=as.numeric(config[245,2])),
sliderInput("polyDetectedOnce",
"Reported by only 1 caller",min=-5,max=5,
value=as.numeric(config[246,2])),
numericInput("polyDatabasesMut",
"Critical number of mutation databases to have information on a variant [1;8]",
min=1,max=8,
value=as.numeric(config[247,2])),
sliderInput("polyDatabasesMutReward","Score",
min=-5,max=5,
value=as.numeric(config[248,2])),
sliderInput("polyNoDatabase",
"Not detected in any polymorphism database",
min=-5,max=5,
value=as.numeric(config[249,2])),
sliderInput("polyPredictionEffect",
"Reliable damaging prediction OR stop gained OR stop lost",
min=-5,max=5,
value=as.numeric(config[250,2])),
numericInput("polyCosmic",
"Critical number of Cosmic entries [1;1000]",
min=1,max=1000,
value=as.numeric(config[251,2])),
hr(),
sliderInput("polyThresholdCritical",
"Threshold polymorphism score if number of Cosmic entries is not critical (still polymorphism)",
min=-10,max=10,
value=as.numeric(config[252,2])),
sliderInput("polyThreshold",
"Threshold polymorphism score if number of Cosmic entries is critical (still polymorphism)",
min=-10,max=10,
value=as.numeric(config[253,2]))
)})
}
if(as.character(config[232,2])=="No"){
output$polymorphism_scoreUI2<-renderUI({NULL})
}
output$messageUI2<-renderUI({h5("Done. Please make sure that everything is correct.")})
return()
})
observeEvent(input$appreci8R,{
log_info<-c()
log_info[1]<-"Starting analysis with the appreci8R...<br><br>"
output$log_info<-renderUI({HTML(log_info)})
#check if input really exists
if(file.exists(input$output_folder)==FALSE){
log_info<-c(log_info,
"Your output folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$gatk_folder)&&
file.exists(input$gatk_folder)==FALSE){
log_info<-c(log_info,
"You want to analyze GATK output, but the folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$platypus_folder)&&
file.exists(input$platypus_folder)==FALSE){
log_info<-c(log_info,
"You want to analyze Platypus output, but the folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$varscan_folder)&&
file.exists(input$varscan_folder)==FALSE){
log_info<-c(log_info,
"You want to analyze VarScan output, but the folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$freebayes_folder)&&
file.exists(input$freebayes_folder)==FALSE){
log_info<-c(log_info,"You want to analyze FreeBayes output, but the folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$lofreq_folder)&&
file.exists(input$lofreq_folder)==FALSE){
log_info<-c(log_info,
"You want to analyze LoFreq output, but the folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$snver_folder)&&
file.exists(input$snver_folder)==FALSE){
log_info<-c(log_info,
"You want to analyze SNVer output, but the folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$samtools_folder)&&
file.exists(input$samtools_folder)==FALSE){
log_info<-c(log_info,
"You want to analyze SamTools output, but the folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$vardict_folder)&&
file.exists(input$vardict_folder)==FALSE){
log_info<-c(log_info,
"You want to analyze VarDict output, but the folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
#test additional callers
if(input$nr_additional>0&&!is.null(input$caller1_folder)&&
file.exists(input$caller1_folder)==FALSE){
log_info<-c(log_info,paste("The output folder of ",
input$caller1_name,
" does not exist<br>",sep=""))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(input$nr_additional>1&&!is.null(input$caller2_folder)&&
file.exists(input$caller2_folder)==FALSE){
log_info<-c(log_info,paste("The output folder of ",
input$caller1_name,
" does not exist<br>",sep=""))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(input$nr_additional>2&&!is.null(input$caller3_folder)&&
file.exists(input$caller3_folder)==FALSE){
log_info<-c(log_info,paste("The output folder of ",
input$caller1_name,
" does not exist<br>",sep=""))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(input$nr_additional>3&&!is.null(input$caller4_folder)&&
file.exists(input$caller4_folder)==FALSE){
log_info<-c(log_info,paste("The output folder of ",
input$caller1_name,
" does not exist<br>",sep=""))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(input$nr_additional>4&&!is.null(input$caller5_folder)&&
file.exists(input$caller5_folder)==FALSE){
log_info<-c(log_info,paste("The output folder of ",
input$caller1_name,
" does not exist<br>",sep=""))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(is.null(input$gatk_folder)&&is.null(input$platypus_folder)&&
is.null(input$varscan_folder)&&
is.null(input$freebayes_folder)
&&is.null(input$lofreq_folder)&&is.null(input$snver_folder)&&
is.null(input$samtools_folder)&&is.null(input$vardict_folder)
&&(input$nr_additional==0||
(input$nr_additional>0&&sum(!is.null(input$caller1_folder),
!is.null(input$caller2_folder),
!is.null(input$caller3_folder),
!is.null(input$caller4_folder),
!is.null(input$caller5_folder))!=input$nr_additional))){
log_info<-c(log_info,
"Please select at least one variant caller<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
#1. Reading Input
log_info<-c(log_info,"0. Reading input<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "0. Reading input", value = 0)
raw_calls<-list()
overview<-data.frame(SampleID=NA,GATK=NA,Platypus=NA,VarScan=NA,
FreeBayes=NA,LoFreq=NA,SNVer=NA,
SamTools=NA,VarDict=NA)
if(!is.null(input$caller1_name)){
namen_overview<-names(overview)
overview<-cbind(overview,New=NA)
names(overview)<-c(namen_overview,input$caller1_name)
}
if(!is.null(input$caller2_name)){
namen_overview<-names(overview)
overview<-cbind(overview,New=NA)
names(overview)<-c(namen_overview,input$caller2_name)
}
if(!is.null(input$caller3_name)){
namen_overview<-names(overview)
overview<-cbind(overview,New=NA)
names(overview)<-c(namen_overview,input$caller3_name)
}
if(!is.null(input$caller4_name)){
namen_overview<-names(overview)
overview<-cbind(overview,New=NA)
names(overview)<-c(namen_overview,input$caller4_name)
}
if(!is.null(input$caller5_name)){
namen_overview<-names(overview)
overview<-cbind(overview,New=NA)
names(overview)<-c(namen_overview,input$caller5_name)
}
included_callers<-rep(NA,13)
progress$inc(1/13)
raw_calls[[1]]<-list()
if(!is.null(input$gatk_folder)){
included_callers[1]<-"GATK"
raw_calls[[1]]<-readInput(input$gatk_folder,
input$gatk_file_names_add,
input$gatk_file_type,
input$gatk_snv_indel,
input$gatk_snv_names_add,
input$gatk_indel_names_add,
input$gatk_chr,input$gatk_pos,
input$gatk_ref,input$gatk_alt)
sampleNameTest<-getSampleNames(input$gatk_folder,
input$gatk_file_names_add,
input$gatk_file_type,
input$gatk_snv_indel,
input$gatk_snv_names_add,
input$gatk_indel_names_add)
}
if(is.null(input$gatk_folder)){
sampleNameTest<-NA
}
progress$inc(1/13)
raw_calls[[2]]<-list()
if(!is.null(input$platypus_folder)){
included_callers[2]<-"Platypus"
raw_calls[[2]]<-readInput(input$platypus_folder,
input$platypus_file_names_add,
input$platypus_file_type,
input$platypus_snv_indel,
input$platypus_snv_names_add,
input$platypus_indel_names_add,
input$platypus_chr,
input$platypus_pos,
input$platypus_ref,
input$platypus_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$platypus_folder,
input$platypus_file_names_add,
input$platypus_file_type,
input$platypus_snv_indel,
input$platypus_snv_names_add,
input$platypus_indel_names_add))
}
progress$inc(1/13)
raw_calls[[3]]<-list()
if(!is.null(input$varscan_folder)){
included_callers[3]<-"VarScan"
raw_calls[[3]]<-readInput(input$varscan_folder,
input$varscan_file_names_add,
input$varscan_file_type,
input$varscan_snv_indel,
input$varscan_snv_names_add,
input$varscan_indel_names_add,
input$varscan_chr,
input$varscan_pos,
input$varscan_ref,
input$varscan_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$varscan_folder,
input$varscan_file_names_add,
input$varscan_file_type,
input$varscan_snv_indel,
input$varscan_snv_names_add,
input$varscan_indel_names_add))
}
progress$inc(1/13)
raw_calls[[4]]<-list()
if(!is.null(input$freebayes_folder)){
included_callers[4]<-"FreeBayes"
raw_calls[[4]]<-readInput(input$freebayes_folder,
input$freebayes_file_names_add
,input$freebayes_file_type,
input$freebayes_snv_indel,
input$freebayes_snv_names_add,
input$freebayes_indel_names_add,
input$freebayes_chr,
input$freebayes_pos,
input$freebayes_ref,
input$freebayes_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$freebayes_folder,
input$freebayes_file_names_add,
input$freebayes_file_type,
input$freebayes_snv_indel,
input$freebayes_snv_names_add,
input$freebayes_indel_names_add))
}
progress$inc(1/13)
raw_calls[[5]]<-list()
if(!is.null(input$lofreq_folder)){
included_callers[5]<-"LoFreq"
raw_calls[[5]]<-readInput(input$lofreq_folder,
input$lofreq_file_names_add,
input$lofreq_file_type,
input$lofreq_snv_indel,
input$lofreq_snv_names_add,
input$lofreq_indel_names_add,
input$lofreq_chr,
input$lofreq_pos,
input$lofreq_ref,
input$lofreq_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$lofreq_folder,
input$lofreq_file_names_add,
input$lofreq_file_type,
input$lofreq_snv_indel,
input$lofreq_snv_names_add,
input$lofreq_indel_names_add))
}
progress$inc(1/13)
raw_calls[[6]]<-list()
if(!is.null(input$snver_folder)){
included_callers[6]<-"SNVer"
raw_calls[[6]]<-readInput(input$snver_folder,
input$snver_file_names_add,
input$snver_file_type,
input$snver_snv_indel,
input$snver_snv_names_add,
input$snver_indel_names_add,
input$snver_chr,
input$snver_pos,
input$snver_ref,input$snver_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$snver_folder,
input$snver_file_names_add,
input$snver_file_type,
input$snver_snv_indel,
input$snver_snv_names_add,
input$snver_indel_names_add))
}
progress$inc(1/13)
raw_calls[[7]]<-list()
if(!is.null(input$samtools_folder)){
included_callers[7]<-"SamTools"
raw_calls[[7]]<-readInput(input$samtools_folder,
input$samtools_file_names_add,
input$samtools_file_type,
input$samtools_snv_indel,
input$samtools_snv_names_add,
input$samtools_indel_names_add,
input$samtools_chr,
input$samtools_pos,
input$samtools_ref,
input$samtools_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$samtools_folder,
input$samtools_file_names_add,
input$samtools_file_type,
input$samtools_snv_indel,
input$samtools_snv_names_add,
input$samtools_indel_names_add))
}
progress$inc(1/13)
raw_calls[[8]]<-list()
if(!is.null(input$vardict_folder)){
included_callers[8]<-"VarDict"
raw_calls[[8]]<-readInput(input$vardict_folder,
input$vardict_file_names_add,
input$vardict_file_type,
input$vardict_snv_indel,
input$vardict_snv_names_add,
input$vardict_indel_names_add,
input$vardict_chr,
input$vardict_pos,
input$vardict_ref,
input$vardict_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$vardict_folder,
input$vardict_file_names_add,
input$vardict_file_type,
input$vardict_snv_indel,
input$vardict_snv_names_add,
input$vardict_indel_names_add))
}
if(is.null(input$caller1_folder)){
progress$inc(5/13)
}
if(!is.null(input$caller1_folder)){
progress$inc(1/13)
raw_calls[[9]]<-list()
included_callers[9]<-input$caller1_name
raw_calls[[9]]<-readInput(input$caller1_folder,
input$caller1_file_names_add,
input$caller1_file_type,
input$caller1_snv_indel,
input$caller1_snv_names_add,
input$caller1_indel_names_add,
input$caller1_chr,
input$caller1_pos,
input$caller1_ref,
input$caller1_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$caller1_folder,
input$caller1_file_names_add,
input$caller1_file_type,
input$caller1_snv_indel,
input$caller1_snv_names_add,
input$caller1_indel_names_add))
if(is.null(input$caller2_folder)){
progress$inc(4/13)
}
if(!is.null(input$caller2_folder)){
progress$inc(1/13)
raw_calls[[10]]<-list()
included_callers[10]<-input$caller2_name
raw_calls[[10]]<-readInput(input$caller2_folder,
input$caller2_file_names_add,
input$caller2_file_type,
input$caller2_snv_indel,
input$caller2_snv_names_add,
input$caller2_indel_names_add,
input$caller2_chr,
input$caller2_pos,
input$caller2_ref,
input$caller2_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$caller2_folder,
input$caller2_file_names_add,
input$caller2_file_type,
input$caller2_snv_indel,
input$caller2_snv_names_add,
input$caller2_indel_names_add))
if(is.null(input$caller3_folder)){
progress$inc(3/13)
}
if(!is.null(input$caller3_folder)){
progress$inc(1/13)
raw_calls[[11]]<-list()
included_callers[11]<-input$caller3_name
raw_calls[[11]]<-readInput(input$caller3_folder,
input$caller3_file_names_add,
input$caller3_file_type,
input$caller3_snv_indel,
input$caller3_snv_names_add,
input$caller3_indel_names_add,
input$caller3_chr,
input$caller3_pos,
input$caller3_ref,
input$caller3_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$caller3_folder,
input$caller3_file_names_add,
input$caller3_file_type,
input$caller3_snv_indel,
input$caller3_snv_names_add,
input$caller3_indel_names_add))
if(is.null(input$caller4_folder)){
progress$inc(2/13)
}
if(!is.null(input$caller4_folder)){
progress$inc(1/13)
raw_calls[[12]]<-list()
included_callers[12]<-input$caller4_name
raw_calls[[12]]<-readInput(input$caller4_folder,
input$caller4_file_names_add,
input$caller4_file_type,
input$caller4_snv_indel,
input$caller4_snv_names_add,
input$caller4_indel_names_add,
input$caller4_chr,
input$caller4_pos,
input$caller4_ref,
input$caller4_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$caller4_folder,
input$caller4_file_names_add,
input$caller4_file_type,
input$caller4_snv_indel,
input$caller4_snv_names_add,
input$caller4_indel_names_add))
if(is.null(input$caller5_folder)){
progress$inc(1/13)
}
if(!is.null(input$caller5_folder)){
progress$inc(1/13)
raw_calls[[13]]<-list()
included_callers[13]<-input$caller5_name
raw_calls[[13]]<-readInput(input$caller5_folder,
input$caller5_file_names_add,
input$caller5_file_type,
input$caller5_snv_indel,
input$caller5_snv_names_add,
input$caller5_indel_names_add,
input$caller5_chr,
input$caller5_pos,
input$caller5_ref,
input$caller5_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$caller5_folder,
input$caller5_file_names_add,
input$caller5_file_type,
input$caller5_snv_indel,
input$caller5_snv_names_add,
input$caller5_indel_names_add))
}
}
}
}
}
#Test for sample names
sampleNameTest<-as.data.frame(sampleNameTest[,!is.na(sampleNameTest[1,])])
if(length(sampleNameTest[1,])==0){
log_info<-c(log_info,"Please check your input files<br>")
output$log_info<-renderUI({HTML(log_info)})
}
if(length(sampleNameTest[1,])==1){
for(i in seq_along(sampleNameTest[,1])){
overview[i,1]<-as.character(sampleNameTest[i,1])
}
output$table <- renderDataTable(datatable(overview))
}
if(length(sampleNameTest[1,])>1){
for(i in seq_along(sampleNameTest[,1])){
compareSample<-sampleNameTest[i,1]
flag<-TRUE
for(j in 2:length(sampleNameTest[1,])){
if(compareSample!=sampleNameTest[i,j]){
flag<-FALSE
}
if(flag==TRUE){
overview[i,1]<-compareSample
}
if(flag==FALSE){
log_info<-c(log_info,
"At least one output file is missing<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
}
}
output$table <- renderDataTable(datatable(overview))
}
#Report raw calls
for(i in seq_along(raw_calls)){
for(j in seq_along(overview[,1])){
if(length(raw_calls[[i]])>0&&
!is.na(raw_calls[[i]][[j]][1,2])){
overview[j,i+1]<-length(raw_calls[[i]][[j]][,1])
}
}
}
progress$close()
#1. Target filtration
log_info<-c(log_info,"1. Target filtration<br>")
output$log_info<-renderUI({HTML(log_info)})
if(is.null(input$targetRegions)){
log_info<-c(log_info,
"Please provide a target regions file<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
progress <- shiny::Progress$new()
progress$set(message = "1. Target filtration", value = 0)
if(!is.null(input$targetRegions)){
for(i in seq_along(overview[,1])){
overview[i,1]<-as.character(overview[i,1])
}
overview2<-overview
overview2[c(seq_along(overview[,1])),c(2:length(overview[1,]))]<-NA
checkpoint<-overview
checkpoint[c(seq_along(overview[,1])),c(2:length(overview[1,]))]<-NA
target_calls<-list()
target_temp<-input$targetRegions
target<-read.table(target_temp$datapath,
header=FALSE,sep="\t",
stringsAsFactors=FALSE)
for(i in seq_along(raw_calls)){
progress$inc(1/length(raw_calls),
detail=paste("->",
as.character(names(overview[i+1]))))
target_calls[[i]]<-list()
if(length(raw_calls[[i]])>0){
for(j in seq_along(overview[,1])){
checkpoint[j,i+1]<-1
if(!is.na(raw_calls[[i]][[j]][1,2])){
include<-rep(FALSE,length(raw_calls[[i]][[j]][,1]))
for(k in seq_along(raw_calls[[i]][[j]][,1])){
flag1<-as.character(raw_calls[[i]][[j]][k,2])==as.character(target[,1])
flag2<-raw_calls[[i]][[j]][k,3]>target[,2]
flag3<-raw_calls[[i]][[j]][k,3]<=target[,3]
if(sum(rowSums(cbind(flag1,flag2,flag3))==3)>0){
include[k]<-TRUE
}
}
target_calls[[i]][[j]]<-raw_calls[[i]][[j]][include,]
names(target_calls[[i]][[j]])<-c("SampleID",
"Chr",
"Pos",
"Ref",
"Alt")
write.table(target_calls[[i]][[j]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".",overview[j,1],
".target.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
overview2[j,i+1]<-length(target_calls[[i]][[j]][,1])
}
if(is.na(raw_calls[[i]][[j]][1,2])){
noCallsAvailable<-data.frame(noCalls=NA)
write.table(noCallsAvailable,
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".",overview[j,1],
".target.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
}
}
}
output$table2 <- renderDataTable(datatable(overview2))
write.table(checkpoint,paste(input$output_folder,
"/checkpoint.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
progress$close()
#2. Normalization
log_info<-c(log_info,"2. Normalization<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "2. Normalization", value = 0)
normalized_calls<-list()
for(i in seq_along(target_calls)){
progress$inc(1/length(target_calls),
detail=paste("->",
as.character(names(overview[i+1]))))
normalized_calls[[i]]<-list()
if(length(target_calls[[i]])>0){
temp<-target_calls[[i]][[1]]
checkpoint[1,i+1]<-2
if(!is.na(temp[1,2])&&length(overview[,1])>1){
for(j in 2:length(overview[,1])){
temp<-rbind(temp,target_calls[[i]][[j]])
checkpoint[j,i+1]<-2
}
}
#GATK
if(i==1){
if(input$gatk_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$gatk_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#Platypus
if(i==2){
if(input$platypus_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$platypus_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#VarScan
if(i==3){
if(input$varscan_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$varscan_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#FreeBayes
if(i==4){
if(input$freebayes_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$freebayes_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#LoFreq
if(i==5){
if(input$lofreq_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$lofreq_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#SNVer
if(i==6){
if(input$snver_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$snver_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#SamTools
if(i==7){
if(input$samtools_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$samtools_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#VarDict
if(i==8){
if(input$vardict_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$vardict_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
if(length(target_calls)>8){
#Caller 1
if(i==9){
if(input$caller1_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller1_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
if(length(target_calls)>9){
#Caller 2
if(i==10){
if(input$caller2_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller2_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
if(length(target_calls)>10){
#Caller 3
if(i==11){
if(input$caller3_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller3_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,
"/",
as.character(names(overview)[i+1]),
".normalized.txt",
sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
if(length(target_calls)>11){
#Caller 4
if(i==12){
if(input$caller4_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller4_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,
"/",
as.character(names(overview)[i+1]),
".normalized.txt",
sep=""),
row.names=FALSE,
quote=FALSE,
sep="\t")
}
if(length(target_calls)>12){
#Caller 5
if(i==13){
if(input$caller5_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller5_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,
"/",
as.character(names(overview)[i+1]),
".normalized.txt",
sep=""),
row.names=FALSE,
quote=FALSE,
sep="\t")
}
}
}
}
}
}
}
}
write.table(checkpoint,paste(input$output_folder,
"/checkpoint.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
progress$close()
#3. Annotate
log_info<-c(log_info,"3. Annotate<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "3. Annotate", value = 0)
annotated_calls<-list()
overview3<-overview
overview3[c(seq_along(overview[,1])),c(2:length(overview[1,]))]<-NA
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
connection_txid_symbol<-transcripts(Homo.sapiens,
columns=c("TXID","SYMBOL"))
for(i in seq_along(normalized_calls)){
progress$inc(1/length(normalized_calls))
annotated_calls[[i]]<-data.frame()
if(length(normalized_calls[[i]])>0){
progress_small <- shiny::Progress$new()
progress_small$set(message = as.character(names(overview[i+1])), value = 0)
test<-VCF(rowRanges=GRanges(seqnames=paste("chr",
as.character(normalized_calls[[i]][,2]),
sep=""),
ranges=IRanges(as.numeric(normalized_calls[[i]][,3]),
(as.numeric(normalized_calls[[i]][,3])+nchar(normalized_calls[[i]][,4])-1))),
fixed=DataFrame(REF=DNAStringSet(normalized_calls[[i]][,4]),
ALT=DNAStringSetList(strsplit(normalized_calls[[i]][,5],",",fixed=TRUE)),
QUAL=1,
FILTER=as.character(normalized_calls[[i]][,1])))
if(is.null(input$locations)){
log_info<-c(log_info,"Please pick at least one location<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$locations)){
located<-locateVariants(test,txdb,AllVariants())
for(j in seq_along(input$locations)){
if(j==1){
of_interest<-data.frame(located$LOCATION==input$locations[j])
}
if(j>1){
of_interest<-data.frame(of_interest,
located$LOCATION==input$locations[j])
}
}
if(length(input$locations)==1){
located<-located[of_interest[,1]>0,]
}
if(length(input$locations)>1){
located<-located[rowSums(of_interest)>0,]
}
}
if(sum(input$locations=="coding")>0&&
is.null(input$consequences)){
log_info<-c(log_info,"Please pick at least one consequence<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$consequences)){
predicted<-predictCoding(query=test,subject=txdb,
seqSource=Hsapiens)
for(j in seq_along(predicted[,1])){
if(as.character(predicted$REFCODON[j])=="CTG"){
if(as.character(predicted$VARCODON[j])=="ATG"){
predicted$CONSEQUENCE[j]<-"nonsynonymous"
}
if(as.character(predicted$VARCODON[j])=="CTA"||
as.character(predicted$VARCODON[j])=="CTC"||
as.character(predicted$VARCODON[j])=="CTT"||
as.character(predicted$VARCODON[j])=="TTA"||
as.character(predicted$VARCODON[j])=="TTG"){
predicted$CONSEQUENCE[j]<-"synonymous"
}
}
if(as.character(predicted$VARCODON[j])=="CTG"){
if(as.character(predicted$REFCODON[j])=="ATG"){
predicted$CONSEQUENCE[j]<-"nonsynonymous"
}
if(as.character(predicted$REFCODON[j])=="CTA"||
as.character(predicted$REFCODON[j])=="CTC"||
as.character(predicted$REFCODON[j])=="CTT"||
as.character(predicted$REFCODON[j])=="TTA"||
as.character(predicted$REFCODON[j])=="TTG"){
predicted$CONSEQUENCE[j]<-"synonymous"
}
}
if(as.character(predicted$REFCODON[j])=="TTG"){
if(as.character(predicted$VARCODON[j])=="ATG"){
predicted$CONSEQUENCE[j]<-"nonsynonymous"
}
if(as.character(predicted$VARCODON[j])=="CTA"||
as.character(predicted$VARCODON[j])=="CTC"||
as.character(predicted$VARCODON[j])=="CTT"||
as.character(predicted$VARCODON[j])=="TTA"||
as.character(predicted$VARCODON[j])=="CTG"){
predicted$CONSEQUENCE[j]<-"synonymous"
}
}
if(as.character(predicted$VARCODON[j])=="TTG"){
if(as.character(predicted$REFCODON[j])=="ATG"){
predicted$CONSEQUENCE[j]<-"nonsynonymous"
}
if(as.character(predicted$REFCODON[j])=="CTA"||
as.character(predicted$REFCODON[j])=="CTC"||
as.character(predicted$REFCODON[j])=="CTT"||
as.character(predicted$REFCODON[j])=="TTA"||
as.character(predicted$REFCODON[j])=="CTG"){
predicted$CONSEQUENCE[j]<-"synonymous"
}
}
}
for(j in seq_along(input$consequences)){
if(j==1){
of_interest<-data.frame(predicted$CONSEQUENCE==input$consequences[j])
}
if(j>1){
of_interest<-data.frame(of_interest,
predicted$CONSEQUENCE==input$consequences[j])
}
}
if(length(input$consequences)==1){
predicted<-predicted[of_interest[,1]>0,]
}
if(length(input$consequences)>1){
predicted<-predicted[rowSums(of_interest)>0,]
}
}
annotated_calls[[i]]<-data.frame(normalized_calls[[i]],
Location=NA,c.=NA,
p.=NA,AA_ref=NA,
AA_alt=NA,Codon_ref=NA,
Codon_alt=NA,
Consequence=NA,Gene=NA,
GeneID=NA,
TranscriptID=NA)
counter_located<-1
counter_predicted<-1
keep<-rep(TRUE,length(annotated_calls[[i]][,1]))
for(k in seq_along(annotated_calls[[i]][,1])){
progress_small$inc(1/length(annotated_calls[[i]][,1]),
detail=paste("-> Call",k,
"out of",
length(annotated_calls[[i]][,1])))
while(counter_located<=length(ranges(located))&&
start(ranges(located))[counter_located]==annotated_calls[[i]][k,3]){
if(!is.na(annotated_calls[[i]][k,6])){
annotated_calls[[i]][k,6]<-paste(annotated_calls[[i]][k,6],
as.character(located$LOCATION[counter_located]),
sep=",")
annotated_calls[[i]][k,7]<-paste(annotated_calls[[i]][k,7],
as.character(located$LOCSTART[counter_located]),
sep=",")
}
if(is.na(annotated_calls[[i]][k,6])){
annotated_calls[[i]][k,6]<-as.character(located$LOCATION[counter_located])
annotated_calls[[i]][k,7]<-as.character(located$LOCSTART[counter_located])
}
counter_located<-counter_located+1
}
if(!is.na(annotated_calls[[i]][k,6])&&
!is.null(input$consequences)){
for(j in seq_along(strsplit(annotated_calls[[i]][k,6],",")[[1]])){
if(counter_predicted>length(ranges(predicted))||
strsplit(annotated_calls[[i]][k,6],",")[[1]][j]!="coding"){
if(!is.na(annotated_calls[[i]][k,8])){
annotated_calls[[i]][k,8]<-paste(annotated_calls[[i]][k,8],"NA",sep=",")
annotated_calls[[i]][k,9]<-paste(annotated_calls[[i]][k,9],"NA",sep=",")
annotated_calls[[i]][k,10]<-paste(annotated_calls[[i]][k,10],"NA",sep=",")
annotated_calls[[i]][k,11]<-paste(annotated_calls[[i]][k,11],"NA",sep=",")
annotated_calls[[i]][k,12]<-paste(annotated_calls[[i]][k,12],"NA",sep=",")
annotated_calls[[i]][k,13]<-paste(annotated_calls[[i]][k,13],"NA",sep=",")
annotated_calls[[i]][k,14]<-paste(annotated_calls[[i]][k,14],"NA",sep=",")
annotated_calls[[i]][k,15]<-paste(annotated_calls[[i]][k,15],"NA",sep=",")
annotated_calls[[i]][k,16]<-paste(annotated_calls[[i]][k,16],"NA",sep=",")
}
if(is.na(annotated_calls[[i]][k,8])){
annotated_calls[[i]][k,8]<-annotated_calls[[i]][k,9]<-"NA"
annotated_calls[[i]][k,10]<-annotated_calls[[i]][k,11]<-"NA"
annotated_calls[[i]][k,12]<-annotated_calls[[i]][k,13]<-"NA"
annotated_calls[[i]][k,14]<-"NA"
annotated_calls[[i]][k,15]<-annotated_calls[[i]][k,16]<-"NA"
}
}
if(counter_predicted<=length(ranges(predicted))&&
strsplit(annotated_calls[[i]][k,6],",")[[1]][j]=="coding"){
if(start(ranges(predicted))[counter_predicted]==annotated_calls[[i]][k,3]){
if(!is.na(annotated_calls[[i]][k,8])){
annotated_calls[[i]][k,8]<-paste(annotated_calls[[i]][k,8],
as.character(predicted$PROTEINLOC[counter_predicted][[1]][1]),
sep=",")
if(as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])!="frameshift"){
if(as.character(predicted$REFCODON[counter_predicted])!="CTG"){
annotated_calls[[i]][k,9]<-paste(annotated_calls[[i]][k,9],
as.character(predicted$REFAA[counter_predicted][[1]][1]),
sep=",")
}
if(as.character(predicted$REFCODON[counter_predicted])=="CTG"){
annotated_calls[[i]][k,9]<-paste(annotated_calls[[i]][k,9],
"L",
sep=",")
}
if(as.character(predicted$VARCODON[counter_predicted])!="CTG"){
annotated_calls[[i]][k,10]<-paste(annotated_calls[[i]][k,10],
as.character(predicted$VARAA[counter_predicted][[1]][1]),
sep=",")
}
if(as.character(predicted$VARCODON[counter_predicted])=="CTG"){
annotated_calls[[i]][k,10]<-paste(annotated_calls[[i]][k,10],"L",sep=",")
}
}
if(as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])=="frameshift"){
annotated_calls[[i]][k,9]<-paste(annotated_calls[[i]][k,9],"NA",sep=",")
annotated_calls[[i]][k,10]<-paste(annotated_calls[[i]][k,10],"NA",sep=",")
}
annotated_calls[[i]][k,11]<-paste(annotated_calls[[i]][k,11],
as.character(predicted$REFCODON[counter_predicted]),
sep=",")
annotated_calls[[i]][k,12]<-paste(annotated_calls[[i]][k,12],
as.character(predicted$VARCODON[counter_predicted]),
sep=",")
annotated_calls[[i]][k,13]<-paste(annotated_calls[[i]][k,13],
as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1]),
sep=",")
annotated_calls[[i]][k,14]<-paste(annotated_calls[[i]][k,14],
as.character(connection_txid_symbol[as.numeric(predicted$TXID[counter_predicted][[1]][1]),]$SYMBOL),
sep=",")
annotated_calls[[i]][k,15]<-paste(annotated_calls[[i]][k,15],
as.character(predicted$GENEID[counter_predicted][[1]][1]),
sep=",")
annotated_calls[[i]][k,16]<-paste(annotated_calls[[i]][k,16],
as.character(predicted$TXID[counter_predicted][[1]][1]),
sep=",")
}
if(is.na(annotated_calls[[i]][k,8])){
annotated_calls[[i]][k,8]<-as.character(predicted$PROTEINLOC[counter_predicted][[1]][1])
if(as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])!="frameshift"){
if(as.character(predicted$REFCODON[counter_predicted])!="CTG"){
annotated_calls[[i]][k,9]<-as.character(predicted$REFAA[counter_predicted][[1]][1])
}
if(as.character(predicted$REFCODON[counter_predicted])=="CTG"){
annotated_calls[[i]][k,9]<-"L"
}
if(as.character(predicted$VARCODON[counter_predicted])!="CTG"){
annotated_calls[[i]][k,10]<-as.character(predicted$VARAA[counter_predicted][[1]][1])
}
if(as.character(predicted$VARCODON[counter_predicted])=="CTG"){
annotated_calls[[i]][k,10]<-"L"
}
}
if(as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])=="frameshift"){
annotated_calls[[i]][k,9]<-"NA"
annotated_calls[[i]][k,10]<-"NA"
}
annotated_calls[[i]][k,11]<-as.character(predicted$REFCODON[counter_predicted])
annotated_calls[[i]][k,12]<-as.character(predicted$VARCODON[counter_predicted])
annotated_calls[[i]][k,13]<-as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])
annotated_calls[[i]][k,14]<-as.character(connection_txid_symbol[as.numeric(predicted$TXID[counter_predicted][[1]][1]),]$SYMBOL)
annotated_calls[[i]][k,15]<-as.character(predicted$GENEID[counter_predicted][[1]][1])
annotated_calls[[i]][k,16]<-as.character(predicted$TXID[counter_predicted][[1]][1])
}
counter_predicted<-counter_predicted+1
}
}
}
}
if(is.na(annotated_calls[[i]][k,6])){
keep[k]<-FALSE
}
if(!is.null(input$consequences)&&
!is.na(annotated_calls[[i]][k,6])&&
sum(strsplit(annotated_calls[[i]][k,6],",")[[1]]=="coding")>0&&
(is.na(annotated_calls[[i]][k,8])||
sum(strsplit(annotated_calls[[i]][k,8],",")[[1]]=="NA")==length(strsplit(annotated_calls[[i]][k,8],",")[[1]]))){
keep[k]<-FALSE
}
}
annotated_calls[[i]]<-annotated_calls[[i]][keep,]
for(k in seq_along(overview3[,1])){
overview3[k,i+1]<-length(annotated_calls[[i]][annotated_calls[[i]][,1]==overview3[k,1],1])
checkpoint[k,i+1]<-3
}
write.table(annotated_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".annotated.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
progress_small$close()
}
}
write.table(checkpoint,paste(input$output_folder,
"/checkpoint.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
output$table3 <- renderDataTable(datatable(overview3))
progress$close()
#4. Combine
log_info<-c(log_info,"4. Combine Output<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "4. Combine Output", value = 0)
combined_calls<-data.frame(SampleID=NA,Chr=NA,Pos=NA,Ref=NA,
Alt=NA,Location=NA,c.=NA,p.=NA,
AA_ref=NA,AA_alt=NA,Codon_ref=NA,
Codon_alt=NA,Consequence=NA,Gene=NA,
GeneID=NA,TranscriptID=NA,
GATK=NA,Platypus=NA,VarScan=NA,
FreeBayes=NA,LoFreq=NA,SNVer=NA,
SamTools=NA,VarDict=NA)
if(length(annotated_calls)>8){
combined_calls<-cbind(combined_calls,Caller1=NA)
if(length(annotated_calls)>9){
combined_calls<-cbind(combined_calls,Caller2=NA)
if(length(annotated_calls)>10){
combined_calls<-cbind(combined_calls,Caller3=NA)
if(length(annotated_calls)>11){
combined_calls<-cbind(combined_calls,Caller4=NA)
if(length(annotated_calls)>12){
combined_calls<-cbind(combined_calls,
Caller5=NA)
}
}
}
}
}
combined_calls_temp<-combined_calls
overview4<-cbind(overview[,1],RawCalls=NA)
for(i in seq_along(annotated_calls)){
if(length(annotated_calls[[i]])>0){
temp<-annotated_calls[[i]]
add_to_temp<-matrix(rep(NA,(length(combined_calls[1,])-16)),
ncol=(length(combined_calls[1,])-16))
temp<-cbind(temp,add_to_temp)
names(temp)<-names(combined_calls)
temp[,16+i]<-1
combined_calls_temp<-rbind(combined_calls_temp,temp)
}
}
combined_calls_temp<-combined_calls_temp[2:length(combined_calls_temp[,1]),]
combined_calls_temp_sorted<-combined_calls_temp[order(combined_calls_temp[,2],
combined_calls_temp[,3],
combined_calls_temp[,4],
combined_calls_temp[,5],
combined_calls_temp[,1]),]
combined_calls<-combined_calls_temp_sorted[1,]
counter<-1
for(i in 2:length(combined_calls_temp_sorted[,1])){
progress$inc(1/length(combined_calls_temp_sorted[,1]))
if(combined_calls[counter,1]==combined_calls_temp_sorted[i,1]&&
combined_calls[counter,2]==combined_calls_temp_sorted[i,2]&&
combined_calls[counter,3]==combined_calls_temp_sorted[i,3]&&
combined_calls[counter,4]==combined_calls_temp_sorted[i,4]&&
combined_calls[counter,5]==combined_calls_temp_sorted[i,5]){
for(j in 17:length(combined_calls[1,])){
if(!is.na(combined_calls[counter,j])||
!is.na(combined_calls_temp_sorted[i,j])){
combined_calls[counter,j]<-1
}
}
}
if(combined_calls[counter,1]!=combined_calls_temp_sorted[i,1]||
combined_calls[counter,2]!=combined_calls_temp_sorted[i,2]||
combined_calls[counter,3]!=combined_calls_temp_sorted[i,3]||
combined_calls[counter,4]!=combined_calls_temp_sorted[i,4]||
combined_calls[counter,5]!=combined_calls_temp_sorted[i,5]){
counter<-counter+1
combined_calls<-rbind(combined_calls,
combined_calls_temp_sorted[i,])
}
}
temp<-unique(combined_calls)
combined_calls<-temp
for(i in seq_along(overview4[,1])){
overview4[i,2]<-length(combined_calls[combined_calls[,1]==overview4[i,1],1])
for(j in seq_along(annotated_calls)){
if(length(annotated_calls[[j]])>0){
checkpoint[i,j+1]<-4
}
}
}
write.table(combined_calls,paste(input$output_folder,
"/Results_Raw.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
write.table(checkpoint,paste(input$output_folder,
"/checkpoint.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
output$table4 <- renderDataTable(datatable(overview4))
progress$close()
#5. Pileup
log_info<-c(log_info,"5. Evaluate Coverage and BQ<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "5. Evaluate Coverage and BQ", value = 0)
results<-cbind(combined_calls[,c(1:5)],Nr_Ref=NA,Nr_Alt=NA,
DP=NA,VAF=NA,BQ_REF=NA,BQ_ALT=NA,
Nr_Ref_fwd=NA,Nr_Alt_fwd=NA,DP_fwd=NA,VAF_fwd=NA,
Nr_Ref_rev=NA,Nr_Alt_rev=NA,DP_rev=NA,VAF_rev=NA)
folder<-input$bam_folder
for(i in seq_along(results[,1])){
progress$inc(1/length(results[,1]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
done<-FALSE
#SNVs
if(nchar(results[i,4])==1&&nchar(results[i,5])==1){
results_temp<-getCharacteristicsFreq(results[i,2],
results[i,3],
results[i,3],
results[i,4],
results[i,5],
folder,
results[i,1])
results[i,6:19]<-results_temp[1,6:19]
if(results[i,8]>=input$dp&&results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
results[i,3],
results[i,3],
results[i,4],
results[i,5],
folder,
results[i,1])
results[i,10:11]<-results_temp[1,6:7]
}
done<-TRUE
}
#Deletions
if(done==FALSE&&nchar(results[i,4])>1&&nchar(results[i,5])==1
&&substr(results[i,4],1,1)==results[i,5]){
if(nchar(results[i,4])==2){
results_temp<-getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+1,
as.numeric(results[i,3])+1,
substr(results[i,4],2,2),
"-",folder,
results[i,1])
results[i,6:19]<-results_temp[1,6:19]
if(results[i,8]>=input$dp&&
results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+1,
as.numeric(results[i,3])+1,
substr(results[i,4],2,2),
"-",folder,
results[i,1])
results[i,10:11]<-results_temp[1,6:7]
}
}
if(nchar(results[i,4])>2){
results_temp<-getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+1,
as.numeric(results[i,3])+1,
substr(results[i,4],2,2),
"-",folder,
results[i,1])
for(j in 3:nchar(results[i,4])){
results_temp<-rbind(results_temp,
getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
"-",
folder,results[i,1]))
}
for(j in 6:19){
results[i,j]<-min(results_temp[,j])
}
if(results[i,8]>=input$dp&&
results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+1,
as.numeric(results[i,3])+1,
substr(results[i,4],2,2),
"-",folder,
results[i,1])
for(j in 3:nchar(results[i,4])){
results_temp<-rbind(results_temp,
getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
"-",folder,results[i,1]))
}
for(j in 6:7){
results_temp[1,j]<-min(results_temp[,j])
}
results[i,10:11]<-results_temp[1,6:7]
}
}
done<-TRUE
}
#Insertions (summed up as +)
if(done==FALSE&&nchar(results[i,4])==1&&nchar(results[i,5])>1
&&substr(results[i,5],1,1)==results[i,4]){
results_temp<-getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3]),
as.numeric(results[i,3]),
results[i,4],
"+",folder,
results[i,1])
results[i,6:19]<-results_temp[1,6:19]
if(results[i,8]>=input$dp&&results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3]),
as.numeric(results[i,3]),
results[i,4],
"+",folder,
results[i,1])
results[i,10:11]<-results_temp[1,6:7]
}
done<-TRUE
}
#Complex Indels
if(done==FALSE){
results_temp<-getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3]),
as.numeric(results[i,3]),
substr(results[i,4],1,1),
substr(results[i,5],1,1),
folder,
results[i,1])
for(j in 2:min(nchar(results[i,4]),nchar(results[i,5]))){
results_temp<-rbind(results_temp,
getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
substr(results[i,5],j,j),
folder,
results[i,1]))
}
#Del in the end
if(nchar(results[i,4])>nchar(results[i,5])){
results_temp<-rbind(results_temp,
getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+j,
as.numeric(results[i,3])+j,
substr(results[i,4],j+1,j+1),
"-",
folder,
results[i,1]))
}
#Ins in the end
if(nchar(results[i,4])>nchar(results[i,5])){
results_temp<-rbind(results_temp,
getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
"+",
folder,
results[i,1]))
}
for(j in 6:19){
results[i,j]<-min(results_temp[,j])
}
if(results[i,8]>=input$dp&&results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3]),
as.numeric(results[i,3]),
substr(results[i,4],1,1),
substr(results[i,5],1,1),
folder,
results[i,1])
for(j in 2:min(nchar(results[i,4]),nchar(results[i,5]))){
results_temp<-rbind(results_temp,
getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
substr(results[i,5],j,j),
folder,
results[i,1]))
}
#Del in the end
if(nchar(results[i,4])>nchar(results[i,5])){
results_temp<-rbind(results_temp,
getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+j,
as.numeric(results[i,3])+j,
substr(results[i,4],j+1,j+1),
"-",
folder,
results[i,1]))
}
#Ins in the end
if(nchar(results[i,4])>nchar(results[i,5])){
results_temp<-rbind(results_temp,
getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
"+",
folder,
results[i,1]))
}
for(j in 6:7){
results_temp[1,j]<-min(results_temp[,j])
}
results[i,10:11]<-results_temp[1,6:7]
}
}
}
frequency_calls_temp<-cbind(combined_calls,results[,c(6:19)])
include1<-results[,8]>=input$dp
include2<-results[,7]>=input$nr_alt
include3<-(results[,9]*100)>=input$vaf
include4<-results[,11]>=input$bq
for(i in seq_along(results[,1])){
if(is.na(results[i,10])){
results[i,10]<-0
}
}
include5<-(results[,10]-results[,11])<=input$bq_diff
frequency_calls<-frequency_calls_temp[rowSums(cbind(include1,include2,include3,include4,include5))>=5&!is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
overview4<-cbind(overview4,VAFandBQFiltered=NA)
for(i in seq_along(overview4[,1])){
overview4[i,3]<-length(frequency_calls[frequency_calls[,1]==overview4[i,1],1])
for(j in 2:length(checkpoint[1,])){
if(!is.na(checkpoint[i,j])){
checkpoint[i,j]<-5
}
}
}
write.table(frequency_calls,
paste(input$output_folder,
"/Results_Frequency.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
write.table(checkpoint,
paste(input$output_folder,"/checkpoint.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
output$table4 <- renderDataTable(datatable(overview4))
progress$close()
#6. Extended Characteristics
log_info<-c(log_info,
"6. Determine Extended Set of Characteristics<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message="6. Determine Extended Set of Characteristics (databases)",
value=0)
progress$inc(0,detail="-> Downloading databases ")
results<-data.frame(frequency_calls[,c(1:5)])
results<-cbind(results,dbSNP=NA,dbSNP_MAF=NA)
snps<-SNPlocs.Hsapiens.dbSNP144.GRCh37
indels<-XtraSNPlocs.Hsapiens.dbSNP144.GRCh37
if(!is.null(input$`1kgenomes`)){
results<-cbind(results,G1000_AF=NA)
g1000<-MafDb.1Kgenomes.phase3.hs37d5
}
if(!is.null(input$exac)){
results<-cbind(results,ExAC_AF=NA)
exac<-MafDb.ExAC.r1.0.hs37d5
}
if(!is.null(input$gad)){
results<-cbind(results,GAD_AF=NA)
gad<-MafDb.gnomADex.r2.1.hs37d5
}
if(!is.null(input$cosmic)){
results<-cbind(results,CosmicID=NA,Cosmic_Counts=NA)
cosmic_67<-c()
data(cosmic_67,envir = environment(),package = "COSMIC.67")
}
if(!is.null(input$clinvar)){
results<-cbind(results,ClinVar=NA)
clinvar<-data.frame(Gene=NA,Start=NA,Stop=NA,Ref=NA,Alt=NA,
Sig=NA)
genes_temp<-c()
for(i in seq_along(frequency_calls[,1])){
genes_temp<-c(genes_temp,strsplit(frequency_calls[i,14],
split=",")[[1]])
}
genes<-unique(genes_temp[genes_temp!="NA"])
for(i in seq_along(genes)){
res<-entrez_search("clinvar",term=genes[i])
cv<-entrez_summary("clinvar",id=res$ids)
info<-extract_from_esummary(cv,"variation_set",
simplify=FALSE)
significance<-extract_from_esummary(cv,
"clinical_significance",
simplify=FALSE)
for(j in seq_along(res$ids)){
info2<-info[res$ids[j]][[1]][[1]]
significance2<-significance[res$ids[j]][[1]][[1]]
if(length(info2$variation_loc[[1]])){
for(k in seq_along(info2$variation_loc[[1]][,1])){
if(info2$variation_loc[[1]][k,2]=="GRCh37"){
temp<-data.frame(Gene=NA,Start=NA,
Stop=NA,Ref=NA,Alt=NA)
temp[1,1]<-genes[i]
temp[1,2]<-info2$variation_loc[[1]][k,5]
temp[1,3]<-info2$variation_loc[[1]][k,6]
temp[1,4]<-info2$variation_loc[[1]][k,15]
temp[1,5]<-info2$variation_loc[[1]][k,16]
temp[1,6]<-significance2$description
if(!is.na(clinvar[1,1])){
clinvar<-rbind(clinvar,temp)
}
if(is.na(clinvar[1,1])){
clinvar<-temp
}
}
}
}
}
}
}
c.<-c()
c.complement<-c()
p.<-c()
for(i in seq_along(frequency_calls[,1])){
progress$inc(0,detail="-> Pre-processing of the calls ")
for(j in 1:(length(strsplit(frequency_calls[i,7],
split=",")[[1]]))){
if(j==1){
c.[i]<-paste("c.",strsplit(frequency_calls[i,7],
split=",")[[1]][j],
frequency_calls[i,4],">",
frequency_calls[i,5],sep="")
c.complement[i]<-paste("c.",
strsplit(frequency_calls[i,7],
split=",")[[1]][j],
as.character(complement(DNAString(frequency_calls[i,4]))),
">",
as.character(complement(DNAString(frequency_calls[i,5]))),
sep="")
if(!is.na(strsplit(frequency_calls[i,11],
split=",")[[1]][j])&&
!is.na(strsplit(frequency_calls[i,12],
split=",")[[1]][j])&&
strsplit(frequency_calls[i,11],
split=",")[[1]][j]!="NA"&&
strsplit(frequency_calls[i,12],
split=",")[[1]][j]!="NA"&&
nchar(strsplit(frequency_calls[i,11],
split=",")[[1]][j])==3&&
nchar(strsplit(frequency_calls[i,12],
split=",")[[1]][j])==3){
p.[i]<-paste("p.",strsplit(frequency_calls[i,9],
split=",")[[1]][j],
strsplit(frequency_calls[i,8],
split=",")[[1]][j],
strsplit(frequency_calls[i,10],
split=",")[[1]][j],sep="")
}
if(!is.na(strsplit(frequency_calls[i,11],
split=",")[[1]][j])&&
!is.na(strsplit(frequency_calls[i,12],
split=",")[[1]][j])&&
strsplit(frequency_calls[i,11],
split=",")[[1]][j]!="NA"&&
strsplit(frequency_calls[i,12],
split=",")[[1]][j]!="NA"&&
(nchar(strsplit(frequency_calls[i,11],
split=",")[[1]][j])!=3||
nchar(strsplit(frequency_calls[i,12],
split=",")[[1]][j])!=3)){
if((nchar(strsplit(frequency_calls[i,11],
split=",")[[1]][j])%%3)!=0||
(nchar(strsplit(frequency_calls[i,12],
split=",")[[1]][j])%%3)!=0){
p.[i]<-paste("p.",
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,11],split=",")[[1]][j]))),
strsplit(frequency_calls[i,8],
split=",")[[1]][j],
"fs",sep="")
}
if((nchar(strsplit(frequency_calls[i,11],
split=",")[[1]][j])%%3)==0&&
(nchar(strsplit(frequency_calls[i,12],
split=",")[[1]][j])%%3)==0){
p.[i]<-paste("p.",
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,11],split=",")[[1]][j]))),
strsplit(frequency_calls[i,8],
split=",")[[1]][j],
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,12],split=",")[[1]][j]))),sep="")
}
}
}
if(j>1){
c.[i]<-paste(c.[i],paste("c.",
strsplit(frequency_calls[i,7],
split=",")[[1]][j],
frequency_calls[i,4],">",
frequency_calls[i,5],
sep=""),
sep=",")
c.complement[i]<-paste(c.complement[i],
paste("c.",
strsplit(frequency_calls[i,7],split=",")[[1]][j],
as.character(complement(DNAString(frequency_calls[i,4]))),
">",
as.character(complement(DNAString(frequency_calls[i,5]))),
sep=""),
sep=",")
if(!is.na(strsplit(frequency_calls[i,11],
split=",")[[1]][j])&&
!is.na(strsplit(frequency_calls[i,12],
split=",")[[1]][j])&&
strsplit(frequency_calls[i,11],
split=",")[[1]][j]!="NA"&&
strsplit(frequency_calls[i,12],
split=",")[[1]][j]!="NA"&&
nchar(strsplit(frequency_calls[i,11],
split=",")[[1]][j])==3&&
nchar(strsplit(frequency_calls[i,12],
split=",")[[1]][j])==3){
p.[i]<-paste(p.[i],
paste("p.",
strsplit(frequency_calls[i,9],
split=",")[[1]][j],
strsplit(frequency_calls[i,8],
split=",")[[1]][j],
strsplit(frequency_calls[i,10],
split=",")[[1]][j],
sep=""),sep=",")
}
if(!is.na(strsplit(frequency_calls[i,11],
split=",")[[1]][j])&&
!is.na(strsplit(frequency_calls[i,12],
split=",")[[1]][j])&&
strsplit(frequency_calls[i,11],
split=",")[[1]][j]!="NA"&&
strsplit(frequency_calls[i,12],
split=",")[[1]][j]!="NA"&&
(nchar(strsplit(frequency_calls[i,11],
split=",")[[1]][j])!=3||
nchar(strsplit(frequency_calls[i,12],
split=",")[[1]][j])!=3)){
if((nchar(strsplit(frequency_calls[i,11],
split=",")[[1]][j])%%3)!=0||
(nchar(strsplit(frequency_calls[i,12],
split=",")[[1]][j])%%3)!=0){
p.[i]<-paste(p.[i],
paste("p.",
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,11],split=",")[[1]][j]))),
strsplit(frequency_calls[i,8],
split=",")[[1]][j],
"fs",sep=""),sep=",")
}
if((nchar(strsplit(frequency_calls[i,11],
split=",")[[1]][j])%%3)==0&&
(nchar(strsplit(frequency_calls[i,12],
split=",")[[1]][j])%%3)==0){
p.[i]<-paste(p.[i],
paste("p.",
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,11],split=",")[[1]][j]))),
strsplit(frequency_calls[i,8],
split=",")[[1]][j],
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,12],split=",")[[1]][j]))),sep=""),sep=",")
}
}
}
}
}
for(i in seq_along(frequency_calls[,1])){
progress$inc(1/length(results[,1]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
#SNPs
if(nchar(frequency_calls[i,4])==1&&
nchar(frequency_calls[i,5])==1){
snp_info<-snpsByOverlaps(snps,
paste(frequency_calls[i,2],":",
frequency_calls[i,3],"-",
frequency_calls[i,3],
sep=""))
if(length(snp_info)>0){
snp_info<-snp_info[pos(snp_info)==frequency_calls[i,3],]
if(length(snp_info)>0){
if(length(grep(results[i,5],
IUPAC_CODE_MAP[snp_info$alleles_as_ambig]))>0||
(length(grep(results[i,4],
IUPAC_CODE_MAP[snp_info$alleles_as_ambig]))==0&&
length(grep(as.character(complement(DNAString(results[i,5]))),
IUPAC_CODE_MAP[snp_info$alleles_as_ambig])>0))){
results[i,6]<-snp_info$RefSNP_id
}
}
}
if(!is.null(input$`1kgenomes`)){
snp_info<-gscores(g1000,
GRanges(paste(frequency_calls[i,2],
":",
frequency_calls[i,3],
sep="")))
if(length(snp_info)>0){
results$G1000_AF[i]<-max(snp_info$AF)
}
}
if(!is.null(input$exac)){
snp_info<-gscores(exac,
GRanges(paste(frequency_calls[i,2],
":",
frequency_calls[i,3],
sep="")))
if(length(snp_info)>0){
results$ExAC_AF[i]<-max(snp_info$AF)
}
}
if(!is.null(input$gad)){
snp_info<-gscores(gad,
GRanges(paste(frequency_calls[i,2],
":",
frequency_calls[i,3],
sep="")))
if(length(snp_info)>0){
results$GAD_AF[i]<-max(snp_info$AF)
}
}
if(!is.null(input$cosmic)){
snp_info<-rowRanges(cosmic_67)[as.character(seqnames(rowRanges(cosmic_67)))==frequency_calls[i,2]&start(ranges(rowRanges(cosmic_67)))==frequency_calls[i,3]]
if(length(snp_info)>0){
for(j in seq_along(snp_info[,1])){
if(snp_info$REF==frequency_calls[i,4]&&
snp_info$ALT[[1]]==frequency_calls[i,5]||
(snp_info$REF==as.character(complement(DNAString(frequency_calls[i,4])))&&
snp_info$ALT[[1]]==as.character(complement(DNAString(frequency_calls[i,5]))))){
snp_info2<-info(cosmic_67)[rownames(info(cosmic_67))==names(snp_info[j,]),]
grep_c.<-grep(snp_info2$CDS,
as.character(strsplit(c.[i],split=",")[[1]]))
grep_c.comp<-grep(snp_info2$CDS,
as.character(strsplit(c.complement[i],split=",")[[1]]))
grep_p.<-grep(snp_info2$AA,
as.character(strsplit(p.[i],split=",")[[1]]))
if(length(intersect(grep_c.,grep_p.))>0||
length(intersect(grep_c.comp,grep_p.))>0){
if(!is.na(results$CosmicID[i])){
results$CosmicID[i]<-paste(results$CosmicID[i],
names(snp_info[j,]),
sep=",")
results$Cosmic_Counts[i]<-paste(results$Cosmic_Counts[i],
snp_info2$CNT,sep=",")
}
if(is.na(results$CosmicID[i])){
results$CosmicID[i]<-names(snp_info[j,])
results$Cosmic_Counts[i]<-snp_info2$CNT
}
}
}
}
}
}
if(!is.null(input$clinvar)){
snp_info_temp<-data.frame()
for(j in seq_along(strsplit(frequency_calls[i,14],
split=",")[[1]])){
if(!is.na(strsplit(frequency_calls[i,14],
split=",")[[1]][j])){
temp<-clinvar[grep(strsplit(frequency_calls[i,14],
split=",")[[1]][j],
clinvar[,1]),]
temp2<-temp[nchar(temp[,4])==1&nchar(temp[,5])==1&temp[,4]!="-"&temp[,5]!="-",]
if(length(snp_info_temp)>0){
snp_info_temp<-rbind(snp_info_temp,temp2)
}
if(length(snp_info_temp[1,1])==0){
snp_info_temp<-temp2
}
}
}
snp_info<-unique(snp_info_temp)
if(length(snp_info)>0){
snp_info2<-snp_info[snp_info[,2]==frequency_calls[i,3],]
if(length(snp_info2[,1])>0){
if((snp_info2[1,4]==frequency_calls[i,4]&&
snp_info2[1,5]==frequency_calls[i,5])||
(snp_info2[1,4]==as.character(complement(DNAString(frequency_calls[i,4])))
&&snp_info2[1,5]==as.character(complement(DNAString(frequency_calls[i,5]))))){
results$ClinVar[i]<-snp_info2[1,6]
}
}
}
}
}
#Indels
if(nchar(frequency_calls[i,4])!=1||
nchar(frequency_calls[i,5])!=1){
suppressWarnings(snp_info<-snpsByOverlaps(indels,
paste("ch",
frequency_calls[i,2],
":",
frequency_calls[i,3],
"-",
(as.numeric(frequency_calls[i,3])+nchar(frequency_calls[i,4])-1),
sep="")))
if(length(snp_info)>0){
snp_info_rs<-snp_info$RefSNP_id[(start(ranges(snp_info))<=frequency_calls[i,3])&(end(ranges(snp_info))>=(as.numeric(frequency_calls[i,3])+nchar(frequency_calls[i,4])-1))]
if(length(snp_info_rs)>0){
ncbi<-ncbi_snp_query(snp_info_rs)
for(j in seq_along(ncbi[,1])){
if(nchar(results[i,4])>nchar(results[i,5])){
if(length(grep(substr(results[i,4],2,
nchar(results[i,4])),
ncbi[j,9]))>0){
results[i,6]<-ncbi[j,1]
}
}
if(nchar(results[i,4])<nchar(results[i,5])){
if(length(grep(substr(results[i,5],2,
nchar(results[i,5])),
ncbi[j,9]))>0){
results[i,6]<-ncbi[j,1]
}
}
}
}
}
if(!is.null(input$cosmic)){
snp_info<-rowRanges(cosmic_67)[as.character(seqnames(rowRanges(cosmic_67)))==frequency_calls[i,2]&start(ranges(rowRanges(cosmic_67)))==frequency_calls[i,3]]
if(length(snp_info)>0){
for(j in seq_along(snp_info[,1])){
if(snp_info$REF==frequency_calls[i,4]&&
snp_info$ALT[[1]]==frequency_calls[i,5]||
(snp_info$REF==as.character(complement(DNAString(frequency_calls[i,4])))
&&snp_info$ALT[[1]]==as.character(complement(DNAString(frequency_calls[i,5]))))){
snp_info2<-info(cosmic_67)[rownames(info(cosmic_67))==names(snp_info[j,]),]
grep_c.<-grep(snp_info2$CDS,
as.character(strsplit(c.[i],split=",")[[1]]))
grep_c.comp<-grep(snp_info2$CDS,
as.character(strsplit(c.complement[i],split=",")[[1]]))
grep_p.<-grep(snp_info2$AA,
as.character(strsplit(p.[i],split=",")[[1]]))
if(length(intersect(grep_c.,grep_p.))>0||
length(intersect(grep_c.comp,grep_p.))>0){
if(!is.na(results$CosmicID[i])){
results$CosmicID[i]<-paste(results$CosmicID[i],
names(snp_info[j,]),sep=",")
results$Cosmic_Counts[i]<-paste(results$Cosmic_Counts[i],
snp_info2$CNT,sep=",")
}
if(is.na(results$CosmicID[i])){
results$CosmicID[i]<-names(snp_info[j,])
results$Cosmic_Counts[i]<-snp_info2$CNT
}
}
}
}
}
}
if(!is.null(input$clinvar)){
snp_info_temp<-data.frame()
for(j in seq_along(strsplit(frequency_calls[i,14],
split=",")[[1]])){
if(!is.na(strsplit(frequency_calls[i,14],
split=",")[[1]][j])){
temp<-clinvar[grep(strsplit(frequency_calls[i,14],split=",")[[1]][j],
clinvar[,1]),]
temp2<-temp[nchar(temp[,4])>1|nchar(temp[,5])>1|temp[,4]=="-"|temp[,5]=="-",]
if(length(snp_info_temp)>0){
snp_info_temp<-rbind(snp_info_temp,temp2)
}
if(length(snp_info_temp[1,1])==0){
snp_info_temp<-temp2
}
}
}
snp_info<-unique(snp_info_temp)
if(length(snp_info)>0){
snp_info2<-snp_info[snp_info[,2]==(as.numeric(frequency_calls[i,3])-1),]
if(length(snp_info2[,1])>0){
for(j in seq_along(snp_info2[,1])){
if(snp_info2[j,4]=="-"&&
snp_info2[j,5]==substr(frequency_calls[i,5],2,nchar(frequency_calls[i,5]))){
results$ClinVar[i]<-snp_info2[j,6]
}
if(snp_info2[j,5]=="-"&&
snp_info2[j,4]==substr(frequency_calls[i,4],2,nchar(frequency_calls[i,4]))){
results$ClinVar[i]<-snp_info2[j,6]
}
}
}
}
}
}
}
if(length(results[!is.na(results[,6]),6])<=3){
suppressWarnings(ncbi<-ncbi_snp_query(results[!is.na(results[,6]),6]))
}
if(length(results[!is.na(results[,6]),6])>3){
abfrage<-results[!is.na(results[,6]),6]
if(((length(results[!is.na(results[,6]),6])-1)%%3)==0){
limits<-seq(1,length(results[!is.na(results[,6]),6]),3)
}
if(((length(results[!is.na(results[,6]),6])-1)%%3)!=0){
limits<-c(seq(1,length(results[!is.na(results[,6]),6]),
3),
length(results[!is.na(results[,6]),6]))
}
suppressWarnings(ncbi<-ncbi_snp_query(abfrage[1:3]))
for(i in 2:(length(limits)-1)){
suppressWarnings(temp<-ncbi_snp_query(abfrage[limits[i]:(limits[i+1]-1)]))
ncbi<-rbind(ncbi,temp)
}
}
for(i in seq_along(results[,1])){
if(!is.na(results[i,6])){
results$dbSNP_MAF[i]<-as.numeric(max(ncbi[ncbi[,1]==results[i,6],10]))
if(sum(ncbi[ncbi[,1]==results[i,6],9]==results[i,4],na.rm=TRUE)>0){
if(!is.na(results$dbSNP_MAF[i])){
results$dbSNP_MAF[i]<-1-results$dbSNP_MAF[i]
}
if(!is.na(results$G1000_AF[i])){
results$G1000_AF[i]<-1-results$G1000_AF[i]
}
if(!is.na(results$ExAC_AF[i])){
results$ExAC_AF[i]<-1-results$ExAC_AF[i]
}
if(!is.na(results$GAD_AF[i])){
results$GAD_AF[i]<-1-results$GAD_AF[i]
}
}
}
}
progress$close()
results<-cbind(results,Prediction=NA,Score=NA)
progress <- shiny::Progress$new()
progress$set(message = "6. Determine Extended Set of Characteristics (prediction)",
value = 0)
if(input$predict!="PolyPhen2"){
for(i in seq(1,length(results[,6]))[!is.na(results[,6])]){
progress$inc(1/length(seq(1,length(results[,6]))[!is.na(results[,6])]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
suppressWarnings(info<-select(SIFT.Hsapiens.dbSNP137,
keys=substr(results[i,6],3,nchar(results[i,6]))))
if(length(info)>0){
if(input$predict=="SIFT"){
#score <0.05 -> damaging (else: tolerated)
results$Prediction[i]<-info[which.min(info[,15]),16]
results$Score[i]<-min(info[,15])
}
if(input$predict=="Provean"){
#score <-2.5 -> deleterious (else: neutral)
results$Prediction[i]<-info[which.min(info[,11]),12]
results$Score[i]<-min(info[,11])
}
}
}
}
if(input$predict=="PolyPhen2"){
#Polyphen (probably damaging, possibly damaging, benign, unknown); probability of variant being damaging
for(i in seq(1,length(results[,6]))[!is.na(results[,6])]){
progress$inc(1/length(seq(1,length(results[,6]))[!is.na(results[,6])]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
suppressWarnings(info<-select(PolyPhen.Hsapiens.dbSNP131,
keys=results[i,6]))
if(length(info)>0){
if(is.na(max(info[,19]))){
results$Prediction[i]<-"unknown"
results$Score[i]<-max(info[,19])
}
if(!is.na(max(info[,19]))){
results$Prediction[i]<-info[which.max(info[,19]),15]
results$Score[i]<-max(info[,19])
}
}
}
}
for(i in seq_along(overview4[,1])){
for(j in 2:length(checkpoint[1,])){
if(!is.na(checkpoint[i,j])){
checkpoint[i,j]<-6
}
}
}
if(is.null(input$dbSNP)){
database_calls<-cbind(results[,c(1:5,8:(length(results[1,])))],
c.,c.complement,p.)
}
if(!is.null(input$dbSNP)){
database_calls<-cbind(results,c.,c.complement,p.)
}
write.table(database_calls,
paste(input$output_folder,
"/Results_Databases.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
write.table(checkpoint,
paste(input$output_folder,"/checkpoint.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
progress$close()
#7. Final Filtration
log_info<-c(log_info,"7. Perform Final Filtration<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "7. Perform final filtration", value = 0)
if(input$stricter_thresholds=="No"){
dp<-input$dp
nr_alt<-input$nr_alt
vaf<-input$vaf
low_bq<-input$bq
bq_diff<-input$bq_diff
}
if(input$stricter_thresholds=="Yes"){
dp<-input$dp2
nr_alt<-input$nr_alt2
vaf<-input$vaf2
low_bq<-input$bq2
bq_diff<-input$bq_diff2
}
nrsamples<-input$nr_samples
nrsamples_high<-ceiling(length(overview4[,1])/2)
if(nrsamples_high==1){
nrsamples_high<-2
}
if(input$predict=="SIFT"){
limit_provean<-input$damaging_safe1
limit_provean2<-input$tolerated_safe1
}
if(input$predict=="Provean"){
limit_provean<-input$damaging_safe2
limit_provean2<-input$tolerated_safe2
}
if(input$predict=="PolyPhen2"){
limit_provean<-input$damaging_safe3
limit_provean2<-input$tolerated_safe3
}
if(!is.null(input$primerPositions)){
primer_temp<-input$primerPositions
primer<-read.table(primer_temp$datapath,
header=FALSE,sep="\t",
stringsAsFactors=FALSE)
}
if(!is.null(input$hotspots)){
hotspots_temp<-input$hotspots
hotspots<-read.table(hotspots_temp$datapath,header=TRUE,
sep="\t",stringsAsFactors=FALSE)
}
results<-cbind(frequency_calls[,c(1:5,14:16,6,13)],
database_calls[,c((length(database_calls[1,])-2):length(database_calls[1,]))],
frequency_calls[,c(11,12)],
Nr_Ref=frequency_calls$Nr_Ref,
Nr_Alt=frequency_calls$Nr_Alt,
DP=frequency_calls$DP,
VAF=frequency_calls$VAF,
frequency_calls[,c(17:(length(frequency_calls[1,])-14))],
Called=rowSums(frequency_calls[,c(17:(length(frequency_calls[1,])-14))],na.rm=TRUE),
database_calls[,c(6:(length(database_calls[1,])-3))],
frequency_calls[,c((length(frequency_calls[1,])-9):(length(frequency_calls[1,])))])
artifact_because<-data.frame(nr_samples=rep(NA,length(frequency_calls[,1])),
nr_samples_similar=rep(NA,length(frequency_calls[,1])),
nr_databases=rep(NA,length(frequency_calls[,1])),
polymorphism_db=rep(NA,length(frequency_calls[,1])),
mutation_db=rep(NA,length(frequency_calls[,1])),
cosmic_nr=rep(NA,length(frequency_calls[,1])),
Poly_freq=rep(NA,length(frequency_calls[,1])))
#filter frequency
if(input$stricter_thresholds=="Yes"){
progress$inc(1/13,detail="-> Consider Frequency and Base Quality")
include1<-results$DP>=dp
include2<-results$Nr_Alt>=nr_alt
include3<-(results$VAF*100)>=vaf
include4<-results$BQ_ALT>=low_bq
include5<-(results$BQ_REF-results$BQ_ALT)<=bq_diff
temp<-results[rowSums(cbind(include1,include2,include3,include4,include5))>=5|is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
results<-temp
temp<-frequency_calls[rowSums(cbind(include1,include2,include3,include4,include5))>=5|is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
frequency_calls<-temp
temp<-database_calls[rowSums(cbind(include1,include2,include3,include4,include5))>=5|is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
database_calls<-temp
temp<-artifact_because[rowSums(cbind(include1,include2,include3,include4,include5))>=5|is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
artifact_because<-temp
}
if(input$stricter_thresholds=="No"){
progress$inc(1/13)
}
#nr of samples
progress$inc(1/13,
detail="-> Consider samples with the same call")
progress_small <- shiny::Progress$new()
progress_small$set(message = "", value = 0)
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
artifact_because[i,1]<-length(combined_calls[intersect(intersect(grep(results[i,2],combined_calls[,2]),grep(results[i,3],combined_calls[,3])),intersect(grep(results[i,4],combined_calls[,4]),grep(results[i,5],combined_calls[,5]))),1])
}
progress_small$close()
progress$inc(1/13,
detail="-> Consider samples with a call at the same position")
progress_small <- shiny::Progress$new()
progress_small$set(message = "", value = 0)
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
artifact_because[i,2]<-length(combined_calls[intersect(grep(results[i,2],combined_calls[,2]),grep(results[i,3],combined_calls[,3])),1])
}
progress_small$close()
progress$inc(1/13,detail="-> Consider background information")
background_info<-rep(0,length(results[,1]))
start<-0
ende<-0
neu<-TRUE
i<-1
while(i<=length(results[,1])){
if(neu==TRUE){
start<-ende<-i
}
i<-i+1
if(i<=length(results[,1])&&
as.character(results[i,2])==as.character(results[i-1,2])&&
results[i,3]==results[i-1,3]&&
results[i,4]==results[i-1,4]&&
results[i,5]==results[i-1,5]){
ende<-i
neu<-FALSE
}
if(i>length(results[,1])||
as.character(results[i,2])!=as.character(results[i-1,2])||
results[i,3]!=results[i-1,3]||
results[i,4]!=results[i-1,4]||
results[i,5]!=results[i-1,5]){
for(j in start:ende){
background_info[j]<-ende-start+1
neu<-TRUE
}
}
}
#databases
progress$inc(1/13,detail="-> Consider nr of databases")
if(length(database_calls[1,])>10){
if(length(grep("dbSNP",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$dbSNP[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],
1,na.rm=TRUE)
if(!is.na(results$dbSNP_MAF[i])&&
as.numeric(results$dbSNP_MAF[i])<=0.001){
artifact_because[i,5]<-sum(artifact_because[i,5],
1,na.rm=TRUE)
}
if(!is.na(results$dbSNP_MAF[i])&&
as.numeric(results$dbSNP_MAF[i])>0.001){
artifact_because[i,4]<-sum(artifact_because[i,4],
1,na.rm=TRUE)
}
}
}
}
if(length(grep("G1000_AF",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$G1000_AF[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],
1,na.rm=TRUE)
if(as.numeric(results$G1000_AF[i])<=0.001){
artifact_because[i,5]<-sum(artifact_because[i,5],
1,na.rm=TRUE)
}
if(as.numeric(results$G1000_AF[i])>0.001){
artifact_because[i,4]<-sum(artifact_because[i,4],
1,na.rm=TRUE)
}
}
}
}
if(length(grep("ExAC_AF",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$ExAC_AF[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],
1,na.rm=TRUE)
if(as.numeric(results$ExAC_AF[i])<=0.0005){
artifact_because[i,5]<-sum(artifact_because[i,5],
1,na.rm=TRUE)
}
if(as.numeric(results$ExAC_AF[i])>0.0005){
artifact_because[i,4]<-sum(artifact_because[i,4],
1,na.rm=TRUE)
}
}
}
}
if(length(grep("GAD_AF",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$GAD_AF[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],
1,na.rm=TRUE)
if(as.numeric(results$GAD_AF[i])<=0.001){
artifact_because[i,5]<-sum(artifact_because[i,5],
1,na.rm=TRUE)
}
if(as.numeric(results$GAD_AF[i])>0.001){
artifact_because[i,4]<-sum(artifact_because[i,4],
1,na.rm=TRUE)
}
}
}
}
if(length(grep("CosmicID",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$CosmicID[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],
1,na.rm=TRUE)
artifact_because[i,6]<-sum(as.numeric(strsplit(as.character(database_calls$Cosmic_Counts[i]),split=",")[[1]]))
if(artifact_because[i,6]>20){
artifact_because[i,5]<-sum(artifact_because[i,5],
1,na.rm=TRUE)
}
if(artifact_because[i,6]<=20){
artifact_because[i,4]<-sum(artifact_because[i,4],
1,na.rm=TRUE)
}
}
}
}
if(length(grep("ClinVar",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$ClinVar[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],
1,na.rm=TRUE)
if(length(grep("Pathogenic",results$ClinVar[i],
ignore.case = TRUE))>0){
artifact_because[i,5]<-sum(artifact_because[i,5],
1,na.rm=TRUE)
}
if(length(grep("Benign",results$ClinVar[i],
ignore.case=TRUE))>0){
artifact_because[i,4]<-sum(artifact_because[i,4],
1,na.rm=TRUE)
}
}
}
}
}
#tolerated and freq
progress$inc(1/13,detail="-> Consider VAF when tolerated")
for(i in seq_along(results[,1])){
if(!is.na(results$VAF[i])&&((results$VAF[i]>=0.35&&
results$VAF[i]<=0.65)||
(results$VAF[i]>=0.85))){
artifact_because[i,7]<-1
}
if(!is.na(results$VAF[i])&&(results$VAF[i]<0.35||
(results$VAF[i]>0.65&&
results$VAF[i]<0.85))){
artifact_because[i,7]<-0
}
}
#large number of samples and high VAF
progress$inc(1/13,
detail="-> Consider VAF when high nr of samples")
i<-1
while(i<=length(results[,1])){
subset<-results[i:(i+background_info[i]-1),]
if(length(subset[,1])>nrsamples&&
sum(!is.na(subset$VAF))==length(subset[,1])&&
sum(subset$VAF>0.85)>=floor(0.9*length(subset[,1]))){
artifact_because[i:(i+background_info[i]-1),7]<-2
}
i<-i+background_info[i]
}
#test for strand bias (8 von 15)
progress$inc(1/13,detail="-> Consider strand bias")
strandbias<-rep(NA,length(results[,1]))
for(i in seq_along(results[,1])){
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])){
test<-fisher.test(x=matrix(c(results$Nr_Ref_fwd[i],
results$Nr_Alt_fwd[i],
results$Nr_Ref_rev[i],
results$Nr_Alt_rev[i]),
ncol=2))
strandbias[i]<-test$p.value
}
if(!is.null(input$primerPositions)){
chr<-as.character(results[i,2])==as.character(primer[,1])
start<-results[i,3]>primer[,2]
end<-(as.numeric(results[i,3])+nchar(results[i,4])-1)<=primer[,3]
if(sum(rowSums(cbind(chr,start,end))==3)>0){
strandbias[i]<-2
}
}
}
#check for hotspots
progress$inc(1/13,detail="-> Consider hotspot list")
hotspot<-rep(NA,length(results[,1]))
progress_small <- shiny::Progress$new()
progress_small$set(message = "", value = 0)
if(!is.null(input$hotspots)){
for(i in seq_along(hotspots[,1])){
progress_small$inc(1/length(hotspots[,1]),
detail=paste("-> Hotspot",i,
"out of",
length(hotspots[,1])))
found1<-grep(hotspots[i,1],results$Gene)
if(length(found1)>0){
if(length(grep("fs",hotspots[i,2]))==0&&
length(grep("del",hotspots[i,2]))==0&&
length(grep("ins",hotspots[i,2]))==0){
#Just an SNV
found2<-grep(hotspots[i,2],results$p.,
fixed=TRUE)
flag<-NA
if(length(found2)>0){
flag<-rep(FALSE,length(results[,1]))
if(is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Ref[found2[j]])==1&&nchar(results$Alt[found2[j]])==1
}
}
if(!is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Ref[found2[j]])==1&&nchar(results$Alt[found2[j]])==1&&as.numeric(results$VAF[found2[j]])>=as.numeric(hotspots[i,3])
}
}
}
}
if(length(grep("fs",hotspots[i,2]))>0){
#frameshift
searchstring<-substr(hotspots[i,2],
2,(nchar(hotspots[i,2])-2))
found2<-grep(searchstring,results$p.)
flag<-NA
if(length(found2)>0){
flag<-rep(FALSE,length(results[,1]))
if(is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))!=0&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0
}
}
if(!is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))!=0&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0&&as.numeric(results$VAF[found2[j]])>=as.numeric(hotspots[i,3])
}
}
}
}
if(length(grep("del",hotspots[i,2]))>0){
#deletion
searchstring_temp<-substr(hotspots[i,2],2,
(nchar(hotspots[i,2])-3))
searchstring<-strsplit(searchstring_temp,split="_")[[1]][1]
found2<-grep(searchstring,results$p.)
flag<-NA
if(length(found2)>0){
flag<-rep(FALSE,length(results[,1]))
if(is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Ref[found2[j]])>1&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0
}
}
if(!is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Ref[found2[j]])>1&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0&&as.numeric(results$VAF[found2[j]])>=as.numeric(hotspots[i,3])
}
}
}
}
if(length(grep("ins",hotspots[i,2]))>0){
#deletion
searchstring_temp<-substr(hotspots[i,2],2,
(nchar(hotspots[i,2])-3))
searchstring<-strsplit(searchstring_temp,split="_")[[1]][1]
found2<-grep(searchstring,results$p.)
flag<-NA
if(length(found2)>0){
flag<-rep(FALSE,length(results[,1]))
if(is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Alt[found2[j]])>1&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0
}
}
if(!is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Alt[found2[j]])>1&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0&&as.numeric(results$VAF[found2[j]])>=as.numeric(hotspots[i,3])
}
}
}
}
if(length(intersect(found1,found2))>0){
for(j in intersect(found1,found2)){
if(flag[j]==TRUE){
hotspot[j]<-1
}
}
}
}
}
}
progress_small$close()
##final filtration
results<-cbind(results,strandbias,
artifact_because[,c(1:2)],Category=NA)
#artifact score
progress$inc(1/13,detail="-> Perform final filtration")
artifact_score<-rep(0,length(results[,1]))
progress_small <- shiny::Progress$new()
progress_small$set(message = "Calculate Artifact Score",
value = 0)
if(input$artifact_score=="No"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,"out of",
length(results[,1])))
if(results$nr_samples[i]>nrsamples){
artifact_score[i]<-artifact_score[i]+2
}
if(results$nr_samples[i]>nrsamples_high&&
is.na(hotspot[i])){
artifact_score[i]<-artifact_score[i]+2
}
if((nchar(results$Ref[i])>1||nchar(results$Alt[i])>1)&&
results$nr_samples_similar[i]>results$nr_samples[i]){
artifact_score[i]<-artifact_score[i]+1
}
if((nchar(results$Ref[i])>1||nchar(results$Alt[i])>1)&&
!is.na(results$VAF[i])&&results$VAF[i]<0.05){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(artifact_because[i,7])&&
artifact_because[i,7]==2){
artifact_score[i]<-artifact_score[i]+2
}
if(is.null(input$primerPositions)||
(!is.na(results$strandbias[i])&&
results$strandbias[i]!=2)){
if(!is.na(results$strandbias[i])&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(results$Nr_Alt_fwd[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_fwd[i]>=(nr_alt/2)&&
results$Nr_Alt_rev[i]>=(nr_alt/2))&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]-1
}
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
(results$Nr_Alt_fwd[i]<=2&&
results$Nr_Ref_fwd[i]>=(dp-nr_alt)/2)&&
results$strandbias[i]>=0.001){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
(results$Nr_Alt_fwd[i]<=2&&
results$Nr_Ref_fwd[i]<(dp-nr_alt)/2)&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]-1
}
if(!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_rev[i]<=2&&
results$Nr_Ref_rev[i]>=(dp-nr_alt)/2)&&
results$strandbias[i]>=0.001){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_rev[i]<=2&&
results$Nr_Ref_rev[i]<(dp-nr_alt)/2)&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]-1
}
}
if(!is.null(input$primerPositions)&&
!is.na(results$strandbias[i])&&
results$strandbias[i]==2){
artifact_score[i]<-artifact_score[i]-1
}
if(!is.na(results$VAF[i])&&results$VAF[i]<0.02){
artifact_score[i]<-artifact_score[i]+2
}
if(is.na(artifact_because[i,3])&&
!is.na(results$VAF[i])&&results$VAF[i]<0.10){
artifact_score[i]<-artifact_score[i]+1
}
if(is.na(artifact_because[i,3])&&
results$nr_samples[i]>nrsamples_high){
artifact_score[i]<-artifact_score[i]+1
}
if((!is.na(results$Score[i])&&
results$Score[i]<limit_provean)){
artifact_score[i]<-artifact_score[i]-1
}
if(!is.na(results$Score[i])&&
results$Score[i]>limit_provean2&&
!is.na(artifact_because[i,7])&&
artifact_because[i,7]==0){
artifact_score[i]<-artifact_score[i]+1
}
if(results$Called[i]>=4){
artifact_score[i]<-artifact_score[i]-1
}
if(results$Called[i]>=5){
artifact_score[i]<-artifact_score[i]-1
}
if(results$Called[i]>=6){
artifact_score[i]<-artifact_score[i]-1
}
if(results$Called[i]==1){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(results$BQ_ALT[i])&&
results$BQ_ALT[i]<(mean(results$BQ_ALT,na.rm=TRUE)-3*sd(results$BQ_ALT,na.rm=TRUE))){
artifact_score[i]<-artifact_score[i]+4
}
if(!is.na(hotspot[i])){
artifact_score[i]<-artifact_score[i]-3
}
if(!is.na(results$LoFreq[i])&&
!is.na(results$FreeBayes[i])&&
!is.na(results$VarDict[i])&&
results$LoFreq[i]==1&&results$FreeBayes[i]==1&&
results$VarDict[i]==1){
artifact_score[i]<-artifact_score[i]-3
}
if(artifact_score[i]>-1){
results$Category[i]<-paste("Artifact (",
artifact_score[i],")",
sep="")
}
if(artifact_score[i]<=-1&&is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],")",
sep="")
}
if(artifact_score[i]<=-1&&!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],")",
sep="")
}
}
}
if(input$artifact_score=="Yes"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,"out of",
length(results[,1])))
if(results$nr_samples[i]>nrsamples){
artifact_score[i]<-artifact_score[i]+input$detectedLow
}
if(results$nr_samples[i]>nrsamples_high&&
is.na(hotspot[i])){
artifact_score[i]<-artifact_score[i]+input$detectedHigh
}
if((nchar(results$Ref[i])>1||nchar(results$Alt[i])>1)&&
results$nr_samples_similar[i]>results$nr_samples[i]){
artifact_score[i]<-artifact_score[i]+input$isIndel
}
if((nchar(results$Ref[i])>1||nchar(results$Alt[i])>1)&&
!is.na(results$VAF[i])&&results$VAF[i]<0.05){
artifact_score[i]<-artifact_score[i]+input$isIndelVAF
}
if(!is.na(artifact_because[i,7])&&
artifact_because[i,7]==2){
artifact_score[i]<-artifact_score[i]+input$detectedLowVAF
}
if(is.null(input$primerPositions)||
(!is.na(results$strandbias[i])&&
results$strandbias[i]!=2)){
if(!is.na(results$strandbias[i])&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+input$noPrimerP
}
if(!is.na(results$Nr_Alt_fwd[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_fwd[i]>=(nr_alt/2)&&
results$Nr_Alt_rev[i]>=(nr_alt/2))&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+input$primerPAlt
}
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
(results$Nr_Alt_fwd[i]<=2&&
results$Nr_Ref_fwd[i]>=(dp-nr_alt)/2)&&
results$strandbias[i]>=0.001){
artifact_score[i]<-artifact_score[i]+input$noPrimerPFwd
}
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
(results$Nr_Alt_fwd[i]<=2&&
results$Nr_Ref_fwd[i]<(dp-nr_alt)/2)&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+input$primerPFwd
}
if(!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_rev[i]<=2&&
results$Nr_Ref_rev[i]>=(dp-nr_alt)/2)&&
results$strandbias[i]>=0.001){
artifact_score[i]<-artifact_score[i]+input$noPrimerPRev
}
if(!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_rev[i]<=2&&
results$Nr_Ref_rev[i]<(dp-nr_alt)/2)&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+input$primerPRev
}
}
if(!is.null(input$primerPositions)&&
!is.na(results$strandbias[i])&&
results$strandbias[i]==2){
artifact_score[i]<-artifact_score[i]+input$primerLocation
}
if(!is.na(results$VAF[i])&&results$VAF[i]<0.02){
artifact_score[i]<-artifact_score[i]+input$vafLow
}
if(is.na(artifact_because[i,3])&&
!is.na(results$VAF[i])&&results$VAF[i]<0.10){
artifact_score[i]<-artifact_score[i]+input$databaseVAF
}
if(is.na(artifact_because[i,3])&&
results$nr_samples[i]>nrsamples_high){
artifact_score[i]<-artifact_score[i]+input$databaseHigh
}
if((!is.na(results$Score[i])&&
results$Score[i]<limit_provean)){
artifact_score[i]<-artifact_score[i]+input$predictionSafe
}
if(!is.na(results$Score[i])&&
results$Score[i]>limit_provean2&&
!is.na(artifact_because[i,7])&&
artifact_because[i,7]==0){
artifact_score[i]<-artifact_score[i]+input$predictionVAF
}
if(results$Called[i]>=input$nrcaller4){
artifact_score[i]<-artifact_score[i]+input$reward4
}
if(results$Called[i]>=input$nrcaller5){
artifact_score[i]<-artifact_score[i]+input$reward5
}
if(results$Called[i]>=input$nrcaller6){
artifact_score[i]<-artifact_score[i]+input$reward6
}
if(results$Called[i]==1){
artifact_score[i]<-artifact_score[i]+input$oneCaller
}
if(!is.na(results$BQ_ALT[i])&&
results$BQ_ALT[i]<(mean(results$BQ_ALT,na.rm=TRUE)-3*sd(results$BQ_ALT,na.rm=TRUE))){
artifact_score[i]<-artifact_score[i]+input$BQ_AltMean
}
if(!is.na(hotspot[i])){
artifact_score[i]<-artifact_score[i]+input$knownHotspot
}
temp<-frequency_calls[i,17:(length(frequency_calls[1,])-14)]
temp<-temp[,!is.na(temp)]
if(length(intersect(names(temp),
input$overlapTools))==length(input$overlapTools)){
artifact_score[i]<-artifact_score[i]+input$overlapReward
}
if(artifact_score[i]>=input$artifactThreshold){
results$Category[i]<-paste("Artifact (",
artifact_score[i],")",
sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],")",
sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],")",
sep="")
}
}
}
progress_small$close()
#polymorphism score
progress$inc(1/13,detail="-> Perform final filtration")
poly_score<-rep(0,length(results[,1]))
cosmic_flag<-rep(FALSE,length(results[,1]))
progress_small <- shiny::Progress$new()
progress_small$set(message = "Calculate Polymorphism Score",
value = 0)
if(input$polymorphism_score=="No"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,"out of",
length(results[,1])))
if(!is.na(results$nr_samples[i])&&
results$nr_samples[i]>nrsamples){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(results$nr_samples[i])&&
results$nr_samples[i]==1){
poly_score[i]<-poly_score[i]-1
}
if(!is.na(artifact_because[i,4])&&
artifact_because[i,4]>=2){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(artifact_because[i,4])&&
artifact_because[i,4]>=4){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(artifact_because[i,5])&&
artifact_because[i,5]>=2){
poly_score[i]<-poly_score[i]-1
}
if(is.na(artifact_because[i,4])){
poly_score[i]<-poly_score[i]-1
}
if(results$Called[i]>=6){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(results$Consequence[i])&&
vcountPattern(pattern="frameshift",
as.character(results$Consequence[i]))>0&&
vcountPattern(pattern="*",
as.character(results$p.[i]),
fixed = TRUE)==0){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(artifact_because[i,7])&&
artifact_because[i,7]==1){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(results$Prediction[i])&&
(results$Prediction[i]=="Tolerated"||
results$Prediction[i]=="benign"||
results$Prediction[i]=="Neutral")&&
results$Score[i]>=limit_provean2){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(results$Score[i])&&!is.na(results$p.[i])&&
as.character(results$p.[i])!="NA"
&&(results$Score[i]<=limit_provean||
vcountPattern(pattern="*",
as.character(results$p.[i]),
fixed = TRUE)>0)){
poly_score[i]<-poly_score[i]-1
}
if(!is.na(results$Cosmic_Counts[i])&&
results$Cosmic_Counts[i]>100){
cosmic_flag[i]<-TRUE
}
if(is.na(hotspot[i])&&poly_score[i]>=2&&
cosmic_flag[i]==TRUE){
results$Category[i]<-paste(results$Category[i],
"Likely Polymorphism",
sep="")
}
if(is.na(hotspot[i])&&((poly_score[i]>=2&&
cosmic_flag[i]==FALSE)||
poly_score[i]>=3)){
results$Category[i]<-"Polymorphism"
}
}
}
if(input$polymorphism_score=="Yes"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,"out of",
length(results[,1])))
if(!is.na(results$nr_samples[i])&&
results$nr_samples[i]>nrsamples){
poly_score[i]<-poly_score[i]+input$polyDetected
}
if(!is.na(results$nr_samples[i])&&
results$nr_samples[i]==1){
poly_score[i]<-poly_score[i]+input$polyDetectedOnce
}
if(!is.na(artifact_because[i,4])&&
artifact_because[i,4]>=input$polyDatabasesPolyLow){
poly_score[i]<-poly_score[i]+input$polyDatabasesPolyLowReward
}
if(!is.na(artifact_because[i,4])&&
artifact_because[i,4]>=input$polyDatabasesPolyHigh){
poly_score[i]<-poly_score[i]+input$polyDatabasesPolyHighReward
}
if(!is.na(artifact_because[i,5])&&
artifact_because[i,5]>=input$polyDatabasesMut){
poly_score[i]<-poly_score[i]+input$polyDatabasesMutReward
}
if(is.na(artifact_because[i,4])){
poly_score[i]<-poly_score[i]+input$polyNoDatabase
}
if(results$Called[i]>=input$polyDatabases){
poly_score[i]<-poly_score[i]+input$polyDatabasesReward
}
if(!is.na(results$Consequence[i])&&
vcountPattern(pattern="frameshift",
as.character(results$Consequence[i]))>0
&&vcountPattern(pattern="*",
as.character(results$p.[i]),
fixed = TRUE)==0){
poly_score[i]<-poly_score[i]+input$polyEffect
}
if(!is.na(artifact_because[i,7])&&
artifact_because[i,7]==1){
poly_score[i]<-poly_score[i]+input$polyVAF
}
if(!is.na(results$Prediction[i])&&
(results$Prediction[i]=="Tolerated"||
results$Prediction[i]=="benign"||
results$Prediction[i]=="Neutral")&&
results$Score[i]>=limit_provean2){
poly_score[i]<-poly_score[i]+input$polyPrediction
}
if(!is.na(results$Score[i])&&!is.na(results$p.[i])&&
as.character(results$p.[i])!="NA"&&
(results$Score[i]<=limit_provean||
vcountPattern(pattern="*",
as.character(results$p.[i]),
fixed = TRUE)>0)){
poly_score[i]<-poly_score[i]+input$polyPredictionEffect
}
if(!is.na(results$Cosmic_Counts[i])&&
results$Cosmic_Counts[i]>input$polyCosmic){
cosmic_flag[i]<-TRUE
}
if(is.na(hotspot[i])&&
poly_score[i]>=input$polyThresholdCritical&&
cosmic_flag[i]==TRUE){
results$Category[i]<-paste(results$Category[i],
"Likely Polymorphism",
sep="")
}
if(is.na(hotspot[i])&&
((poly_score[i]>=input$polyThresholdCritical&&
cosmic_flag[i]==FALSE)||
poly_score[i]>=input$polyThreshold)){
results$Category[i]<-"Polymorphism"
}
}
}
progress_small$close()
#corrections
progress$inc(1/13,detail="-> Perform final filtration")
progress_small <- shiny::Progress$new()
progress_small$set(message = "Correct Scores", value = 0)
if(input$artifact_score=="No"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,"out of",
length(results[,1])))
if((poly_score[i]>=2&&cosmic_flag[i]==TRUE&&
is.na(hotspot[i]))||
(is.na(hotspot[i])&&((poly_score[i]>=2&&
cosmic_flag[i]==FALSE)||
poly_score[i]>=3))){
if(!is.na(results$VAF[i])&&results$VAF[i]<=0.1){
artifact_score[i]<-artifact_score[i]+5
if(artifact_score[i]>-1){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
if(!is.na(results$VAF[i])&&results$VAF[i]<=0.2){
artifact_score[i]<-artifact_score[i]+2
if(artifact_score[i]>-1){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
if(!is.na(results$Consequence[i])&&
vcountPattern(pattern="frameshift",
results$Consequence[i])>0){
artifact_score[i]<-artifact_score[i]+2
if(artifact_score[i]>-1){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
}
}
}
if(input$artifact_score=="Yes"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,"out of",
length(results[,1])))
if((poly_score[i]>=2&&cosmic_flag[i]==TRUE&&
is.na(hotspot[i]))||(is.na(hotspot[i])&&
((poly_score[i]>=2&&
cosmic_flag[i]==FALSE)||
poly_score[i]>=3))){
if(!is.na(results$VAF[i])&&results$VAF[i]<=0.1){
artifact_score[i]<-artifact_score[i]+input$PolymorphismVAF10
if(artifact_score[i]>=input$artifactThreshold){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
if(!is.na(results$VAF[i])&&results$VAF[i]<=0.2){
artifact_score[i]<-artifact_score[i]+input$PolymorphismVAF20
if(artifact_score[i]>=input$artifactThreshold){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
if(!is.na(results$Consequence[i])&&
vcountPattern(pattern="frameshift",
results$Consequence[i])>0){
artifact_score[i]<-artifact_score[i]+input$PolymorphismFrame
if(artifact_score[i]>=input$artifactThreshold){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
}
}
}
progress_small$close()
#identical calls as polymorphism
progress$inc(1/13,detail="-> Re-consider polymorphisms")
i<-1
while(i<=length(results[,1])){
subset<-results[i:(i+background_info[i]-1),]
if(sum(subset$Category=="Polymorphism",na.rm=TRUE)>=1){
for(j in i:(i+background_info[i]-1)){
if(!is.na(results$VAF[j])&&results$VAF[j]>0.2){
results$Category[j]<-"Polymorphism"
}
}
}
i<-i+background_info[i]
}
results.artifacts<-results[vcountPattern(results$Category,pattern="Artifact")>0 | is.na(results$VAF) | (results$DP-results$Nr_Ref)<nr_alt,]
results.polymorphisms<-results[vcountPattern(results$Category,pattern="Polymorphism")>0 & !is.na(results$VAF) & (results$DP-results$Nr_Ref)>=nr_alt,]
results.mutations<-results[(vcountPattern(results$Category,pattern="True")>0 | vcountPattern(results$Category,pattern="Hotspot")>0) & !is.na(results$VAF) & (results$DP-results$Nr_Ref)>=nr_alt,]
overview4<-cbind(overview4,Mutations=NA,Polymorphisms=NA,
Artifacts=NA)
for(i in seq_along(overview4[,1])){
overview4[i,4]<-length(results.mutations[results.mutations[,1]==overview4[i,1],1])
overview4[i,5]<-length(results.polymorphisms[results.polymorphisms[,1]==overview4[i,1],1])
overview4[i,6]<-length(results.artifacts[results.artifacts[,1]==overview4[i,1],1])
for(j in 2:length(checkpoint[1,])){
if(!is.na(checkpoint[i,j])){
checkpoint[i,j]<-7
}
}
}
write.table(results,paste(input$output_folder,
"/Results_Final.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
write.table(checkpoint,paste(input$output_folder,
"/checkpoint.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
output$table4 <- renderDataTable(datatable(overview4))
output$table_mutations <- renderDataTable(datatable(results.mutations))
output$table_polymorphisms <- renderDataTable(datatable(results.polymorphisms))
output$table_artifacts <- renderDataTable(datatable(results.artifacts))
results.workbook <- createWorkbook()
addWorksheet(wb=results.workbook,sheetName="Mutations")
addWorksheet(wb=results.workbook,sheetName="Polymorphisms")
addWorksheet(wb=results.workbook,sheetName="Artifacts")
writeData(wb=results.workbook,
x=results.mutations,sheet="Mutations")
writeData(wb=results.workbook,
x=results.polymorphisms,sheet="Polymorphisms")
writeData(wb=results.workbook,
x=results.artifacts,sheet="Artifacts")
saveWorkbook(results.workbook,
paste(input$output_folder,"/Results_Final.xlsx",
sep=""),
overwrite = TRUE)
progress$close()
})
observeEvent(input$appreci8Rcheckpoint,{
log_info<-c()
log_info[1]<-"Starting analysis with the appreci8R...<br><br>"
output$log_info<-renderUI({HTML(log_info)})
checkpoint_state<-input$checkpoint
checkpointFile<-read.table(paste(input$output_folder,
"/checkpoint.txt",sep=""),
stringsAsFactors = FALSE,header=TRUE,
sep="\t")
checkpoint<-checkpointFile
#1: After target filtration
if(checkpoint_state==1){
#1. Reading Input
log_info<-c(log_info,"0. Reading input<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "0. Reading input", value = 0)
target_calls<-list()
for(i in 1:(length(checkpointFile[1,])-1)){
progress$inc(1/(length(checkpointFile[1,])-1),
detail=paste("->",
as.character(names(checkpointFile[i+1]))))
target_calls[[i]]<-list()
for(j in seq_along(checkpointFile[,i+1])){
if(!is.na(checkpointFile[j,i+1])){
target_calls[[i]][[j]]<-read.table(paste(input$output_folder,
"/",
as.character(names(checkpointFile)[i+1]),
".",
checkpointFile[j,1],
".target.txt",sep=""),
stringsAsFactors = FALSE,
header=TRUE,
sep="\t")
}
}
}
progress$close()
#2. Normalization
log_info<-c(log_info,"2. Normalization<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "2. Normalization", value = 0)
normalized_calls<-list()
for(i in seq_along(target_calls)){
progress$inc(1/length(target_calls),
detail=paste("->",
as.character(names(checkpointFile[i+1]))))
normalized_calls[[i]]<-list()
if(length(target_calls[[i]])>0){
temp<-target_calls[[i]][[1]]
checkpoint[1,i+1]<-2
if(!is.na(temp[1,2])&&length(checkpointFile[,1])>1){
for(j in 2:length(checkpointFile[,1])){
temp<-rbind(temp,target_calls[[i]][[j]])
checkpoint[j,i+1]<-2
}
}
#GATK
if(i==1&&is.null(input$gatk_indels)){
log_info<-c(log_info,
"Please add GATK if you want to analyze its output<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==1){
if(input$gatk_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$gatk_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#Platypus
if(i==2&&is.null(input$platypus_indels)){
log_info<-c(log_info,
"Please add Platypus if you want to analyze its output<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==2){
if(input$platypus_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$platypus_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#VarScan
if(i==3&&is.null(input$varscan_indels)){
log_info<-c(log_info,
"Please add VarScan if you want to analyze its output<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==3){
if(input$varscan_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$varscan_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#FreeBayes
if(i==4&&is.null(input$freebayes_indels)){
log_info<-c(log_info,
"Please add FreeBayes if you want to analyze its output<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==4){
if(input$freebayes_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$freebayes_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
#LoFreq
if(i==5&&is.null(input$lofreq_indels)){
log_info<-c(log_info,
"Please add LoFreq if you want to analyze its output<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==5){
if(input$lofreq_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$lofreq_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
#SNVer
if(i==6&&is.null(input$snver_indels)){
log_info<-c(log_info,
"Please add SNVer if you want to analyze its output<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==6){
if(input$snver_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$snver_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
#SamTools
if(i==7&&is.null(input$samtools_indels)){
log_info<-c(log_info,
"Please add samtools if you want to analyze its output<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==7){
if(input$samtools_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$samtools_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
#VarDict
if(i==8&&is.null(input$vardict_indels)){
log_info<-c(log_info,
"Please add VarDict if you want to analyze its output<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==8){
if(input$vardict_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$vardict_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
if(length(target_calls)>8){
#Caller 1
if(i==9&&is.null(input$caller1_indels)){
log_info<-c(log_info,
paste("Please add ",
as.character(names(checkpointFile)[i+1]),
"if you want to analyze its output<br>"))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==9){
if(input$caller1_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller1_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
if(length(target_calls)>9){
#Caller 2
if(i==10&&is.null(input$caller2_indels)){
log_info<-c(log_info,
paste("Please add ",
as.character(names(checkpointFile)[i+1]),
"if you want to analyze its output<br>"))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==10){
if(input$caller2_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller2_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,
"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",
sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
if(length(target_calls)>10){
#Caller 3
if(i==11&&is.null(input$caller11_indels)){
log_info<-c(log_info,
paste("Please add ",
as.character(names(checkpointFile)[i+1]),
"if you want to analyze its output<br>"))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==11){
if(input$caller3_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller3_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,
"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",
sep=""),
row.names=FALSE,
quote=FALSE,
sep="\t")
}
if(length(target_calls)>11){
#Caller 4
if(i==12&&
is.null(input$caller12_indels)){
log_info<-c(log_info,
paste("Please add ",
as.character(names(checkpointFile)[i+1]),
"if you want to analyze its output<br>"))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==12){
if(input$caller4_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller4_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,
"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",
sep=""),
row.names=FALSE,
quote=FALSE,
sep="\t")
}
if(length(target_calls)>12){
#Caller 5
if(i==13&&is.null(input$caller13_indels)){
log_info<-c(log_info,
paste("Please add ",
as.character(names(checkpointFile)[i+1]),
"if you want to analyze its output<br>"))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==13){
if(input$caller5_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller5_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,
"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",
sep=""),
row.names=FALSE,
quote=FALSE,
sep="\t")
}
}
}
}
}
}
}
}
write.table(checkpoint,paste(input$output_folder,
"/checkpoint.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
checkpoint_state<-2
progress$close()
}
#2: After normalization
if(checkpoint_state==2){
if(exists("normalized_calls")==FALSE){
#1. Reading Input
log_info<-c(log_info,"0. Reading input<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "0. Reading input", value = 0)
normalized_calls<-list()
for(i in 1:(length(checkpointFile[1,])-1)){
progress$inc(1/(length(checkpointFile[1,])-1),
detail=paste("->",
as.character(names(checkpointFile[i+1]))))
normalized_calls[[i]]<-list()
if(!is.na(checkpointFile[1,i+1])){
normalized_calls[[i]]<-read.table(paste(input$output_folder,
"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",
sep=""),
stringsAsFactors = FALSE,
header=TRUE,
sep="\t")
}
}
progress$close()
}
#3. Annotate
log_info<-c(log_info,"3. Annotate<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "3. Annotate", value = 0)
annotated_calls<-list()
overview3<-checkpointFile
overview3[c(seq_along(checkpointFile[,1])),c(2:length(checkpointFile[1,]))]<-NA
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
connection_txid_symbol<-transcripts(Homo.sapiens,
columns=c("TXID",
"SYMBOL"))
for(i in seq_along(normalized_calls)){
progress$inc(1/length(normalized_calls))
annotated_calls[[i]]<-data.frame()
if(length(normalized_calls[[i]])>0){
progress_small <- shiny::Progress$new()
progress_small$set(message = as.character(names(checkpointFile[i+1])),
value = 0)
test<-VCF(rowRanges=GRanges(seqnames=paste("chr",
as.character(normalized_calls[[i]][,2]),
sep=""),
ranges=IRanges(as.numeric(normalized_calls[[i]][,3]),
(as.numeric(normalized_calls[[i]][,3])+nchar(normalized_calls[[i]][,4])-1))),
fixed=DataFrame(REF=DNAStringSet(normalized_calls[[i]][,4]),
ALT=DNAStringSetList(strsplit(normalized_calls[[i]][,5],",",fixed=TRUE)),
QUAL=1,
FILTER=as.character(normalized_calls[[i]][,1])))
if(is.null(input$locations)){
log_info<-c(log_info,"Please pick at least one location<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$locations)){
located<-locateVariants(test,txdb,AllVariants())
for(j in seq_along(input$locations)){
if(j==1){
of_interest<-data.frame(located$LOCATION==input$locations[j])
}
if(j>1){
of_interest<-data.frame(of_interest,
located$LOCATION==input$locations[j])
}
}
if(length(input$locations)==1){
located<-located[of_interest[,1]>0,]
}
if(length(input$locations)>1){
located<-located[rowSums(of_interest)>0,]
}
}
if(sum(input$locations=="coding")>0&&
is.null(input$consequences)){
log_info<-c(log_info,"Please pick at least one consequence<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$consequences)){
predicted<-predictCoding(query=test,
subject=txdb,
seqSource=Hsapiens)
for(j in seq_along(predicted[,1])){
if(as.character(predicted$REFCODON[j])=="CTG"){
if(as.character(predicted$VARCODON[j])=="ATG"){
predicted$CONSEQUENCE[j]<-"nonsynonymous"
}
if(as.character(predicted$VARCODON[j])=="CTA"||
as.character(predicted$VARCODON[j])=="CTC"||
as.character(predicted$VARCODON[j])=="CTT"||
as.character(predicted$VARCODON[j])=="TTA"||
as.character(predicted$VARCODON[j])=="TTG"){
predicted$CONSEQUENCE[j]<-"synonymous"
}
}
if(as.character(predicted$VARCODON[j])=="CTG"){
if(as.character(predicted$REFCODON[j])=="ATG"){
predicted$CONSEQUENCE[j]<-"nonsynonymous"
}
if(as.character(predicted$REFCODON[j])=="CTA"||
as.character(predicted$REFCODON[j])=="CTC"||
as.character(predicted$REFCODON[j])=="CTT"||
as.character(predicted$REFCODON[j])=="TTA"||
as.character(predicted$REFCODON[j])=="TTG"){
predicted$CONSEQUENCE[j]<-"synonymous"
}
}
if(as.character(predicted$REFCODON[j])=="TTG"){
if(as.character(predicted$VARCODON[j])=="ATG"){
predicted$CONSEQUENCE[j]<-"nonsynonymous"
}
if(as.character(predicted$VARCODON[j])=="CTA"||
as.character(predicted$VARCODON[j])=="CTC"||
as.character(predicted$VARCODON[j])=="CTT"||
as.character(predicted$VARCODON[j])=="TTA"||
as.character(predicted$VARCODON[j])=="CTG"){
predicted$CONSEQUENCE[j]<-"synonymous"
}
}
if(as.character(predicted$VARCODON[j])=="TTG"){
if(as.character(predicted$REFCODON[j])=="ATG"){
predicted$CONSEQUENCE[j]<-"nonsynonymous"
}
if(as.character(predicted$REFCODON[j])=="CTA"||
as.character(predicted$REFCODON[j])=="CTC"||
as.character(predicted$REFCODON[j])=="CTT"||
as.character(predicted$REFCODON[j])=="TTA"||
as.character(predicted$REFCODON[j])=="CTG"){
predicted$CONSEQUENCE[j]<-"synonymous"
}
}
}
for(j in seq_along(input$consequences)){
if(j==1){
of_interest<-data.frame(predicted$CONSEQUENCE==input$consequences[j])
}
if(j>1){
of_interest<-data.frame(of_interest,
predicted$CONSEQUENCE==input$consequences[j])
}
}
if(length(input$consequences)==1){
predicted<-predicted[of_interest[,1]>0,]
}
if(length(input$consequences)>1){
predicted<-predicted[rowSums(of_interest)>0,]
}
}
annotated_calls[[i]]<-data.frame(normalized_calls[[i]],
Location=NA,c.=NA,
p.=NA,AA_ref=NA,
AA_alt=NA,
Codon_ref=NA,
Codon_alt=NA,
Consequence=NA,
Gene=NA,GeneID=NA,
TranscriptID=NA)
counter_located<-1
counter_predicted<-1
keep<-rep(TRUE,length(annotated_calls[[i]][,1]))
for(k in seq_along(annotated_calls[[i]][,1])){
progress_small$inc(1/length(annotated_calls[[i]][,1]),
detail=paste("-> Call",k,
"out of",
length(annotated_calls[[i]][,1])))
while(counter_located<=length(ranges(located))&&
start(ranges(located))[counter_located]==annotated_calls[[i]][k,3]){
if(!is.na(annotated_calls[[i]][k,6])){
annotated_calls[[i]][k,6]<-paste(annotated_calls[[i]][k,6],
as.character(located$LOCATION[counter_located]),
sep=",")
annotated_calls[[i]][k,7]<-paste(annotated_calls[[i]][k,7],
as.character(located$LOCSTART[counter_located]),
sep=",")
}
if(is.na(annotated_calls[[i]][k,6])){
annotated_calls[[i]][k,6]<-as.character(located$LOCATION[counter_located])
annotated_calls[[i]][k,7]<-as.character(located$LOCSTART[counter_located])
}
counter_located<-counter_located+1
}
if(!is.na(annotated_calls[[i]][k,6])&&
!is.null(input$consequences)){
for(j in seq_along(strsplit(annotated_calls[[i]][k,6],",")[[1]])){
if(counter_predicted>length(ranges(predicted))||
strsplit(annotated_calls[[i]][k,6],",")[[1]][j]!="coding"){
if(!is.na(annotated_calls[[i]][k,8])){
annotated_calls[[i]][k,8]<-paste(annotated_calls[[i]][k,8],"NA",sep=",")
annotated_calls[[i]][k,9]<-paste(annotated_calls[[i]][k,9],"NA",sep=",")
annotated_calls[[i]][k,10]<-paste(annotated_calls[[i]][k,10],"NA",sep=",")
annotated_calls[[i]][k,11]<-paste(annotated_calls[[i]][k,11],"NA",sep=",")
annotated_calls[[i]][k,12]<-paste(annotated_calls[[i]][k,12],"NA",sep=",")
annotated_calls[[i]][k,13]<-paste(annotated_calls[[i]][k,13],"NA",sep=",")
annotated_calls[[i]][k,14]<-paste(annotated_calls[[i]][k,14],"NA",sep=",")
annotated_calls[[i]][k,15]<-paste(annotated_calls[[i]][k,15],"NA",sep=",")
annotated_calls[[i]][k,16]<-paste(annotated_calls[[i]][k,16],"NA",sep=",")
}
if(is.na(annotated_calls[[i]][k,8])){
annotated_calls[[i]][k,8]<-annotated_calls[[i]][k,9]<-"NA"
annotated_calls[[i]][k,10]<-annotated_calls[[i]][k,11]<-"NA"
annotated_calls[[i]][k,12]<-annotated_calls[[i]][k,13]<-"NA"
annotated_calls[[i]][k,14]<-"NA"
annotated_calls[[i]][k,15]<-annotated_calls[[i]][k,16]<-"NA"
}
}
if(counter_predicted<=length(ranges(predicted))&&
strsplit(annotated_calls[[i]][k,6],",")[[1]][j]=="coding"){
if(start(ranges(predicted))[counter_predicted]==annotated_calls[[i]][k,3]){
if(!is.na(annotated_calls[[i]][k,8])){
annotated_calls[[i]][k,8]<-paste(annotated_calls[[i]][k,8],
as.character(predicted$PROTEINLOC[counter_predicted][[1]][1]),sep=",")
if(as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])!="frameshift"){
if(as.character(predicted$REFCODON[counter_predicted])!="CTG"){
annotated_calls[[i]][k,9]<-paste(annotated_calls[[i]][k,9],
as.character(predicted$REFAA[counter_predicted][[1]][1]),sep=",")
}
if(as.character(predicted$REFCODON[counter_predicted])=="CTG"){
annotated_calls[[i]][k,9]<-paste(annotated_calls[[i]][k,9],
"L",sep=",")
}
if(as.character(predicted$VARCODON[counter_predicted])!="CTG"){
annotated_calls[[i]][k,10]<-paste(annotated_calls[[i]][k,10],
as.character(predicted$VARAA[counter_predicted][[1]][1]),sep=",")
}
if(as.character(predicted$VARCODON[counter_predicted])=="CTG"){
annotated_calls[[i]][k,10]<-paste(annotated_calls[[i]][k,10],"
L",sep=",")
}
}
if(as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])=="frameshift"){
annotated_calls[[i]][k,9]<-paste(annotated_calls[[i]][k,9],"NA",sep=",")
annotated_calls[[i]][k,10]<-paste(annotated_calls[[i]][k,10],"NA",sep=",")
}
annotated_calls[[i]][k,11]<-paste(annotated_calls[[i]][k,11],
as.character(predicted$REFCODON[counter_predicted]),sep=",")
annotated_calls[[i]][k,12]<-paste(annotated_calls[[i]][k,12],
as.character(predicted$VARCODON[counter_predicted]),sep=",")
annotated_calls[[i]][k,13]<-paste(annotated_calls[[i]][k,13],
as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1]),sep=",")
annotated_calls[[i]][k,14]<-paste(annotated_calls[[i]][k,14],
as.character(connection_txid_symbol[as.numeric(predicted$TXID[counter_predicted][[1]][1]),]$SYMBOL),sep=",")
annotated_calls[[i]][k,15]<-paste(annotated_calls[[i]][k,15],
as.character(predicted$GENEID[counter_predicted][[1]][1]),sep=",")
annotated_calls[[i]][k,16]<-paste(annotated_calls[[i]][k,16],
as.character(predicted$TXID[counter_predicted][[1]][1]),sep=",")
}
if(is.na(annotated_calls[[i]][k,8])){
annotated_calls[[i]][k,8]<-as.character(predicted$PROTEINLOC[counter_predicted][[1]][1])
if(as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])!="frameshift"){
if(as.character(predicted$REFCODON[counter_predicted])!="CTG"){
annotated_calls[[i]][k,9]<-as.character(predicted$REFAA[counter_predicted][[1]][1])
}
if(as.character(predicted$REFCODON[counter_predicted])=="CTG"){
annotated_calls[[i]][k,9]<-"L"
}
if(as.character(predicted$VARCODON[counter_predicted])!="CTG"){
annotated_calls[[i]][k,10]<-as.character(predicted$VARAA[counter_predicted][[1]][1])
}
if(as.character(predicted$VARCODON[counter_predicted])=="CTG"){
annotated_calls[[i]][k,10]<-"L"
}
}
if(as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])=="frameshift"){
annotated_calls[[i]][k,9]<-"NA"
annotated_calls[[i]][k,10]<-"NA"
}
annotated_calls[[i]][k,11]<-as.character(predicted$REFCODON[counter_predicted])
annotated_calls[[i]][k,12]<-as.character(predicted$VARCODON[counter_predicted])
annotated_calls[[i]][k,13]<-as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])
annotated_calls[[i]][k,14]<-as.character(connection_txid_symbol[as.numeric(predicted$TXID[counter_predicted][[1]][1]),]$SYMBOL)
annotated_calls[[i]][k,15]<-as.character(predicted$GENEID[counter_predicted][[1]][1])
annotated_calls[[i]][k,16]<-as.character(predicted$TXID[counter_predicted][[1]][1])
}
counter_predicted<-counter_predicted+1
}
}
}
}
if(is.na(annotated_calls[[i]][k,6])){
keep[k]<-FALSE
}
if(!is.null(input$consequences)&&
!is.na(annotated_calls[[i]][k,6])&&
sum(strsplit(annotated_calls[[i]][k,6],",")[[1]]=="coding")>0&&
(is.na(annotated_calls[[i]][k,8])||
sum(strsplit(annotated_calls[[i]][k,8],",")[[1]]=="NA")==length(strsplit(annotated_calls[[i]][k,8],",")[[1]]))){
keep[k]<-FALSE
}
}
annotated_calls[[i]]<-annotated_calls[[i]][keep,]
for(k in seq_along(overview3[,1])){
overview3[k,i+1]<-length(annotated_calls[[i]][annotated_calls[[i]][,1]==overview3[k,1],1])
checkpoint[k,i+1]<-3
}
write.table(annotated_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".annotated.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
progress_small$close()
}
}
write.table(checkpoint,
paste(input$output_folder,"/checkpoint.txt",
sep=""),row.names=FALSE,quote=FALSE,
sep="\t")
output$table3 <- renderDataTable(datatable(overview3))
checkpoint_state<-3
progress$close()
}
#3: After annotation
if(checkpoint_state==3){
if(exists("annotated_calls")==FALSE){
#1. Reading Input
log_info<-c(log_info,"0. Reading input<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "0. Reading input", value = 0)
annotated_calls<-list()
for(i in 1:(length(checkpointFile[1,])-1)){
progress$inc(1/(length(checkpointFile[1,])-1),
detail=paste("->",
as.character(names(checkpointFile[i+1]))))
annotated_calls[[i]]<-data.frame()
if(!is.na(checkpointFile[1,i+1])){
annotated_calls[[i]]<-read.table(paste(input$output_folder,
"/",
as.character(names(checkpointFile)[i+1]),
".annotated.txt",
sep=""),
stringsAsFactors=FALSE,
header=TRUE,
sep="\t")
}
}
progress$close()
}
#4. Combine
log_info<-c(log_info,"4. Combine Output<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "4. Combine Output", value = 0)
combined_calls<-data.frame(SampleID=NA,Chr=NA,Pos=NA,
Ref=NA,Alt=NA,Location=NA,
c.=NA,p.=NA,AA_ref=NA,AA_alt=NA,
Codon_ref=NA,Codon_alt=NA,
Consequence=NA,Gene=NA,GeneID=NA,
TranscriptID=NA,GATK=NA,
Platypus=NA,VarScan=NA,
FreeBayes=NA,LoFreq=NA,SNVer=NA,
SamTools=NA,VarDict=NA)
if(length(annotated_calls)>8){
combined_calls<-cbind(combined_calls,Caller1=NA)
if(length(annotated_calls)>9){
combined_calls<-cbind(combined_calls,Caller2=NA)
if(length(annotated_calls)>10){
combined_calls<-cbind(combined_calls,Caller3=NA)
if(length(annotated_calls)>11){
combined_calls<-cbind(combined_calls,
Caller4=NA)
if(length(annotated_calls)>12){
combined_calls<-cbind(combined_calls,
Caller5=NA)
}
}
}
}
}
combined_calls_temp<-combined_calls
overview4<-cbind(checkpointFile[,1],RawCalls=NA)
for(i in seq_along(annotated_calls)){
if(length(annotated_calls[[i]])>0){
temp<-annotated_calls[[i]]
add_to_temp<-matrix(rep(NA,
(length(combined_calls[1,])-16)),
ncol=(length(combined_calls[1,])-16))
temp<-cbind(temp,add_to_temp)
names(temp)<-names(combined_calls)
temp[,16+i]<-1
combined_calls_temp<-rbind(combined_calls_temp,temp)
}
}
combined_calls_temp<-combined_calls_temp[2:length(combined_calls_temp[,1]),]
combined_calls_temp_sorted<-combined_calls_temp[order(combined_calls_temp[,2],
combined_calls_temp[,3],
combined_calls_temp[,4],
combined_calls_temp[,5],
combined_calls_temp[,1]),]
combined_calls<-combined_calls_temp_sorted[1,]
counter<-1
for(i in 2:length(combined_calls_temp_sorted[,1])){
progress$inc(1/length(combined_calls_temp_sorted[,1]))
if(combined_calls[counter,1]==combined_calls_temp_sorted[i,1]&&
combined_calls[counter,2]==combined_calls_temp_sorted[i,2]&&
combined_calls[counter,3]==combined_calls_temp_sorted[i,3]&&
combined_calls[counter,4]==combined_calls_temp_sorted[i,4]&&
combined_calls[counter,5]==combined_calls_temp_sorted[i,5]){
for(j in 17:length(combined_calls[1,])){
if(!is.na(combined_calls[counter,j])||
!is.na(combined_calls_temp_sorted[i,j])){
combined_calls[counter,j]<-1
}
}
}
if(combined_calls[counter,1]!=combined_calls_temp_sorted[i,1]||
combined_calls[counter,2]!=combined_calls_temp_sorted[i,2]||
combined_calls[counter,3]!=combined_calls_temp_sorted[i,3]||
combined_calls[counter,4]!=combined_calls_temp_sorted[i,4]||
combined_calls[counter,5]!=combined_calls_temp_sorted[i,5]){
counter<-counter+1
combined_calls<-rbind(combined_calls,
combined_calls_temp_sorted[i,])
}
}
temp<-unique(combined_calls)
combined_calls<-temp
for(i in seq_along(overview4[,1])){
overview4[i,2]<-length(combined_calls[combined_calls[,1]==overview4[i,1],1])
for(j in seq_along(annotated_calls)){
if(length(annotated_calls[[j]])>0){
checkpoint[i,j+1]<-4
}
}
}
write.table(combined_calls,
paste(input$output_folder,"/Results_Raw.txt",
sep=""),row.names=FALSE,quote=FALSE,
sep="\t")
write.table(checkpoint,
paste(input$output_folder,"/checkpoint.txt",
sep=""),row.names=FALSE,quote=FALSE,
sep="\t")
output$table4 <- renderDataTable(datatable(overview4))
checkpoint_state<-4
progress$close()
}
#4: After combination
if(checkpoint_state==4){
if(exists("combined_calls")==FALSE){
#1. Reading Input
log_info<-c(log_info,"0. Reading input<br>")
output$log_info<-renderUI({HTML(log_info)})
combined_calls<-read.table(paste(input$output_folder,
"/Results_Raw.txt",
sep=""),
stringsAsFactors = FALSE,
header=TRUE,sep="\t")
}
#5. Pileup
log_info<-c(log_info,"5. Evaluate Coverage and BQ<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "5. Evaluate Coverage and BQ",
value = 0)
results<-cbind(combined_calls[,c(1:5)],Nr_Ref=NA,Nr_Alt=NA,
DP=NA,VAF=NA,BQ_REF=NA,BQ_ALT=NA,
Nr_Ref_fwd=NA,Nr_Alt_fwd=NA,DP_fwd=NA,
VAF_fwd=NA,Nr_Ref_rev=NA,Nr_Alt_rev=NA,
DP_rev=NA,VAF_rev=NA)
folder<-input$bam_folder
for(i in seq_along(results[,1])){
progress$inc(1/length(results[,1]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
done<-FALSE
#SNVs
if(nchar(results[i,4])==1&&nchar(results[i,5])==1){
results_temp<-getCharacteristicsFreq(results[i,2],
results[i,3],
results[i,3],
results[i,4],
results[i,5],
folder,
results[i,1])
results[i,6:19]<-results_temp[1,6:19]
if(results[i,8]>=input$dp&&
results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
results[i,3],
results[i,3],
results[i,4],
results[i,5],
folder,
results[i,1])
results[i,10:11]<-results_temp[1,6:7]
}
done<-TRUE
}
#Deletions
if(done==FALSE&&nchar(results[i,4])>1&&
nchar(results[i,5])==1
&&substr(results[i,4],1,1)==results[i,5]){
if(nchar(results[i,4])==2){
results_temp<-getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+1,
as.numeric(results[i,3])+1,
substr(results[i,4],2,2),
"-",folder,
results[i,1])
results[i,6:19]<-results_temp[1,6:19]
if(results[i,8]>=input$dp&&
results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+1,
as.numeric(results[i,3])+1,
substr(results[i,4],2,2),
"-",
folder,
results[i,1])
results[i,10:11]<-results_temp[1,6:7]
}
}
if(nchar(results[i,4])>2){
results_temp<-getCharacteristicsFreq(results[i,2],as.numeric(results[i,3])+1,
as.numeric(results[i,3])+1,
substr(results[i,4],2,2),"-",folder,results[i,1])
for(j in 3:nchar(results[i,4])){
results_temp<-rbind(results_temp,
getCharacteristicsFreq(results[i,2],as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),"-",folder,results[i,1]))
}
for(j in 6:19){
results[i,j]<-min(results_temp[,j])
}
if(results[i,8]>=input$dp&&results[i,7]>=input$nr_alt&&(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],as.numeric(results[i,3])+1,
as.numeric(results[i,3])+1,
substr(results[i,4],2,2),"-",folder,results[i,1])
for(j in 3:nchar(results[i,4])){
results_temp<-rbind(results_temp,
getCharacteristicsBQ(results[i,2],as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),"-",folder,results[i,1]))
}
for(j in 6:7){
results_temp[1,j]<-min(results_temp[,j])
}
results[i,10:11]<-results_temp[1,6:7]
}
}
done<-TRUE
}
#Insertions (summed up as +)
if(done==FALSE&&nchar(results[i,4])==1&&nchar(results[i,5])>1
&&substr(results[i,5],1,1)==results[i,4]){
results_temp<-getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3]),
as.numeric(results[i,3]),
results[i,4],
"+",folder,
results[i,1])
results[i,6:19]<-results_temp[1,6:19]
if(results[i,8]>=input$dp&&
results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3]),
as.numeric(results[i,3]),
results[i,4],
"+",folder,
results[i,1])
results[i,10:11]<-results_temp[1,6:7]
}
done<-TRUE
}
#Complex Indels
if(done==FALSE){
results_temp<-getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3]),
as.numeric(results[i,3]),
substr(results[i,4],1,1),
substr(results[i,5],1,1),
folder,results[i,1])
for(j in 2:min(nchar(results[i,4]),nchar(results[i,5]))){
results_temp<-rbind(results_temp,
getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
substr(results[i,5],j,j),
folder,results[i,1]))
}
#Del in the end
if(nchar(results[i,4])>nchar(results[i,5])){
results_temp<-rbind(results_temp,
getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+j,
as.numeric(results[i,3])+j,
substr(results[i,4],j+1,j+1),
"-",
folder,results[i,1]))
}
#Ins in the end
if(nchar(results[i,4])>nchar(results[i,5])){
results_temp<-rbind(results_temp,
getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
"+",
folder,results[i,1]))
}
for(j in 6:19){
results[i,j]<-min(results_temp[,j])
}
if(results[i,8]>=input$dp&&
results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3]),
as.numeric(results[i,3]),
substr(results[i,4],1,1),
substr(results[i,5],1,1),
folder,
results[i,1])
for(j in 2:min(nchar(results[i,4]),nchar(results[i,5]))){
results_temp<-rbind(results_temp,
getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
substr(results[i,5],j,j),
folder,results[i,1]))
}
#Del in the end
if(nchar(results[i,4])>nchar(results[i,5])){
results_temp<-rbind(results_temp,
getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+j,
as.numeric(results[i,3])+j,
substr(results[i,4],j+1,j+1),
"-",
folder,results[i,1]))
}
#Ins in the end
if(nchar(results[i,4])>nchar(results[i,5])){
results_temp<-rbind(results_temp,
getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
"+",
folder,results[i,1]))
}
for(j in 6:7){
results_temp[1,j]<-min(results_temp[,j])
}
results[i,10:11]<-results_temp[1,6:7]
}
}
}
frequency_calls_temp<-cbind(combined_calls,
results[,c(6:19)])
include1<-results[,8]>=input$dp
include2<-results[,7]>=input$nr_alt
include3<-(results[,9]*100)>=input$vaf
include4<-results[,11]>=input$bq
for(i in seq_along(results[,1])){
if(is.na(results[i,10])){
results[i,10]<-0
}
}
include5<-(results[,10]-results[,11])<=input$bq_diff
frequency_calls<-frequency_calls_temp[rowSums(cbind(include1,include2,include3,include4,include5))>=5&!is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
if(exists("overview4")==TRUE){
overview4<-cbind(overview4,VAFandBQFiltered=NA)
}
if(exists("overview4")==FALSE){
overview4<-cbind(checkpointFile[,1],RawCalls=NA,
VAFandBQFiltered=NA)
}
for(i in seq_along(overview4[,1])){
overview4[i,3]<-length(frequency_calls[frequency_calls[,1]==overview4[i,1],1])
for(j in 2:length(checkpoint[1,])){
if(!is.na(checkpoint[i,j])){
checkpoint[i,j]<-5
}
}
}
write.table(frequency_calls,
paste(input$output_folder,
"/Results_Frequency.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
write.table(checkpoint,
paste(input$output_folder,"/checkpoint.txt",
sep=""),row.names=FALSE,quote=FALSE,
sep="\t")
output$table4 <- renderDataTable(datatable(overview4))
checkpoint_state<-5
progress$close()
}
#5: After coverage and BQ filtration
if(checkpoint_state==5){
if(exists("frequency_calls")==FALSE){
#1. Reading Input
log_info<-c(log_info,"0. Reading input<br>")
output$log_info<-renderUI({HTML(log_info)})
frequency_calls<-read.table(paste(input$output_folder,
"/Results_Frequency.txt",
sep=""),
stringsAsFactors = FALSE,
header=TRUE,sep="\t")
}
#6. Extended Characteristics
log_info<-c(log_info,
"6. Determine Extended Set of Characteristics<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "6. Determine Extended Set of Characteristics (databases)",
value = 0)
progress$inc(0,detail="-> Downloading databases ")
results<-data.frame(frequency_calls[,c(1:5)])
results<-cbind(results,dbSNP=NA,dbSNP_MAF=NA)
snps<-SNPlocs.Hsapiens.dbSNP144.GRCh37
indels<-XtraSNPlocs.Hsapiens.dbSNP144.GRCh37
if(!is.null(input$`1kgenomes`)){
results<-cbind(results,G1000_AF=NA)
g1000<-MafDb.1Kgenomes.phase3.hs37d5
}
if(!is.null(input$exac)){
results<-cbind(results,ExAC_AF=NA)
exac<-MafDb.ExAC.r1.0.hs37d5
}
if(!is.null(input$gad)){
results<-cbind(results,GAD_AF=NA)
gad<-MafDb.gnomADex.r2.1.hs37d5
}
if(!is.null(input$cosmic)){
results<-cbind(results,CosmicID=NA,Cosmic_Counts=NA)
cosmic_67<-c()
data(cosmic_67,envir=environment(),package="COSMIC.67")
}
if(!is.null(input$clinvar)){
results<-cbind(results,ClinVar=NA)
clinvar<-data.frame(Gene=NA,Start=NA,Stop=NA,Ref=NA,
Alt=NA,Sig=NA)
genes_temp<-c()
for(i in seq_along(frequency_calls[,1])){
genes_temp<-c(genes_temp,
strsplit(frequency_calls[i,14],
split=",")[[1]])
}
genes<-unique(genes_temp[genes_temp!="NA"])
for(i in seq_along(genes)){
res<-entrez_search("clinvar",term=genes[i])
cv<-entrez_summary("clinvar",id=res$ids)
info<-extract_from_esummary(cv,
"variation_set",
simplify=FALSE)
significance<-extract_from_esummary(cv,
"clinical_significance",
simplify=FALSE)
for(j in seq_along(res$ids)){
info2<-info[res$ids[j]][[1]][[1]]
significance2<-significance[res$ids[j]][[1]][[1]]
if(length(info2$variation_loc[[1]])){
for(k in seq_along(info2$variation_loc[[1]][,1])){
if(info2$variation_loc[[1]][k,2]=="GRCh37"){
temp<-data.frame(Gene=NA,Start=NA,
Stop=NA,Ref=NA,Alt=NA)
temp[1,1]<-genes[i]
temp[1,2]<-info2$variation_loc[[1]][k,5]
temp[1,3]<-info2$variation_loc[[1]][k,6]
temp[1,4]<-info2$variation_loc[[1]][k,15]
temp[1,5]<-info2$variation_loc[[1]][k,16]
temp[1,6]<-significance2$description
if(!is.na(clinvar[1,1])){
clinvar<-rbind(clinvar,temp)
}
if(is.na(clinvar[1,1])){
clinvar<-temp
}
}
}
}
}
}
}
c.<-c()
c.complement<-c()
p.<-c()
for(i in seq_along(frequency_calls[,1])){
progress$inc(0,detail="-> Pre-processing of the calls ")
for(j in 1:(length(strsplit(frequency_calls[i,7],
split=",")[[1]]))){
if(j==1){
c.[i]<-paste("c.",
strsplit(frequency_calls[i,7],
split=",")[[1]][j],
frequency_calls[i,4],">",
frequency_calls[i,5],sep="")
c.complement[i]<-paste("c.",
strsplit(frequency_calls[i,7],
split=",")[[1]][j],
as.character(complement(DNAString(frequency_calls[i,4]))),
">",
as.character(complement(DNAString(frequency_calls[i,5]))),
sep="")
if(!is.na(strsplit(frequency_calls[i,11],split=",")[[1]][j])&&
!is.na(strsplit(frequency_calls[i,12],split=",")[[1]][j])&&
strsplit(frequency_calls[i,11],split=",")[[1]][j]!="NA"&&
strsplit(frequency_calls[i,12],split=",")[[1]][j]!="NA"&&
nchar(strsplit(frequency_calls[i,11],split=",")[[1]][j])==3&&
nchar(strsplit(frequency_calls[i,12],split=",")[[1]][j])==3){
p.[i]<-paste("p.",
strsplit(frequency_calls[i,9],split=",")[[1]][j],
strsplit(frequency_calls[i,8],split=",")[[1]][j],
strsplit(frequency_calls[i,10],split=",")[[1]][j],
sep="")
}
if(!is.na(strsplit(frequency_calls[i,11],split=",")[[1]][j])&&
!is.na(strsplit(frequency_calls[i,12],split=",")[[1]][j])&&
strsplit(frequency_calls[i,11],split=",")[[1]][j]!="NA"&&
strsplit(frequency_calls[i,12],split=",")[[1]][j]!="NA"&&
(nchar(strsplit(frequency_calls[i,11],split=",")[[1]][j])!=3||
nchar(strsplit(frequency_calls[i,12],split=",")[[1]][j])!=3)){
if((nchar(strsplit(frequency_calls[i,11],split=",")[[1]][j])%%3)!=0||
(nchar(strsplit(frequency_calls[i,12],split=",")[[1]][j])%%3)!=0){
p.[i]<-paste("p.",
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,11],split=",")[[1]][j]))),
strsplit(frequency_calls[i,8],split=",")[[1]][j],
"fs",sep="")
}
if((nchar(strsplit(frequency_calls[i,11],split=",")[[1]][j])%%3)==0&&
(nchar(strsplit(frequency_calls[i,12],split=",")[[1]][j])%%3)==0){
p.[i]<-paste("p.",
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,11],split=",")[[1]][j]))),
strsplit(frequency_calls[i,8],split=",")[[1]][j],
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,12],split=",")[[1]][j]))),sep="")
}
}
}
if(j>1){
c.[i]<-paste(c.[i],
paste("c.",
strsplit(frequency_calls[i,7],split=",")[[1]][j],
frequency_calls[i,4],">",
frequency_calls[i,5],sep=""),
sep=",")
c.complement[i]<-paste(c.complement[i],
paste("c.",
strsplit(frequency_calls[i,7],split=",")[[1]][j],
as.character(complement(DNAString(frequency_calls[i,4]))),
">",
as.character(complement(DNAString(frequency_calls[i,5]))),
sep=""),sep=",")
if(!is.na(strsplit(frequency_calls[i,11],split=",")[[1]][j])&&
!is.na(strsplit(frequency_calls[i,12],split=",")[[1]][j])&&
strsplit(frequency_calls[i,11],split=",")[[1]][j]!="NA"&&
strsplit(frequency_calls[i,12],split=",")[[1]][j]!="NA"&&
nchar(strsplit(frequency_calls[i,11],split=",")[[1]][j])==3&&
nchar(strsplit(frequency_calls[i,12],split=",")[[1]][j])==3){
p.[i]<-paste(p.[i],
paste("p.",
strsplit(frequency_calls[i,9],split=",")[[1]][j],
strsplit(frequency_calls[i,8],split=",")[[1]][j],
strsplit(frequency_calls[i,10],split=",")[[1]][j],
sep=""),
sep=",")
}
if(!is.na(strsplit(frequency_calls[i,11],split=",")[[1]][j])&&
!is.na(strsplit(frequency_calls[i,12],split=",")[[1]][j])&&
strsplit(frequency_calls[i,11],split=",")[[1]][j]!="NA"&&
strsplit(frequency_calls[i,12],split=",")[[1]][j]!="NA"&&
(nchar(strsplit(frequency_calls[i,11],split=",")[[1]][j])!=3||
nchar(strsplit(frequency_calls[i,12],split=",")[[1]][j])!=3)){
if((nchar(strsplit(frequency_calls[i,11],split=",")[[1]][j])%%3)!=0||
(nchar(strsplit(frequency_calls[i,12],split=",")[[1]][j])%%3)!=0){
p.[i]<-paste(p.[i],
paste("p.",
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,11],split=",")[[1]][j]))),
strsplit(frequency_calls[i,8],split=",")[[1]][j],
"fs",sep=""),
sep=",")
}
if((nchar(strsplit(frequency_calls[i,11],split=",")[[1]][j])%%3)==0&&
(nchar(strsplit(frequency_calls[i,12],split=",")[[1]][j])%%3)==0){
p.[i]<-paste(p.[i],
paste("p.",
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,11],split=",")[[1]][j]))),
strsplit(frequency_calls[i,8],split=",")[[1]][j],
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,12],split=",")[[1]][j]))),sep=""),sep=",")
}
}
}
}
}
for(i in seq_along(frequency_calls[,1])){
progress$inc(1/length(results[,1]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
#SNPs
if(nchar(frequency_calls[i,4])==1&&
nchar(frequency_calls[i,5])==1){
snp_info<-snpsByOverlaps(snps,
paste(frequency_calls[i,2],
":",
frequency_calls[i,3],
"-",
frequency_calls[i,3],
sep=""))
if(length(snp_info)>0){
snp_info<-snp_info[pos(snp_info)==frequency_calls[i,3],]
if(length(snp_info)>0){
if(length(grep(results[i,5],
IUPAC_CODE_MAP[snp_info$alleles_as_ambig]))>0||
(length(grep(results[i,4],
IUPAC_CODE_MAP[snp_info$alleles_as_ambig]))==0&&
length(grep(as.character(complement(DNAString(results[i,5]))),
IUPAC_CODE_MAP[snp_info$alleles_as_ambig])>0))){
results[i,6]<-snp_info$RefSNP_id
}
}
}
if(!is.null(input$`1kgenomes`)){
snp_info<-gscores(g1000,
GRanges(paste(frequency_calls[i,2],
":",
frequency_calls[i,3],
sep="")))
if(length(snp_info)>0){
results$G1000_AF[i]<-max(snp_info$AF)
}
}
if(!is.null(input$exac)){
snp_info<-gscores(exac,
GRanges(paste(frequency_calls[i,2],
":",
frequency_calls[i,3],
sep="")))
if(length(snp_info)>0){
results$ExAC_AF[i]<-max(snp_info$AF)
}
}
if(!is.null(input$gad)){
snp_info<-gscores(gad,
GRanges(paste(frequency_calls[i,2],
":",
frequency_calls[i,3],
sep="")))
if(length(snp_info)>0){
results$GAD_AF[i]<-max(snp_info$AF)
}
}
if(!is.null(input$cosmic)){
snp_info<-rowRanges(cosmic_67)[as.character(seqnames(rowRanges(cosmic_67)))==frequency_calls[i,2]&start(ranges(rowRanges(cosmic_67)))==frequency_calls[i,3]]
if(length(snp_info)>0){
for(j in seq_along(snp_info[,1])){
if(snp_info$REF==frequency_calls[i,4]&&
snp_info$ALT[[1]]==frequency_calls[i,5]||
(snp_info$REF==as.character(complement(DNAString(frequency_calls[i,4])))&&
snp_info$ALT[[1]]==as.character(complement(DNAString(frequency_calls[i,5]))))){
snp_info2<-info(cosmic_67)[rownames(info(cosmic_67))==names(snp_info[j,]),]
grep_c.<-grep(snp_info2$CDS,
as.character(strsplit(c.[i],split=",")[[1]]))
grep_c.comp<-grep(snp_info2$CDS,
as.character(strsplit(c.complement[i],split=",")[[1]]))
grep_p.<-grep(snp_info2$AA,
as.character(strsplit(p.[i],split=",")[[1]]))
if(length(intersect(grep_c.,grep_p.))>0||
length(intersect(grep_c.comp,grep_p.))>0){
if(!is.na(results$CosmicID[i])){
results$CosmicID[i]<-paste(results$CosmicID[i],
names(snp_info[j,]),sep=",")
results$Cosmic_Counts[i]<-paste(results$Cosmic_Counts[i],
snp_info2$CNT,sep=",")
}
if(is.na(results$CosmicID[i])){
results$CosmicID[i]<-names(snp_info[j,])
results$Cosmic_Counts[i]<-snp_info2$CNT
}
}
}
}
}
}
if(!is.null(input$clinvar)){
snp_info_temp<-data.frame()
for(j in seq_along(strsplit(frequency_calls[i,14],
split=",")[[1]])){
if(!is.na(strsplit(frequency_calls[i,14],split=",")[[1]][j])){
temp<-clinvar[grep(strsplit(frequency_calls[i,14],split=",")[[1]][j],clinvar[,1]),]
temp2<-temp[nchar(temp[,4])==1&nchar(temp[,5])==1&temp[,4]!="-"&temp[,5]!="-",]
if(length(snp_info_temp)>0){
snp_info_temp<-rbind(snp_info_temp,
temp2)
}
if(length(snp_info_temp[1,1])==0){
snp_info_temp<-temp2
}
}
}
snp_info<-unique(snp_info_temp)
if(length(snp_info)>0){
snp_info2<-snp_info[snp_info[,2]==frequency_calls[i,3],]
if(length(snp_info2[,1])>0){
if((snp_info2[1,4]==frequency_calls[i,4]&&
snp_info2[1,5]==frequency_calls[i,5])||
(snp_info2[1,4]==as.character(complement(DNAString(frequency_calls[i,4])))&&
snp_info2[1,5]==as.character(complement(DNAString(frequency_calls[i,5]))))){
results$ClinVar[i]<-snp_info2[1,6]
}
}
}
}
}
#Indels
if(nchar(frequency_calls[i,4])!=1||
nchar(frequency_calls[i,5])!=1){
suppressWarnings(snp_info<-snpsByOverlaps(indels,paste("ch",frequency_calls[i,2],":",frequency_calls[i,3],"-",(as.numeric(frequency_calls[i,3])+nchar(frequency_calls[i,4])-1),sep="")))
if(length(snp_info)>0){
snp_info_rs<-snp_info$RefSNP_id[(start(ranges(snp_info))<=frequency_calls[i,3])&(end(ranges(snp_info))>=(as.numeric(frequency_calls[i,3])+nchar(frequency_calls[i,4])-1))]
if(length(snp_info_rs)>0){
ncbi<-ncbi_snp_query(snp_info_rs)
for(j in seq_along(ncbi[,1])){
if(nchar(results[i,4])>nchar(results[i,5])){
if(length(grep(substr(results[i,4],
2,
nchar(results[i,4])),
ncbi[j,9]))>0){
results[i,6]<-ncbi[j,1]
}
}
if(nchar(results[i,4])<nchar(results[i,5])){
if(length(grep(substr(results[i,5],
2,
nchar(results[i,5])),
ncbi[j,9]))>0){
results[i,6]<-ncbi[j,1]
}
}
}
}
}
if(!is.null(input$cosmic)){
snp_info<-rowRanges(cosmic_67)[as.character(seqnames(rowRanges(cosmic_67)))==frequency_calls[i,2]&start(ranges(rowRanges(cosmic_67)))==frequency_calls[i,3]]
if(length(snp_info)>0){
for(j in seq_along(snp_info[,1])){
if(snp_info$REF==frequency_calls[i,4]&&
snp_info$ALT[[1]]==frequency_calls[i,5]||
(snp_info$REF==as.character(complement(DNAString(frequency_calls[i,4])))&&
snp_info$ALT[[1]]==as.character(complement(DNAString(frequency_calls[i,5]))))){
snp_info2<-info(cosmic_67)[rownames(info(cosmic_67))==names(snp_info[j,]),]
grep_c.<-grep(snp_info2$CDS,
as.character(strsplit(c.[i],split=",")[[1]]))
grep_c.comp<-grep(snp_info2$CDS,
as.character(strsplit(c.complement[i],split=",")[[1]]))
grep_p.<-grep(snp_info2$AA,
as.character(strsplit(p.[i],split=",")[[1]]))
if(length(intersect(grep_c.,grep_p.))>0||
length(intersect(grep_c.comp,grep_p.))>0){
if(!is.na(results$CosmicID[i])){
results$CosmicID[i]<-paste(results$CosmicID[i],names(snp_info[j,]),sep=",")
results$Cosmic_Counts[i]<-paste(results$Cosmic_Counts[i],snp_info2$CNT,sep=",")
}
if(is.na(results$CosmicID[i])){
results$CosmicID[i]<-names(snp_info[j,])
results$Cosmic_Counts[i]<-snp_info2$CNT
}
}
}
}
}
}
if(!is.null(input$clinvar)){
snp_info_temp<-data.frame()
for(j in seq_along(strsplit(frequency_calls[i,14],
split=",")[[1]])){
if(!is.na(strsplit(frequency_calls[i,14],
split=",")[[1]][j])){
temp<-clinvar[grep(strsplit(frequency_calls[i,14],
split=",")[[1]][j],
clinvar[,1]),]
temp2<-temp[nchar(temp[,4])>1|nchar(temp[,5])>1|temp[,4]=="-"|temp[,5]=="-",]
if(length(snp_info_temp)>0){
snp_info_temp<-rbind(snp_info_temp,
temp2)
}
if(length(snp_info_temp[1,1])==0){
snp_info_temp<-temp2
}
}
}
snp_info<-unique(snp_info_temp)
if(length(snp_info)>0){
snp_info2<-snp_info[snp_info[,2]==(as.numeric(frequency_calls[i,3])-1),]
if(length(snp_info2[,1])>0){
for(j in seq_along(snp_info2[,1])){
if(snp_info2[j,4]=="-"&&
snp_info2[j,5]==substr(frequency_calls[i,5],
2,
nchar(frequency_calls[i,5]))){
results$ClinVar[i]<-snp_info2[j,6]
}
if(snp_info2[j,5]=="-"&&
snp_info2[j,4]==substr(frequency_calls[i,4],
2,
nchar(frequency_calls[i,4]))){
results$ClinVar[i]<-snp_info2[j,6]
}
}
}
}
}
}
}
if(length(results[!is.na(results[,6]),6])<=3){
suppressWarnings(ncbi<-ncbi_snp_query(results[!is.na(results[,6]),6]))
}
if(length(results[!is.na(results[,6]),6])>3){
abfrage<-results[!is.na(results[,6]),6]
if(((length(results[!is.na(results[,6]),6])-1)%%3)==0){
limits<-seq(1,
length(results[!is.na(results[,6]),6]),
3)
}
if(((length(results[!is.na(results[,6]),6])-1)%%3)!=0){
limits<-c(seq(1,
length(results[!is.na(results[,6]),6]),
3),
length(results[!is.na(results[,6]),6]))
}
suppressWarnings(ncbi<-ncbi_snp_query(abfrage[1:3]))
for(i in 2:(length(limits)-1)){
suppressWarnings(temp<-ncbi_snp_query(abfrage[limits[i]:(limits[i+1]-1)]))
ncbi<-rbind(ncbi,temp)
}
}
for(i in seq_along(results[,1])){
if(!is.na(results[i,6])){
results$dbSNP_MAF[i]<-as.numeric(max(ncbi[ncbi[,1]==results[i,6],10]))
if(sum(ncbi[ncbi[,1]==results[i,6],9]==results[i,4],na.rm=TRUE)>0){
if(!is.na(results$dbSNP_MAF[i])){
results$dbSNP_MAF[i]<-1-results$dbSNP_MAF[i]
}
if(!is.na(results$G1000_AF[i])){
results$G1000_AF[i]<-1-results$G1000_AF[i]
}
if(!is.na(results$ExAC_AF[i])){
results$ExAC_AF[i]<-1-results$ExAC_AF[i]
}
if(!is.na(results$GAD_AF[i])){
results$GAD_AF[i]<-1-results$GAD_AF[i]
}
}
}
}
progress$close()
results<-cbind(results,Prediction=NA,Score=NA)
progress <- shiny::Progress$new()
progress$set(message = "6. Determine Extended Set of Characteristics (prediction)",
value = 0)
if(input$predict!="PolyPhen2"){
for(i in seq(1,length(results[,6]))[!is.na(results[,6])]){
progress$inc(1/length(seq(1,length(results[,6]))[!is.na(results[,6])]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
suppressWarnings(info<-select(SIFT.Hsapiens.dbSNP137,keys=substr(results[i,6],3,nchar(results[i,6]))))
if(length(info)>0){
if(input$predict=="SIFT"){
#score <0.05 -> damaging (else: tolerated)
results$Prediction[i]<-info[which.min(info[,15]),16]
results$Score[i]<-min(info[,15])
}
if(input$predict=="Provean"){
#score <-2.5 -> deleterious (else: neutral)
results$Prediction[i]<-info[which.min(info[,11]),12]
results$Score[i]<-min(info[,11])
}
}
}
}
if(input$predict=="PolyPhen2"){
#Polyphen (probably damaging, possibly damaging, benign,
#unknown); probability of variant being damaging
for(i in seq(1,length(results[,6]))[!is.na(results[,6])]){
progress$inc(1/length(seq(1,length(results[,6]))[!is.na(results[,6])]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
suppressWarnings(info<-select(PolyPhen.Hsapiens.dbSNP131,keys=results[i,6]))
if(length(info)>0){
if(is.na(max(info[,19]))){
results$Prediction[i]<-"unknown"
results$Score[i]<-max(info[,19])
}
if(!is.na(max(info[,19]))){
results$Prediction[i]<-info[which.max(info[,19]),15]
results$Score[i]<-max(info[,19])
}
}
}
}
for(i in seq_along(checkpoint[,1])){
for(j in 2:length(checkpoint[1,])){
if(!is.na(checkpoint[i,j])){
checkpoint[i,j]<-6
}
}
}
if(is.null(input$dbSNP)){
database_calls<-cbind(results[,c(1:5,8:(length(results[1,])))],
c.,c.complement,p.)
}
if(!is.null(input$dbSNP)){
database_calls<-cbind(results,c.,c.complement,p.)
}
write.table(database_calls,
paste(input$output_folder,
"/Results_Databases.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
write.table(checkpoint,
paste(input$output_folder,"/checkpoint.txt",
sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
checkpoint_state<-6
progress$close()
}
#6: After Extended Set of Characteristics
if(checkpoint_state==6){
if(exists("frequency_calls")==FALSE||
exists("database_calls")==FALSE||
exists("combined_calls")==FALSE){
#1. Reading Input
log_info<-c(log_info,"0. Reading input<br>")
output$log_info<-renderUI({HTML(log_info)})
frequency_calls<-read.table(paste(input$output_folder,
"/Results_Frequency.txt",
sep=""),
stringsAsFactors = FALSE,
header=TRUE,sep="\t")
database_calls<-read.table(paste(input$output_folder,
"/Results_Databases.txt",
sep=""),
stringsAsFactors = FALSE,
header=TRUE,sep="\t")
combined_calls<-read.table(paste(input$output_folder,
"/Results_Raw.txt",
sep=""),
stringsAsFactors = FALSE,
header=TRUE,sep="\t")
}
#7. Final filtration
log_info<-c(log_info,"7. Perform Final Filtration<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "7. Perform final filtration",
value = 0)
if(input$stricter_thresholds=="No"){
dp<-input$dp
nr_alt<-input$nr_alt
vaf<-input$vaf
low_bq<-input$low_bq
bq_diff<-input$bq_diff
}
if(input$stricter_thresholds=="Yes"){
dp<-input$dp2
nr_alt<-input$nr_alt2
vaf<-input$vaf2
low_bq<-input$bq2
bq_diff<-input$bq_diff2
}
nrsamples<-input$nr_samples
nrsamples_high<-ceiling(length(checkpointFile[,1])/2)
if(nrsamples_high==1){
nrsamples_high<-2
}
if(input$predict=="SIFT"){
limit_provean<-input$damaging_safe1
limit_provean2<-input$tolerated_safe1
}
if(input$predict=="Provean"){
limit_provean<-input$damaging_safe2
limit_provean2<-input$tolerated_safe2
}
if(input$predict=="PolyPhen2"){
limit_provean<-input$damaging_safe3
limit_provean2<-input$tolerated_safe3
}
if(!is.null(input$primerPositions)){
primer_temp<-input$primerPositions
primer<-read.table(primer_temp$datapath,
header=FALSE,sep="\t",
stringsAsFactors=FALSE)
}
if(!is.null(input$hotspots)){
hotspots_temp<-input$hotspots
hotspots<-read.table(hotspots_temp$datapath,
header=TRUE,sep="\t",
stringsAsFactors=FALSE)
}
results<-cbind(frequency_calls[,c(1:5,14:16,6,13)],
database_calls[,c((length(database_calls[1,])-2):length(database_calls[1,]))],
frequency_calls[,c(11,12)],
Nr_Ref=frequency_calls$Nr_Ref,
Nr_Alt=frequency_calls$Nr_Alt,
DP=frequency_calls$DP,
VAF=frequency_calls$VAF,
frequency_calls[,c(17:(length(frequency_calls[1,])-14))],
Called=rowSums(frequency_calls[,c(17:(length(frequency_calls[1,])-14))],na.rm=TRUE),
database_calls[,c(6:(length(database_calls[1,])-3))],
frequency_calls[,c((length(frequency_calls[1,])-9):(length(frequency_calls[1,])))])
artifact_because<-data.frame(nr_samples=rep(NA,length(frequency_calls[,1])),
nr_samples_similar=rep(NA,length(frequency_calls[,1])),
nr_databases=rep(NA,length(frequency_calls[,1])),
polymorphism_db=rep(NA,length(frequency_calls[,1])),
mutation_db=rep(NA,length(frequency_calls[,1])),
cosmic_nr=rep(NA,length(frequency_calls[,1])),
Poly_freq=rep(NA,length(frequency_calls[,1])))
#filter frequency
if(input$stricter_thresholds=="Yes"){
progress$inc(1/13,
detail="-> Consider Frequency and Base Quality")
include1<-results$DP>=dp
include2<-results$Nr_Alt>=nr_alt
include3<-(results$VAF*100)>=vaf
include4<-results$BQ_ALT>=low_bq
include5<-(results$BQ_REF-results$BQ_ALT)<=bq_diff
temp<-results[rowSums(cbind(include1,include2,include3,include4,include5))>=5|is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
results<-temp
temp<-frequency_calls[rowSums(cbind(include1,include2,include3,include4,include5))>=5|is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
frequency_calls<-temp
temp<-database_calls[rowSums(cbind(include1,include2,include3,include4,include5))>=5|is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
database_calls<-temp
temp<-artifact_because[rowSums(cbind(include1,include2,include3,include4,include5))>=5|is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
artifact_because<-temp
}
if(input$stricter_thresholds=="No"){
progress$inc(1/13)
}
#nr of samples
progress$inc(1/13,
detail="-> Consider samples with the same call")
progress_small <- shiny::Progress$new()
progress_small$set(message = "", value = 0)
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
artifact_because[i,1]<-length(combined_calls[intersect(intersect(grep(results[i,2],combined_calls[,2]),grep(results[i,3],combined_calls[,3])),intersect(grep(results[i,4],combined_calls[,4]),grep(results[i,5],combined_calls[,5]))),1])
}
progress_small$close()
progress$inc(1/13,
detail="-> Consider samples with a call at the same position")
progress_small <- shiny::Progress$new()
progress_small$set(message = "", value = 0)
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
artifact_because[i,2]<-length(combined_calls[intersect(grep(results[i,2],combined_calls[,2]),grep(results[i,3],combined_calls[,3])),1])
}
progress_small$close()
progress$inc(1/13,
detail="-> Consider background information")
background_info<-rep(0,length(results[,1]))
start<-0
ende<-0
neu<-TRUE
i<-1
while(i<=length(results[,1])){
if(neu==TRUE){
start<-ende<-i
}
i<-i+1
if(i<=length(results[,1])&&
as.character(results[i,2])==as.character(results[i-1,2])&&
results[i,3]==results[i-1,3]&&
results[i,4]==results[i-1,4]&&
results[i,5]==results[i-1,5]){
ende<-i
neu<-FALSE
}
if(i>length(results[,1])||
as.character(results[i,2])!=as.character(results[i-1,2])||
results[i,3]!=results[i-1,3]||
results[i,4]!=results[i-1,4]||
results[i,5]!=results[i-1,5]){
for(j in start:ende){
background_info[j]<-ende-start+1
neu<-TRUE
}
}
}
#databases
progress$inc(1/13,detail="-> Consider nr of databases")
if(length(database_calls[1,])>10){
if(length(grep("dbSNP",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$dbSNP[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],1,na.rm=TRUE)
if(!is.na(results$dbSNP_MAF[i])&&
as.numeric(results$dbSNP_MAF[i])<=0.001){
artifact_because[i,5]<-sum(artifact_because[i,5],1,na.rm=TRUE)
}
if(!is.na(results$dbSNP_MAF[i])&&
as.numeric(results$dbSNP_MAF[i])>0.001){
artifact_because[i,4]<-sum(artifact_because[i,4],1,na.rm=TRUE)
}
}
}
}
if(length(grep("G1000_AF",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$G1000_AF[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],1,na.rm=TRUE)
if(as.numeric(results$G1000_AF[i])<=0.001){
artifact_because[i,5]<-sum(artifact_because[i,5],1,na.rm=TRUE)
}
if(as.numeric(results$G1000_AF[i])>0.001){
artifact_because[i,4]<-sum(artifact_because[i,4],1,na.rm=TRUE)
}
}
}
}
if(length(grep("ExAC_AF",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$ExAC_AF[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],1,na.rm=TRUE)
if(as.numeric(results$ExAC_AF[i])<=0.0005){
artifact_because[i,5]<-sum(artifact_because[i,5],1,na.rm=TRUE)
}
if(as.numeric(results$ExAC_AF[i])>0.0005){
artifact_because[i,4]<-sum(artifact_because[i,4],1,na.rm=TRUE)
}
}
}
}
if(length(grep("GAD_AF",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$GAD_AF[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],1,na.rm=TRUE)
if(as.numeric(results$GAD_AF[i])<=0.001){
artifact_because[i,5]<-sum(artifact_because[i,5],1,na.rm=TRUE)
}
if(as.numeric(results$GAD_AF[i])>0.001){
artifact_because[i,4]<-sum(artifact_because[i,4],1,na.rm=TRUE)
}
}
}
}
if(length(grep("CosmicID",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$CosmicID[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],1,na.rm=TRUE)
artifact_because[i,6]<-sum(as.numeric(strsplit(as.character(database_calls$Cosmic_Counts[i]),split=",")[[1]]))
if(artifact_because[i,6]>20){
artifact_because[i,5]<-sum(artifact_because[i,5],1,na.rm=TRUE)
}
if(artifact_because[i,6]<=20){
artifact_because[i,4]<-sum(artifact_because[i,4],1,na.rm=TRUE)
}
}
}
}
if(length(grep("ClinVar",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$ClinVar[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],1,na.rm=TRUE)
if(length(grep("Pathogenic",
results$ClinVar[i],
ignore.case = TRUE))>0){
artifact_because[i,5]<-sum(artifact_because[i,5],1,na.rm=TRUE)
}
if(length(grep("Benign",
results$ClinVar[i],
ignore.case = TRUE))>0){
artifact_because[i,4]<-sum(artifact_because[i,4],1,na.rm=TRUE)
}
}
}
}
}
#tolerated and freq
progress$inc(1/13,detail="-> Consider VAF when tolerated")
for(i in seq_along(results[,1])){
if(!is.na(results$VAF[i])&&((results$VAF[i]>=0.35&&
results$VAF[i]<=0.65)||
(results$VAF[i]>=0.85))){
artifact_because[i,7]<-1
}
if(!is.na(results$VAF[i])&&(results$VAF[i]<0.35||
(results$VAF[i]>0.65&&
results$VAF[i]<0.85))){
artifact_because[i,7]<-0
}
}
#large number of samples and high VAF
progress$inc(1/13,
detail="-> Consider VAF when high nr of samples")
i<-1
while(i<=length(results[,1])){
subset<-results[i:(i+background_info[i]-1),]
if(length(subset[,1])>nrsamples&&
sum(!is.na(subset$VAF))==length(subset[,1])&&
sum(subset$VAF>0.85)>=floor(0.9*length(subset[,1]))){
artifact_because[i:(i+background_info[i]-1),7]<-2
}
i<-i+background_info[i]
}
#test for strand bias (8 von 15)
progress$inc(1/13,detail="-> Consider strand bias")
strandbias<-rep(NA,length(results[,1]))
for(i in seq_along(results[,1])){
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])){
test<-fisher.test(x=matrix(c(results$Nr_Ref_fwd[i],
results$Nr_Alt_fwd[i],
results$Nr_Ref_rev[i],
results$Nr_Alt_rev[i]),
ncol=2))
strandbias[i]<-test$p.value
}
if(!is.null(input$primerPositions)){
chr<-as.character(results[i,2])==as.character(primer[,1])
start<-results[i,3]>primer[,2]
end<-(as.numeric(results[i,3])+nchar(results[i,4])-1)<=primer[,3]
if(sum(rowSums(cbind(chr,start,end))==3)>0){
strandbias[i]<-2
}
}
}
#check for hotspots
progress$inc(1/13,detail="-> Consider hotspot list")
hotspot<-rep(NA,length(results[,1]))
progress_small <- shiny::Progress$new()
progress_small$set(message = "", value = 0)
if(!is.null(input$hotspots)){
for(i in seq_along(hotspots[,1])){
progress_small$inc(1/length(hotspots[,1]),
detail=paste("-> Hotspot",i,
"out of",
length(hotspots[,1])))
found1<-grep(hotspots[i,1],results$Gene)
if(length(found1)>0){
if(length(grep("fs",hotspots[i,2]))==0&&
length(grep("del",hotspots[i,2]))==0&&
length(grep("ins",hotspots[i,2]))==0){
#Just an SNV
found2<-grep(hotspots[i,2],results$p.,
fixed=TRUE)
flag<-NA
if(length(found2)>0){
flag<-rep(FALSE,length(results[,1]))
if(is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Ref[found2[j]])==1&&
nchar(results$Alt[found2[j]])==1
}
}
if(!is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Ref[found2[j]])==1&&
nchar(results$Alt[found2[j]])==1&&
as.numeric(results$VAF[found2[j]])>=as.numeric(hotspots[i,3])
}
}
}
}
if(length(grep("fs",hotspots[i,2]))>0){
#frameshift
searchstring<-substr(hotspots[i,2],2,
(nchar(hotspots[i,2])-2))
found2<-grep(searchstring,results$p.)
flag<-NA
if(length(found2)>0){
flag<-rep(FALSE,length(results[,1]))
if(is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))!=0&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0
}
}
if(!is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))!=0&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0&&as.numeric(results$VAF[found2[j]])>=as.numeric(hotspots[i,3])
}
}
}
}
if(length(grep("del",hotspots[i,2]))>0){
#deletion
searchstring_temp<-substr(hotspots[i,2],2,
(nchar(hotspots[i,2])-3))
searchstring<-strsplit(searchstring_temp,
split="_")[[1]][1]
found2<-grep(searchstring,results$p.)
flag<-NA
if(length(found2)>0){
flag<-rep(FALSE,length(results[,1]))
if(is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Ref[found2[j]])>1&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0
}
}
if(!is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Ref[found2[j]])>1&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0&&as.numeric(results$VAF[found2[j]])>=as.numeric(hotspots[i,3])
}
}
}
}
if(length(grep("ins",hotspots[i,2]))>0){
#deletion
searchstring_temp<-substr(hotspots[i,2],2,
(nchar(hotspots[i,2])-3))
searchstring<-strsplit(searchstring_temp,split="_")[[1]][1]
found2<-grep(searchstring,results$p.)
flag<-NA
if(length(found2)>0){
flag<-rep(FALSE,length(results[,1]))
if(is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Alt[found2[j]])>1&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0
}
}
if(!is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Alt[found2[j]])>1&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0&&as.numeric(results$VAF[found2[j]])>=as.numeric(hotspots[i,3])
}
}
}
}
if(length(intersect(found1,found2))>0){
for(j in intersect(found1,found2)){
if(flag[j]==TRUE){
hotspot[j]<-1
}
}
}
}
}
}
progress_small$close()
write.table(cbind(hotspot,results),
paste(input$output_folder,"Hotspot_test.txt"),
sep="\t",quote=FALSE,row.names=FALSE)
##final filtration
results<-cbind(results,strandbias,artifact_because[,c(1:2)],
Category=NA)
#artifact score
progress$inc(1/13,detail="-> Perform final filtration")
artifact_score<-rep(0,length(results[,1]))
progress_small <- shiny::Progress$new()
progress_small$set(message = "Calculate Artifact Score",
value = 0)
if(input$artifact_score=="No"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,
"out of",
length(results[,1])))
if(results$nr_samples[i]>nrsamples){
artifact_score[i]<-artifact_score[i]+2
}
if(results$nr_samples[i]>nrsamples_high&&
is.na(hotspot[i])){
artifact_score[i]<-artifact_score[i]+2
}
if((nchar(results$Ref[i])>1||
nchar(results$Alt[i])>1)&&
results$nr_samples_similar[i]>results$nr_samples[i]){
artifact_score[i]<-artifact_score[i]+1
}
if((nchar(results$Ref[i])>1||
nchar(results$Alt[i])>1)&&
!is.na(results$VAF[i])&&results$VAF[i]<0.05){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(artifact_because[i,7])&&
artifact_because[i,7]==2){
artifact_score[i]<-artifact_score[i]+2
}
if(is.null(input$primerPositions)||
(!is.na(results$strandbias[i])&&
results$strandbias[i]!=2)){
if(!is.na(results$strandbias[i])&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(results$Nr_Alt_fwd[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_fwd[i]>=(nr_alt/2)&&
results$Nr_Alt_rev[i]>=(nr_alt/2))&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]-1
}
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
(results$Nr_Alt_fwd[i]<=2&&
results$Nr_Ref_fwd[i]>=(dp-nr_alt)/2)&&
results$strandbias[i]>=0.001){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
(results$Nr_Alt_fwd[i]<=2&&
results$Nr_Ref_fwd[i]<(dp-nr_alt)/2)&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]-1
}
if(!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_rev[i]<=2&&
results$Nr_Ref_rev[i]>=(dp-nr_alt)/2)&&
results$strandbias[i]>=0.001){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_rev[i]<=2&&
results$Nr_Ref_rev[i]<(dp-nr_alt)/2)&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]-1
}
}
if(!is.null(input$primerPositions)&&
!is.na(results$strandbias[i])&&
results$strandbias[i]==2){
artifact_score[i]<-artifact_score[i]-1
}
if(!is.na(results$VAF[i])&&results$VAF[i]<0.02){
artifact_score[i]<-artifact_score[i]+2
}
if(is.na(artifact_because[i,3])&&
!is.na(results$VAF[i])&&
results$VAF[i]<0.10){
artifact_score[i]<-artifact_score[i]+1
}
if(is.na(artifact_because[i,3])&&
results$nr_samples[i]>nrsamples_high){
artifact_score[i]<-artifact_score[i]+1
}
if((!is.na(results$Score[i])&&
results$Score[i]<limit_provean)){
artifact_score[i]<-artifact_score[i]-1
}
if(!is.na(results$Score[i])&&
results$Score[i]>limit_provean2&&
!is.na(artifact_because[i,7])&&
artifact_because[i,7]==0){
artifact_score[i]<-artifact_score[i]+1
}
if(results$Called[i]>=4){
artifact_score[i]<-artifact_score[i]-1
}
if(results$Called[i]>=5){
artifact_score[i]<-artifact_score[i]-1
}
if(results$Called[i]>=6){
artifact_score[i]<-artifact_score[i]-1
}
if(results$Called[i]==1){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(results$BQ_ALT[i])&&
results$BQ_ALT[i]<(mean(results$BQ_ALT,na.rm=TRUE)-3*sd(results$BQ_ALT,na.rm=TRUE))){
artifact_score[i]<-artifact_score[i]+4
}
if(!is.na(hotspot[i])){
artifact_score[i]<-artifact_score[i]-3
}
if(!is.na(results$LoFreq[i])&&
!is.na(results$FreeBayes[i])&&
!is.na(results$VarDict[i])&&
results$LoFreq[i]==1&&
results$FreeBayes[i]==1&&results$VarDict[i]==1){
artifact_score[i]<-artifact_score[i]-3
}
if(artifact_score[i]>-1){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
}
if(input$artifact_score=="Yes"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,
"out of",
length(results[,1])))
if(results$nr_samples[i]>nrsamples){
artifact_score[i]<-artifact_score[i]+input$detectedLow
}
if(results$nr_samples[i]>nrsamples_high&&
is.na(hotspot[i])){
artifact_score[i]<-artifact_score[i]+input$detectedHigh
}
if((nchar(results$Ref[i])>1||
nchar(results$Alt[i])>1)&&
results$nr_samples_similar[i]>results$nr_samples[i]){
artifact_score[i]<-artifact_score[i]+input$isIndel
}
if((nchar(results$Ref[i])>1||
nchar(results$Alt[i])>1)&&
!is.na(results$VAF[i])&&results$VAF[i]<0.05){
artifact_score[i]<-artifact_score[i]+input$isIndelVAF
}
if(!is.na(artifact_because[i,7])&&
artifact_because[i,7]==2){
artifact_score[i]<-artifact_score[i]+input$detectedLowVAF
}
if(is.null(input$primerPositions)||
(!is.na(results$strandbias[i])&&
results$strandbias[i]!=2)){
if(!is.na(results$strandbias[i])&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+input$noPrimerP
}
if(!is.na(results$Nr_Alt_fwd[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_fwd[i]>=(nr_alt/2)&&
results$Nr_Alt_rev[i]>=(nr_alt/2))&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+input$primerPAlt
}
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
(results$Nr_Alt_fwd[i]<=2&&
results$Nr_Ref_fwd[i]>=(dp-nr_alt)/2)&&
results$strandbias[i]>=0.001){
artifact_score[i]<-artifact_score[i]+input$noPrimerPFwd
}
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
(results$Nr_Alt_fwd[i]<=2&&
results$Nr_Ref_fwd[i]<(dp-nr_alt)/2)&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+input$primerPFwd
}
if(!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_rev[i]<=2&&
results$Nr_Ref_rev[i]>=(dp-nr_alt)/2)&&
results$strandbias[i]>=0.001){
artifact_score[i]<-artifact_score[i]+input$noPrimerPRev
}
if(!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_rev[i]<=2&&
results$Nr_Ref_rev[i]<(dp-nr_alt)/2)&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+input$primerPRev
}
}
if(!is.null(input$primerPositions)&&
!is.na(results$strandbias[i])&&
results$strandbias[i]==2){
artifact_score[i]<-artifact_score[i]+input$primerLocation
}
if(!is.na(results$VAF[i])&&results$VAF[i]<0.02){
artifact_score[i]<-artifact_score[i]+input$vafLow
}
if(is.na(artifact_because[i,3])&&
!is.na(results$VAF[i])&&results$VAF[i]<0.10){
artifact_score[i]<-artifact_score[i]+input$databaseVAF
}
if(is.na(artifact_because[i,3])&&
results$nr_samples[i]>nrsamples_high){
artifact_score[i]<-artifact_score[i]+input$databaseHigh
}
if((!is.na(results$Score[i])&&
results$Score[i]<limit_provean)){
artifact_score[i]<-artifact_score[i]+input$predictionSafe
}
if(!is.na(results$Score[i])&&
results$Score[i]>limit_provean2&&
!is.na(artifact_because[i,7])&&
artifact_because[i,7]==0){
artifact_score[i]<-artifact_score[i]+input$predictionVAF
}
if(results$Called[i]>=input$nrcaller4){
artifact_score[i]<-artifact_score[i]+input$reward4
}
if(results$Called[i]>=input$nrcaller5){
artifact_score[i]<-artifact_score[i]+input$reward5
}
if(results$Called[i]>=input$nrcaller6){
artifact_score[i]<-artifact_score[i]+input$reward6
}
if(results$Called[i]==1){
artifact_score[i]<-artifact_score[i]+input$oneCaller
}
if(!is.na(results$BQ_ALT[i])&&
results$BQ_ALT[i]<(mean(results$BQ_ALT,na.rm=TRUE)-3*sd(results$BQ_ALT,na.rm=TRUE))){
artifact_score[i]<-artifact_score[i]+input$BQ_AltMean
}
if(!is.na(hotspot[i])){
artifact_score[i]<-artifact_score[i]+input$knownHotspot
}
temp<-frequency_calls[i,17:(length(frequency_calls[1,])-14)]
temp<-temp[,!is.na(temp)]
if(length(intersect(names(temp),input$overlapTools))==length(input$overlapTools)){
artifact_score[i]<-artifact_score[i]+input$overlapReward
}
if(artifact_score[i]>=input$artifactThreshold){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
}
progress_small$close()
#polymorphism score
progress$inc(1/13,detail="-> Perform final filtration")
poly_score<-rep(0,length(results[,1]))
cosmic_flag<-rep(FALSE,length(results[,1]))
progress_small <- shiny::Progress$new()
progress_small$set(message = "Calculate Polymorphism Score",
value = 0)
if(input$polymorphism_score=="No"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,
"out of",
length(results[,1])))
if(!is.na(results$nr_samples[i])&&
results$nr_samples[i]>nrsamples){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(results$nr_samples[i])&&
results$nr_samples[i]==1){
poly_score[i]<-poly_score[i]-1
}
if(!is.na(artifact_because[i,4])&&
artifact_because[i,4]>=2){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(artifact_because[i,4])&&
artifact_because[i,4]>=4){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(artifact_because[i,5])&&
artifact_because[i,5]>=2){
poly_score[i]<-poly_score[i]-1
}
if(is.na(artifact_because[i,4])){
poly_score[i]<-poly_score[i]-1
}
if(results$Called[i]>=6){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(results$Consequence[i])&&
vcountPattern(pattern="frameshift",
results$Consequence[i])>0&&
vcountPattern(pattern="*",
as.character(results$p.[i]),
fixed = TRUE)==0){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(artifact_because[i,7])&&
artifact_because[i,7]==1){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(results$Prediction[i])&&
(results$Prediction[i]=="Tolerated"||
results$Prediction[i]=="benign"||
results$Prediction[i]=="Neutral")&&
results$Score[i]>=limit_provean2){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(results$Score[i])&&!is.na(results$p.[i])&&
as.character(results$p.[i])!="NA"&&
(results$Score[i]<=limit_provean||
vcountPattern(pattern="*",
as.character(results$p.[i]),
fixed = TRUE)>0)){
poly_score[i]<-poly_score[i]-1
}
if(!is.na(results$Cosmic_Counts[i])&&
results$Cosmic_Counts[i]>100){
cosmic_flag[i]<-TRUE
}
if(is.na(hotspot[i])&&poly_score[i]>=2&&
cosmic_flag[i]==TRUE){
results$Category[i]<-paste(results$Category[i],
"Likely Polymorphism",
sep="")
}
if(is.na(hotspot[i])&&((poly_score[i]>=2&&
cosmic_flag[i]==FALSE)
||poly_score[i]>=3)){
results$Category[i]<-"Polymorphism"
}
}
}
if(input$polymorphism_score=="Yes"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,
"out of",
length(results[,1])))
if(!is.na(results$nr_samples[i])&&
results$nr_samples[i]>nrsamples){
poly_score[i]<-poly_score[i]+input$polyDetected
}
if(!is.na(results$nr_samples[i])&&
results$nr_samples[i]==1){
poly_score[i]<-poly_score[i]+input$polyDetectedOnce
}
if(!is.na(artifact_because[i,4])&&
artifact_because[i,4]>=input$polyDatabasesPolyLow){
poly_score[i]<-poly_score[i]+input$polyDatabasesPolyLowReward
}
if(!is.na(artifact_because[i,4])&&
artifact_because[i,4]>=input$polyDatabasesPolyHigh){
poly_score[i]<-poly_score[i]+input$polyDatabasesPolyHighReward
}
if(!is.na(artifact_because[i,5])&&
artifact_because[i,5]>=input$polyDatabasesMut){
poly_score[i]<-poly_score[i]+input$polyDatabasesMutReward
}
if(is.na(artifact_because[i,4])){
poly_score[i]<-poly_score[i]+input$polyNoDatabase
}
if(results$Called[i]>=input$polyDatabases){
poly_score[i]<-poly_score[i]+input$polyDatabasesReward
}
if(!is.na(results$Consequence[i])&&
vcountPattern(pattern="frameshift",
results$Consequence[i])>0&&
vcountPattern(pattern="*",
as.character(results$p.[i]),
fixed = TRUE)==0){
poly_score[i]<-poly_score[i]+input$polyEffect
}
if(!is.na(artifact_because[i,7])&&
artifact_because[i,7]==1){
poly_score[i]<-poly_score[i]+input$polyVAF
}
if(!is.na(results$Prediction[i])&&
(results$Prediction[i]=="Tolerated"||
results$Prediction[i]=="benign"||
results$Prediction[i]=="Neutral")&&
results$Score[i]>=limit_provean2){
poly_score[i]<-poly_score[i]+input$polyPrediction
}
if(!is.na(results$Score[i])&&
!is.na(results$p.[i])&&
as.character(results$p.[i])!="NA"&&
(results$Score[i]<=limit_provean||
vcountPattern(pattern="*",
as.character(results$p.[i]),
fixed = TRUE)>0)){
poly_score[i]<-poly_score[i]+input$polyPredictionEffect
}
if(!is.na(results$Cosmic_Counts[i])&&
results$Cosmic_Counts[i]>input$polyCosmic){
cosmic_flag[i]<-TRUE
}
if(is.na(hotspot[i])&&
poly_score[i]>=input$polyThresholdCritical&&
cosmic_flag[i]==TRUE){
results$Category[i]<-paste(results$Category[i],
"Likely Polymorphism",
sep="")
}
if(is.na(hotspot[i])&&
((poly_score[i]>=input$polyThresholdCritical&&
cosmic_flag[i]==FALSE)||
poly_score[i]>=input$polyThreshold)){
results$Category[i]<-"Polymorphism"
}
}
}
progress_small$close()
#corrections
progress$inc(1/13,detail="-> Perform final filtration")
progress_small <- shiny::Progress$new()
progress_small$set(message = "Correct Scores", value = 0)
if(input$artifact_score=="No"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,
"out of",
length(results[,1])))
if((poly_score[i]>=2&&cosmic_flag[i]==TRUE&&
is.na(hotspot[i]))||(is.na(hotspot[i])&&
((poly_score[i]>=2&&
cosmic_flag[i]==FALSE)||
poly_score[i]>=3))){
if(!is.na(results$VAF[i])&&
results$VAF[i]<=0.1){
artifact_score[i]<-artifact_score[i]+5
if(artifact_score[i]>-1){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
if(!is.na(results$VAF[i])&&
results$VAF[i]<=0.2){
artifact_score[i]<-artifact_score[i]+2
if(artifact_score[i]>-1){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
if(!is.na(results$Consequence[i])&&
vcountPattern(pattern="frameshift",
results$Consequence[i])>0){
artifact_score[i]<-artifact_score[i]+2
if(artifact_score[i]>-1){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
}
}
}
if(input$artifact_score=="Yes"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,
"out of",
length(results[,1])))
if((poly_score[i]>=2&&cosmic_flag[i]==TRUE&&
is.na(hotspot[i]))||(is.na(hotspot[i])&&
((poly_score[i]>=2&&
cosmic_flag[i]==FALSE)||
poly_score[i]>=3))){
if(!is.na(results$VAF[i])&&results$VAF[i]<=0.1){
artifact_score[i]<-artifact_score[i]+input$PolymorphismVAF10
if(artifact_score[i]>=input$artifactThreshold){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
if(!is.na(results$VAF[i])&&results$VAF[i]<=0.2){
artifact_score[i]<-artifact_score[i]+input$PolymorphismVAF20
if(artifact_score[i]>=input$artifactThreshold){
results$Category[i]<-paste("Artifact (",
artifact_score[i],")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
if(!is.na(results$Consequence[i])&&
vcountPattern(pattern="frameshift",
results$Consequence[i])>0){
artifact_score[i]<-artifact_score[i]+input$PolymorphismFrame
if(artifact_score[i]>=input$artifactThreshold){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
}
}
}
progress_small$close()
#identical calls as polymorphism
progress$inc(1/13,detail="-> Re-consider polymorphisms")
i<-1
while(i<=length(results[,1])){
subset<-results[i:(i+background_info[i]-1),]
if(sum(subset$Category=="Polymorphism",na.rm=TRUE)>=1){
for(j in i:(i+background_info[i]-1)){
if(!is.na(results$VAF[j])&&results$VAF[j]>0.2){
results$Category[j]<-"Polymorphism"
}
}
}
i<-i+background_info[i]
}
results.artifacts<-results[vcountPattern(results$Category,pattern="Artifact")>0 | is.na(results$VAF) | (results$DP-results$Nr_Ref)<nr_alt,]
results.polymorphisms<-results[vcountPattern(results$Category,pattern="Polymorphism")>0 & !is.na(results$VAF) & (results$DP-results$Nr_Ref)>=nr_alt,]
results.mutations<-results[(vcountPattern(results$Category,pattern="True")>0 | vcountPattern(results$Category,pattern="Hotspot")>0) & !is.na(results$VAF) & (results$DP-results$Nr_Ref)>=nr_alt,]
if(exists("overview4")==TRUE){
overview4<-cbind(overview4,Mutations=NA,
Polymorphisms=NA,Artifacts=NA)
}
if(exists("overview4")==FALSE){
overview4<-cbind(checkpointFile[,1],RawCalls=NA,
VAFandBQFiltered=NA,Mutations=NA,
Polymorphisms=NA,Artifacts=NA)
}
for(i in seq_along(overview4[,1])){
overview4[i,4]<-length(results.mutations[results.mutations[,1]==overview4[i,1],1])
overview4[i,5]<-length(results.polymorphisms[results.polymorphisms[,1]==overview4[i,1],1])
overview4[i,6]<-length(results.artifacts[results.artifacts[,1]==overview4[i,1],1])
for(j in 2:length(checkpoint[1,])){
if(!is.na(checkpoint[i,j])){
checkpoint[i,j]<-7
}
}
}
write.table(results,
paste(input$output_folder,"/Results_Final.txt",
sep=""),row.names=FALSE,quote=FALSE,
sep="\t")
write.table(checkpoint,
paste(input$output_folder,"/checkpoint.txt",
sep=""),row.names=FALSE,quote=FALSE,
sep="\t")
output$table4 <- renderDataTable(datatable(overview4))
output$table_mutations <- renderDataTable(datatable(results.mutations))
output$table_polymorphisms <- renderDataTable(datatable(results.polymorphisms))
output$table_artifacts <- renderDataTable(datatable(results.artifacts))
results.workbook <- createWorkbook()
addWorksheet(wb=results.workbook,sheetName="Mutations")
addWorksheet(wb=results.workbook,sheetName="Polymorphisms")
addWorksheet(wb=results.workbook,sheetName="Artifacts")
writeData(wb=results.workbook,x=results.mutations,
sheet="Mutations")
writeData(wb=results.workbook,x=results.polymorphisms,
sheet="Polymorphisms")
writeData(wb=results.workbook,x=results.artifacts,
sheet="Artifacts")
saveWorkbook(results.workbook,
paste(input$output_folder,
"/Results_Final.xlsx",sep=""),
overwrite = TRUE)
checkpoint_state<-7
progress$close()
}
#7: After Final Filtration
if(checkpoint_state==7){
#1. Reading Input
log_info<-c(log_info,"You are done <br>")
output$log_info<-renderUI({HTML(log_info)})
if(exists("results.artifacts")==FALSE){
results.artifacts<-read.xlsx(paste(input$output_folder,
"/Results_Final.xlsx",
sep=""),
sheet="Artifacts")
results.polymorphisms<-read.xlsx(paste(input$output_folder,
"/Results_Final.xlsx",
sep=""),
sheet="Polymorphisms")
results.mutations<-read.xlsx(paste(input$output_folder,"
/Results_Final.xlsx",
sep=""),
sheet="Mutations")
overview4<-cbind(checkpointFile[,1],RawCalls=NA,
VAFandBQFiltered=NA,Mutations=NA,
Polymorphisms=NA,Artifacts=NA)
for(i in seq_along(overview4[,1])){
overview4[i,4]<-length(results.mutations[results.mutations[,1]==overview4[i,1],1])
overview4[i,5]<-length(results.polymorphisms[results.polymorphisms[,1]==overview4[i,1],1])
overview4[i,6]<-length(results.artifacts[results.artifacts[,1]==overview4[i,1],1])
for(j in 2:length(checkpoint[1,])){
if(!is.na(checkpoint[i,j])){
checkpoint[i,j]<-7
}
}
}
output$table4 <- renderDataTable(datatable(overview4))
output$table_mutations <- renderDataTable(datatable(results.mutations))
output$table_polymorphisms <- renderDataTable(datatable(results.polymorphisms))
output$table_artifacts <- renderDataTable(datatable(results.artifacts))
}
}
})
}
)
}
sandmanns/appreci8R documentation built on Dec. 7, 2020, 12:32 a.m.
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions appreci8Rshiny
Documented in appreci8Rshiny
#Open appreci8R GUI
appreci8Rshiny <- function() {
shinyApp(
ui=shinyUI(navbarPage("appreci8R",
tabPanel("Analysis",
fluidRow(
wellPanel(
navbarPage(
title='',
tabPanel("Important notes",
h4("Important notes:"),
h5("Please make sure that all your files containing variant calling results as well as the corresponding
bam- and bai files start with the sample name (e.g. Sample1.vcf, Sample2_rawCalls.txt or Sample3.bam)."),
h5("Currently, the analysis is just available for variant calling results, target regions and bam files
using \'1\', \'2\' etc. and not \'chr1\', \'chr2\'."),
h5("Currently, the analysis is just available for hg19/GRCh37.")),
tabPanel("0. Preparations",
h3("0. Preparations:"),
uiOutput("output_folderUI"),
hr(),
h3("Variant Caller Input (appreci8R):"),
h4("GATK:"),
actionButton("gatk_add","Add"),
actionButton("gatk_remove","Remove"),
hr(),
uiOutput("gatkUI1"),
uiOutput("gatkUI2"),
uiOutput("gatkUI3"),
uiOutput("gatkUI4"),
uiOutput("gatkUI5"),
uiOutput("gatkUI6"),
uiOutput("gatkUI7"),
uiOutput("gatkUI8"),
h4("Platypus:"),
actionButton("platypus_add","Add"),
actionButton("platypus_remove","Remove"),
hr(),
uiOutput("platypusUI1"),
uiOutput("platypusUI2"),
uiOutput("platypusUI3"),
uiOutput("platypusUI4"),
uiOutput("platypusUI5"),
uiOutput("platypusUI6"),
uiOutput("platypusUI7"),
uiOutput("platypusUI8"),
h4("VarScan:"),
actionButton("varscan_add","Add"),
actionButton("varscan_remove","Remove"),
hr(),
uiOutput("varscanUI1"),
uiOutput("varscanUI2"),
uiOutput("varscanUI3"),
uiOutput("varscanUI4"),
uiOutput("varscanUI5"),
uiOutput("varscanUI6"),
uiOutput("varscanUI7"),
uiOutput("varscanUI8"),
h4("FreeBayes:"),
actionButton("freebayes_add","Add"),
actionButton("freebayes_remove","Remove"),
hr(),
uiOutput("freebayesUI1"),
uiOutput("freebayesUI2"),
uiOutput("freebayesUI3"),
uiOutput("freebayesUI4"),
uiOutput("freebayesUI5"),
uiOutput("freebayesUI6"),
uiOutput("freebayesUI7"),
uiOutput("freebayesUI8"),
h4("LoFreq:"),
actionButton("lofreq_add","Add"),
actionButton("lofreq_remove","Remove"),
hr(),
uiOutput("lofreqUI1"),
uiOutput("lofreqUI2"),
uiOutput("lofreqUI3"),
uiOutput("lofreqUI4"),
uiOutput("lofreqUI5"),
uiOutput("lofreqUI6"),
uiOutput("lofreqUI7"),
uiOutput("lofreqUI8"),
h4("SNVer:"),
actionButton("snver_add","Add"),
actionButton("snver_remove","Remove"),
hr(),
uiOutput("snverUI1"),
uiOutput("snverUI2"),
uiOutput("snverUI3"),
uiOutput("snverUI4"),
uiOutput("snverUI5"),
uiOutput("snverUI6"),
uiOutput("snverUI7"),
uiOutput("snverUI8"),
h4("SamTools:"),
actionButton("samtools_add","Add"),
actionButton("samtools_remove","Remove"),
hr(),
uiOutput("samtoolsUI1"),
uiOutput("samtoolsUI2"),
uiOutput("samtoolsUI3"),
uiOutput("samtoolsUI4"),
uiOutput("samtoolsUI5"),
uiOutput("samtoolsUI6"),
uiOutput("samtoolsUI7"),
uiOutput("samtoolsUI8"),
h4("VarDict:"),
actionButton("vardict_add","Add"),
actionButton("vardict_remove","Remove"),
hr(),
uiOutput("vardictUI1"),
uiOutput("vardictUI2"),
uiOutput("vardictUI3"),
uiOutput("vardictUI4"),
uiOutput("vardictUI5"),
uiOutput("vardictUI6"),
uiOutput("vardictUI7"),
uiOutput("vardictUI8"),
numericInput('nr_additional',"How many additional callers would you like to add? (max 5)",value=0,min=0,max=5),
actionButton("nr_additional_action","Go"),
hr(),
uiOutput("caller1UI0"),
uiOutput("caller1UI0.1"),
uiOutput("caller1UI1"),
uiOutput("caller1UI2"),
uiOutput("caller1UI3"),
uiOutput("caller1UI4"),
uiOutput("caller1UI5"),
uiOutput("caller1UI6"),
uiOutput("caller1UI7"),
uiOutput("caller1UI8"),
uiOutput("caller2UI0"),
uiOutput("caller2UI0.1"),
uiOutput("caller2UI1"),
uiOutput("caller2UI2"),
uiOutput("caller2UI3"),
uiOutput("caller2UI4"),
uiOutput("caller2UI5"),
uiOutput("caller2UI6"),
uiOutput("caller2UI7"),
uiOutput("caller2UI8"),
uiOutput("caller3UI0"),
uiOutput("caller3UI0.1"),
uiOutput("caller3UI1"),
uiOutput("caller3UI2"),
uiOutput("caller3UI3"),
uiOutput("caller3UI4"),
uiOutput("caller3UI5"),
uiOutput("caller3UI6"),
uiOutput("caller3UI7"),
uiOutput("caller3UI8"),
uiOutput("caller4UI0"),
uiOutput("caller4UI0.1"),
uiOutput("caller4UI1"),
uiOutput("caller4UI2"),
uiOutput("caller4UI3"),
uiOutput("caller4UI4"),
uiOutput("caller4UI5"),
uiOutput("caller4UI6"),
uiOutput("caller4UI7"),
uiOutput("caller4UI8"),
uiOutput("caller5UI0"),
uiOutput("caller5UI0.1"),
uiOutput("caller5UI1"),
uiOutput("caller5UI2"),
uiOutput("caller5UI3"),
uiOutput("caller5UI4"),
uiOutput("caller5UI5"),
uiOutput("caller5UI6"),
uiOutput("caller5UI7"),
uiOutput("caller5UI8"),
hr()),
tabPanel("1. Target filtration",
h3("1. Target filtration:"),
fileInput('targetRegions', 'Upload your target region (*.bed)'),
hr()),
tabPanel("2. Normalization",
h3("2. Normalization"),
hr()),
tabPanel("3. Annotation",
h3("3. Annotation:"),
h4("Important note:"),
h5("Currently, only UCSC is available."),
uiOutput("locationsUI"),
uiOutput("consequencesUI"),
hr()),
tabPanel("4. Combine output",
h3("4. Combine output"),
hr()),
tabPanel("5. Evaluate Coverage and BQ",
h3("5. Evaluate Coverage and BQ:"),
uiOutput("bam_folderUI"),
uiOutput("dpUI"),
uiOutput("nr_altUI"),
uiOutput("vafUI"),
uiOutput("bqUI"),
uiOutput("bq_diffUI"),
hr()),
tabPanel("6. Extended Set of Characteristics",
h3("6. Extended Set of Characteristics:"),
h4("What databases would you like to query?"),
uiOutput("dbSNPUI"),
uiOutput("1kgenomesUI"),
uiOutput("exacUI"),
uiOutput("gadUI"),
uiOutput("cosmicUI"),
uiOutput("clinvarUI"),
uiOutput("predictUI"),
hr()),
tabPanel("7. Final Filtration",
h3("7. Final Filtration:"),
fileInput('primerPositions', 'Optional: Upload your primer positions (*.bed)'),
fileInput('hotspots', 'Optional: Upload your hotspot list (*.txt)'),
h5("Please make sure your hotspot list has the following format:"),
h5("3 tab-seperated columns (with header)"),
h5(" 1. Gene (e.g. ASXL1)"),
h5(" 2. Mutation (e.g. V617F or G646fs or R420* or I836ins or P95_R102del or G12)"),
h5(" 3. Minimum expected frequency for that mutation (e.g. 0.1 or NA)"),
uiOutput("stricter_thresholdsUI"),
uiOutput("stricter_thresholdsUI2"),
uiOutput("nr_samplesUI"),
uiOutput("predictionUI1"),
uiOutput("predictionUI2"),
uiOutput("predictionUI3"),
uiOutput("artifact_scoreUI"),
uiOutput("artifact_scoreUI2"),
uiOutput("polymorphism_scoreUI"),
uiOutput("polymorphism_scoreUI2")),
tabPanel("Action",
actionButton("appreci8R", "Start complete analysis"),
actionButton("checkpointCheck","Check for possible checkpoints"),
actionButton("exportConfig","Export current configuration"),
actionButton("importConfig","Import configuration"),
actionButton("done","Done"),
hr(),
uiOutput("checkpointUI1"),
uiOutput("checkpointUI2"),
hr(),
uiOutput("exportconfigUI0"),
uiOutput("exportconfigUI0.1"),
hr(),
uiOutput("exportconfigUI1"),
uiOutput("exportconfigUI2"),
hr(),
uiOutput("messageUI1"),
hr(),
uiOutput("importconfigUI0"),
uiOutput("importconfigUI0.1"),
hr(),
uiOutput("importconfigUI1"),
uiOutput("importconfigUI2"),
hr(),
uiOutput("messageUI2")
))))),
tabPanel("Overview results",
wellPanel(
navbarPage(
title='',
tabPanel("Log",
htmlOutput("log_info")),
tabPanel("Raw Calls",
DT::dataTableOutput('table')),
tabPanel("Calls On Target",
DT::dataTableOutput('table2')),
tabPanel("Annotated Calls",
DT::dataTableOutput('table3')),
tabPanel("Filtered Calls",
DT::dataTableOutput('table4'))
)
)
),
tabPanel("Detailed results",
wellPanel(
navbarPage(
title='',
tabPanel("Mutations",
DT::dataTableOutput('table_mutations')),
tabPanel("Polymorphisms",
DT::dataTableOutput('table_polymorphisms')),
tabPanel("Artifacts",
DT::dataTableOutput('table_artifacts'))
)
)
)
)),
server = function(input, output) {
observeEvent(input$done,{
stopApp()
})
observeEvent(input$gatk_add,{
output$gatkUI1<-renderUI({textInput('gatk_folder',
'Variant calling results',
"/home/gatk/")})
output$gatkUI2<-renderUI({radioButtons('gatk_file_type',
"Output file type",
c(".vcf",".txt"),".vcf",
inline=TRUE)})
output$gatkUI3<-renderUI({
conditionalPanel(
condition="input.gatk_file_type=='.txt'",
numericInput('gatk_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('gatk_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('gatk_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('gatk_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$gatkUI4<-renderUI({textInput('gatk_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',".rawMutations")})
output$gatkUI5<-renderUI({radioButtons('gatk_mnvs',
'MNVs reported?',
c("Yes","No"),"No",
inline = TRUE)})
output$gatkUI6<-renderUI({radioButtons('gatk_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),"Yes",
inline = TRUE)})
output$gatkUI7<-renderUI({conditionalPanel(
condition="input.gatk_snv_indel=='No'",
textInput('gatk_snv_names_add','Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',""),
textInput('gatk_indel_names_add','Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',""))})
output$gatkUI8<-renderUI({radioButtons('gatk_indels',
'How are Indels reported?',
c("CA>C","C>-A","CAAAC>CAAC"),
selected="CA>C",
inline = TRUE)})
})
observeEvent(input$gatk_remove,{
output$gatkUI1<-renderUI({NULL})
output$gatkUI2<-renderUI({NULL})
output$gatkUI3<-renderUI({NULL})
output$gatkUI4<-renderUI({NULL})
output$gatkUI5<-renderUI({NULL})
output$gatkUI6<-renderUI({NULL})
output$gatkUI7<-renderUI({NULL})
output$gatkUI8<-renderUI({NULL})
})
observeEvent(input$platypus_add,{
output$platypusUI1<-renderUI({textInput('platypus_folder',
'Variant calling results',
"/home/platypus/")})
output$platypusUI2<-renderUI({radioButtons('platypus_file_type',
"Output file type",
c(".vcf",".txt"),
".vcf",inline=TRUE)})
output$platypusUI3<-renderUI({
conditionalPanel(
condition="input.platypus_file_type=='.txt'",
numericInput('platypus_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('platypus_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('platypus_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('platypus_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$platypusUI4<-renderUI({textInput('platypus_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$platypusUI5<-renderUI({radioButtons('platypus_mnvs',
'MNVs reported?',
c("Yes","No"),"No",
inline = TRUE)})
output$platypusUI6<-renderUI({radioButtons('platypus_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),"Yes",
inline = TRUE)})
output$platypusUI7<-renderUI({conditionalPanel(
condition="input.platypus_snv_indel=='No'",
textInput('platypus_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',""),
textInput('platypus_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',""))})
output$platypusUI8<-renderUI({radioButtons('platypus_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
"CA>C",
inline = TRUE)})
})
observeEvent(input$platypus_remove,{
output$platypusUI1<-renderUI({NULL})
output$platypusUI2<-renderUI({NULL})
output$platypusUI3<-renderUI({NULL})
output$platypusUI4<-renderUI({NULL})
output$platypusUI5<-renderUI({NULL})
output$platypusUI6<-renderUI({NULL})
output$platypusUI7<-renderUI({NULL})
output$platypusUI8<-renderUI({NULL})
})
observeEvent(input$varscan_add,{
output$varscanUI1<-renderUI({textInput('varscan_folder',
'Variant calling results',
"/home/varscan/")})
output$varscanUI2<-renderUI({radioButtons('varscan_file_type',
"Output file type",
c(".vcf",".txt"),
".txt",inline=TRUE)})
output$varscanUI3<-renderUI({
conditionalPanel(
condition="input.varscan_file_type=='.txt'",
numericInput('varscan_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('varscan_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('varscan_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('varscan_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$varscanUI4<-renderUI({textInput('varscan_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$varscanUI5<-renderUI({radioButtons('varscan_mnvs',
'MNVs reported?',
c("Yes","No"),"No",
inline = TRUE)})
output$varscanUI6<-renderUI({radioButtons('varscan_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),"No",
inline = TRUE)})
output$varscanUI7<-renderUI({conditionalPanel(
condition="input.varscan_snv_indel=='No'",
textInput('varscan_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
"_snvs"),
textInput('varscan_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
"_indels"))})
output$varscanUI8<-renderUI({radioButtons('varscan_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected="C>-A",
inline = TRUE)})
})
observeEvent(input$varscan_remove,{
output$varscanUI1<-renderUI({NULL})
output$varscanUI2<-renderUI({NULL})
output$varscanUI3<-renderUI({NULL})
output$varscanUI4<-renderUI({NULL})
output$varscanUI5<-renderUI({NULL})
output$varscanUI6<-renderUI({NULL})
output$varscanUI7<-renderUI({NULL})
output$varscanUI8<-renderUI({NULL})
})
observeEvent(input$freebayes_add,{
output$freebayesUI1<-renderUI({textInput('freebayes_folder',
'Variant calling results',
"/home/freebayes/")})
output$freebayesUI2<-renderUI({radioButtons('freebayes_file_type',
"Output file type",
c(".vcf",".txt"),
".vcf",inline=TRUE)})
output$freebayesUI3<-renderUI({
conditionalPanel(
condition="input.freebayes_file_type=='.txt'",
numericInput('freebayes_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('freebayes_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('freebayes_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('freebayes_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$freebayesUI4<-renderUI({textInput('freebayes_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$freebayesUI5<-renderUI({radioButtons('freebayes_mnvs',
'MNVs reported?',
c("Yes","No"),"Yes",
inline = TRUE)})
output$freebayesUI6<-renderUI({radioButtons('freebayes_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),"Yes",
inline = TRUE)})
output$freebayesUI7<-renderUI({conditionalPanel(
condition="input.freebayes_snv_indel=='No'",
textInput('freebayes_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',""),
textInput('freebayes_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',""))})
output$freebayesUI8<-renderUI({radioButtons('freebayes_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected="CAAAC>CAAC",
inline = TRUE)})
})
observeEvent(input$freebayes_remove,{
output$freebayesUI1<-renderUI({NULL})
output$freebayesUI2<-renderUI({NULL})
output$freebayesUI3<-renderUI({NULL})
output$freebayesUI4<-renderUI({NULL})
output$freebayesUI5<-renderUI({NULL})
output$freebayesUI6<-renderUI({NULL})
output$freebayesUI7<-renderUI({NULL})
output$freebayesUI8<-renderUI({NULL})
})
observeEvent(input$lofreq_add,{
output$lofreqUI1<-renderUI({textInput('lofreq_folder',
'Variant calling results',
"/home/lofreq/")})
output$lofreqUI2<-renderUI({radioButtons('lofreq_file_type',
"Output file type",
c(".vcf",".txt"),
".vcf",inline=TRUE)})
output$lofreqUI3<-renderUI({
conditionalPanel(
condition="input.lofreq_file_type=='.txt'",
numericInput('lofreq_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('lofreq_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('lofreq_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('lofreq_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$lofreqUI4<-renderUI({textInput('lofreq_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$lofreqUI5<-renderUI({radioButtons('lofreq_mnvs',
'MNVs reported?',
c("Yes","No"),"No",
inline = TRUE)})
output$lofreqUI6<-renderUI({radioButtons('lofreq_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),"Yes",
inline = TRUE)})
output$lofreqUI7<-renderUI({conditionalPanel(
condition="input.lofreq_snv_indel=='No'",
textInput('lofreq_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
""),
textInput('lofreq_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
""))})
output$lofreqUI8<-renderUI({radioButtons('lofreq_indels',
'How are Indels reported?',
c("CA>C","C>-A","CAAAC>CAAC"),
selected="CA>C",
inline = TRUE)})
})
observeEvent(input$lofreq_remove,{
output$lofreqUI1<-renderUI({NULL})
output$lofreqUI2<-renderUI({NULL})
output$lofreqUI3<-renderUI({NULL})
output$lofreqUI4<-renderUI({NULL})
output$lofreqUI5<-renderUI({NULL})
output$lofreqUI6<-renderUI({NULL})
output$lofreqUI7<-renderUI({NULL})
output$lofreqUI8<-renderUI({NULL})
})
observeEvent(input$snver_add,{
output$snverUI1<-renderUI({textInput('snver_folder',
'Variant calling results',
"/home/snver/")})
output$snverUI2<-renderUI({radioButtons('snver_file_type',
"Output file type",
c(".vcf",".txt"),".vcf",
inline=TRUE)})
output$snverUI3<-renderUI({
conditionalPanel(
condition="input.snver_file_type=='.txt'",
numericInput('snver_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('snver_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('snver_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('snver_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$snverUI4<-renderUI({textInput('snver_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$snverUI5<-renderUI({radioButtons('snver_mnvs',
'MNVs reported?',
c("Yes","No"),"No",
inline = TRUE)})
output$snverUI6<-renderUI({radioButtons('snver_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),"No",
inline = TRUE)})
output$snverUI7<-renderUI({conditionalPanel(
condition="input.snver_snv_indel=='No'",
textInput('snver_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
".snv.filter"),
textInput('snver_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
".indel.filter"))})
output$snverUI8<-renderUI({radioButtons('snver_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected="CA>C",
inline = TRUE)})
})
observeEvent(input$snver_remove,{
output$snverUI1<-renderUI({NULL})
output$snverUI2<-renderUI({NULL})
output$snverUI3<-renderUI({NULL})
output$snverUI4<-renderUI({NULL})
output$snverUI5<-renderUI({NULL})
output$snverUI6<-renderUI({NULL})
output$snverUI7<-renderUI({NULL})
output$snverUI8<-renderUI({NULL})
})
observeEvent(input$samtools_add,{
output$samtoolsUI1<-renderUI({textInput('samtools_folder',
'Variant calling results',
"/home/samtools/")})
output$samtoolsUI2<-renderUI({radioButtons('samtools_file_type',
"Output file type",
c(".vcf",".txt"),
".vcf",
inline=TRUE)})
output$samtoolsUI3<-renderUI({
conditionalPanel(
condition="input.samtools_file_type=='.txt'",
numericInput('samtools_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('samtools_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('samtools_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('samtools_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$samtoolsUI4<-renderUI({textInput('samtools_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$samtoolsUI5<-renderUI({radioButtons('samtools_mnvs',
'MNVs reported?',
c("Yes","No"),"No",
inline = TRUE)})
output$samtoolsUI6<-renderUI({radioButtons('samtools_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),"Yes",
inline = TRUE)})
output$samtoolsUI7<-renderUI({conditionalPanel(
condition="input.samtools_snv_indel=='No'",
textInput('samtools_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
""),
textInput('samtools_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
""))})
output$samtoolsUI8<-renderUI({radioButtons('samtools_indels',
'How are Indels reported?',
c("CA>C","C>-A","CAAAC>CAAC"),
selected="CAAAC>CAAC",
inline = TRUE)})
})
observeEvent(input$samtools_remove,{
output$samtoolsUI1<-renderUI({NULL})
output$samtoolsUI2<-renderUI({NULL})
output$samtoolsUI3<-renderUI({NULL})
output$samtoolsUI4<-renderUI({NULL})
output$samtoolsUI5<-renderUI({NULL})
output$samtoolsUI6<-renderUI({NULL})
output$samtoolsUI7<-renderUI({NULL})
output$samtoolsUI8<-renderUI({NULL})
})
observeEvent(input$vardict_add,{
output$vardictUI1<-renderUI({textInput('vardict_folder',
'Variant calling results',
"/home/vardict/")})
output$vardictUI2<-renderUI({radioButtons('vardict_file_type',
"Output file type",
c(".vcf",".txt"),
".txt",inline=TRUE)})
output$vardictUI3<-renderUI({
conditionalPanel(
condition="input.vardict_file_type=='.txt'",
numericInput('vardict_chr',
"In which column do you find Chr?",
min = 1,max=20,value=3),
numericInput('vardict_pos',
"In which column do you find Pos?",
min = 1,max=20,value=4),
numericInput('vardict_ref',
"In which column do you find Ref?",
min = 1,max=20,value=6),
numericInput('vardict_alt',
"In which column do you find Alt?",
min = 1,max=20,value=7))})
output$vardictUI4<-renderUI({textInput('vardict_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$vardictUI5<-renderUI({radioButtons('vardict_mnvs',
'MNVs reported?',
c("Yes","No"),"Yes",
inline = TRUE)})
output$vardictUI6<-renderUI({radioButtons('vardict_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),"Yes",
inline = TRUE)})
output$vardictUI7<-renderUI({conditionalPanel(
condition="input.vardict_snv_indel=='No'",
textInput('vardict_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
""),
textInput('vardict_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
""))})
output$vardictUI8<-renderUI({radioButtons('vardict_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected="CA>C",
inline = TRUE)})
})
observeEvent(input$vardict_remove,{
output$vardictUI1<-renderUI({NULL})
output$vardictUI2<-renderUI({NULL})
output$vardictUI3<-renderUI({NULL})
output$vardictUI4<-renderUI({NULL})
output$vardictUI5<-renderUI({NULL})
output$vardictUI6<-renderUI({NULL})
output$vardictUI7<-renderUI({NULL})
output$vardictUI8<-renderUI({NULL})
})
observeEvent(input$nr_additional_action,{
output$caller1UI0<-renderUI({NULL})
output$caller1UI0.1<-renderUI({NULL})
output$caller1UI1<-renderUI({NULL})
output$caller1UI2<-renderUI({NULL})
output$caller1UI3<-renderUI({NULL})
output$caller1UI4<-renderUI({NULL})
output$caller1UI5<-renderUI({NULL})
output$caller1UI6<-renderUI({NULL})
output$caller1UI7<-renderUI({NULL})
output$caller1UI8<-renderUI({NULL})
output$caller2UI0<-renderUI({NULL})
output$caller2UI0.1<-renderUI({NULL})
output$caller2UI1<-renderUI({NULL})
output$caller2UI2<-renderUI({NULL})
output$caller2UI3<-renderUI({NULL})
output$caller2UI4<-renderUI({NULL})
output$caller2UI5<-renderUI({NULL})
output$caller2UI6<-renderUI({NULL})
output$caller2UI7<-renderUI({NULL})
output$caller2UI8<-renderUI({NULL})
output$caller3UI0<-renderUI({NULL})
output$caller3UI0.1<-renderUI({NULL})
output$caller3UI1<-renderUI({NULL})
output$caller3UI2<-renderUI({NULL})
output$caller3UI3<-renderUI({NULL})
output$caller3UI4<-renderUI({NULL})
output$caller3UI5<-renderUI({NULL})
output$caller3UI6<-renderUI({NULL})
output$caller3UI7<-renderUI({NULL})
output$caller3UI8<-renderUI({NULL})
output$caller4UI0<-renderUI({NULL})
output$caller4UI0.1<-renderUI({NULL})
output$caller4UI1<-renderUI({NULL})
output$caller4UI2<-renderUI({NULL})
output$caller4UI3<-renderUI({NULL})
output$caller4UI4<-renderUI({NULL})
output$caller4UI5<-renderUI({NULL})
output$caller4UI6<-renderUI({NULL})
output$caller4UI7<-renderUI({NULL})
output$caller4UI8<-renderUI({NULL})
output$caller5UI0<-renderUI({NULL})
output$caller5UI0.1<-renderUI({NULL})
output$caller5UI1<-renderUI({NULL})
output$caller5UI2<-renderUI({NULL})
output$caller5UI3<-renderUI({NULL})
output$caller5UI4<-renderUI({NULL})
output$caller5UI5<-renderUI({NULL})
output$caller5UI6<-renderUI({NULL})
output$caller5UI7<-renderUI({NULL})
output$caller5UI8<-renderUI({NULL})
if(input$nr_additional>0){
output$caller1UI0<-renderUI({h4("Caller 1:")})
output$caller1UI0.1<-renderUI({textInput('caller1_name',
'Name of caller 1',
"Caller 1")})
output$caller1UI1<-renderUI({textInput('caller1_folder',
'Variant calling results',
"/home/")})
output$caller1UI2<-renderUI({radioButtons('caller1_file_type',
"Output file type",
c(".vcf",".txt"),
".vcf",
inline=TRUE)})
output$caller1UI3<-renderUI({
conditionalPanel(
condition="input.caller1_file_type=='.txt'",
numericInput('caller1_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('caller1_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('caller1_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('caller1_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$caller1UI4<-renderUI({textInput('caller1_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
"")})
output$caller1UI5<-renderUI({radioButtons('caller1_mnvs',
'MNVs reported?',
c("Yes","No"),
"No",
inline = TRUE)})
output$caller1UI6<-renderUI({radioButtons('caller1_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
"Yes",
inline = TRUE)})
output$caller1UI7<-renderUI({conditionalPanel(
condition="input.caller1_snv_indel=='No'",
textInput('caller1_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
""),
textInput('caller1_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
""))})
output$caller1UI8<-renderUI({radioButtons('caller1_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected="CA>C",
inline = TRUE)})
if(input$nr_additional>1){
output$caller2UI0<-renderUI({h4("Caller 2:")})
output$caller2UI0.1<-renderUI({textInput('caller2_name',
'Name of caller 2',
"Caller 2")})
output$caller2UI1<-renderUI({textInput('caller2_folder',
'Variant calling results',
"/home/")})
output$caller2UI2<-renderUI({radioButtons('caller2_file_type',
"Output file type",
c(".vcf",
".txt"),
".vcf",
inline=TRUE)})
output$caller2UI3<-renderUI({
conditionalPanel(
condition="input.caller2_file_type=='.txt'",
numericInput('caller2_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('caller2_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('caller2_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('caller2_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$caller2UI4<-renderUI({textInput('caller2_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$caller2UI5<-renderUI({radioButtons('caller2_mnvs',
'MNVs reported?',
c("Yes","No"),
"No",
inline=TRUE)})
output$caller2UI6<-renderUI({radioButtons('caller2_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
"Yes",
inline=TRUE)})
output$caller2UI7<-renderUI({conditionalPanel(
condition="input.caller2_snv_indel=='No'",
textInput('caller2_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
""),
textInput('caller2_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
""))})
output$caller2UI8<-renderUI({radioButtons('caller2_indels',
'How are Indels reported?',
c("CA>C",
"C>-A",
"CAAAC>CAAC"),
selected="CA>C",
inline=TRUE)})
if(input$nr_additional>2){
output$caller3UI0<-renderUI({h4("Caller 3:")})
output$caller3UI0.1<-renderUI({textInput('caller3_name',
'Name of caller 3',
"Caller 3")})
output$caller3UI1<-renderUI({textInput('caller3_folder',
'Variant calling results',
"/home/")})
output$caller3UI2<-renderUI({radioButtons('caller3_file_type',
"Output file type",
c(".vcf",
".txt"),
".vcf",
inline=TRUE)})
output$caller3UI3<-renderUI({
conditionalPanel(
condition="input.caller3_file_type=='.txt'",
numericInput('caller3_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('caller3_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('caller3_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('caller3_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$caller3UI4<-renderUI({textInput('caller3_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$caller3UI5<-renderUI({radioButtons('caller3_mnvs',
'MNVs reported?',
c("Yes","No"),
"No",
inline = TRUE)})
output$caller3UI6<-renderUI({radioButtons('caller3_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
"Yes",
inline = TRUE)})
output$caller3UI7<-renderUI({conditionalPanel(
condition="input.caller3_snv_indel=='No'",
textInput('caller3_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
""),
textInput('caller3_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
""))})
output$caller3UI8<-renderUI({radioButtons('caller3_indels',
'How are Indels reported?',
c("CA>C","C>-A","CAAAC>CAAC"),
selected="CA>C",
inline = TRUE)})
if(input$nr_additional>3){
output$caller4UI0<-renderUI({h4("Caller 4:")})
output$caller4UI0.1<-renderUI({textInput('caller4_name',
'Name of caller 4',
"Caller 4")})
output$caller4UI1<-renderUI({textInput('caller4_folder',
'Variant calling results',
"/home/")})
output$caller4UI2<-renderUI({radioButtons('caller4_file_type',
"Output file type",
c(".vcf",".txt"),
".vcf",
inline=TRUE)})
output$caller4UI3<-renderUI({
conditionalPanel(
condition="input.caller4_file_type=='.txt'",
numericInput('caller4_chr',
"In which column do you find Chr?",
min = 1,max=20,value=1),
numericInput('caller4_pos',
"In which column do you find Pos?",
min = 1,max=20,value=2),
numericInput('caller4_ref',
"In which column do you find Ref?",
min = 1,max=20,value=3),
numericInput('caller4_alt',
"In which column do you find Alt?",
min = 1,max=20,value=4))})
output$caller4UI4<-renderUI({textInput('caller4_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$caller4UI5<-renderUI({radioButtons('caller4_mnvs',
'MNVs reported?',
c("Yes","No"),
"No",
inline=TRUE)})
output$caller4UI6<-renderUI({radioButtons('caller4_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
"Yes",
inline=TRUE)})
output$caller4UI7<-renderUI({conditionalPanel(
condition="input.caller4_snv_indel=='No'",
textInput('caller4_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',""),
textInput('caller4_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',""))})
output$caller4UI8<-renderUI({radioButtons('caller4_indels',
'How are Indels reported?',
c("CA>C","C>-A","CAAAC>CAAC"),
selected="CA>C",
inline=TRUE)})
if(input$nr_additional>4){
output$caller5UI0<-renderUI({h4("Caller 5:")})
output$caller5UI0.1<-renderUI({textInput('caller5_name',
'Name of caller 5',
"Caller 5")})
output$caller5UI1<-renderUI({textInput('caller5_folder',
'Variant calling results',
"/home/")})
output$caller5UI2<-renderUI({radioButtons('caller5_file_type',
"Output file type",
c(".vcf",".txt"),
".vcf",
inline=TRUE)})
output$caller5UI3<-renderUI({
conditionalPanel(
condition="input.caller5_file_type=='.txt'",
numericInput('caller5_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=1),
numericInput('caller5_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=2),
numericInput('caller5_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=3),
numericInput('caller5_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=4))})
output$caller5UI4<-renderUI({textInput('caller5_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',"")})
output$caller5UI5<-renderUI({radioButtons('caller5_mnvs',
'MNVs reported?',
c("Yes","No"),
"No",
inline=TRUE)})
output$caller5UI6<-renderUI({radioButtons('caller5_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
"Yes",
inline=TRUE)})
output$caller5UI7<-renderUI({conditionalPanel(
condition="input.caller5_snv_indel=='No'",
textInput('caller5_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
""),
textInput('caller5_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
""))})
output$caller5UI8<-renderUI({radioButtons('caller5_indels',
'How are Indels reported?',
c("CA>C","C>-A","CAAAC>CAAC"),
selected="CA>C",
inline=TRUE)})
}
}
}
}
}
})
observeEvent(input$checkpointCheck,{
output$messageUI1<-renderUI({NULL})
output$messageUI2<-renderUI({NULL})
if(file.exists(paste(input$output_folder,
"/checkpoint.txt",sep=""))){
checkpointFile<-read.table(paste(input$output_folder,
"/checkpoint.txt",sep=""),
header=TRUE,sep="\t",
stringsAsFactors = FALSE)
minimumProgress<-min(checkpointFile[,2:length(checkpointFile[1,])],
na.rm = TRUE)
if(minimumProgress==1){
output$checkpointUI1<-renderUI({selectInput('checkpoint',
"",
choices=c("1: After target filtration"=1))})
}
if(minimumProgress==2){
output$checkpointUI1<-renderUI({selectInput('checkpoint',
"",
choices=c("1: After target filtration"=1,
"2: After normalization"=2))})
}
if(minimumProgress==3){
output$checkpointUI1<-renderUI({selectInput('checkpoint',
"",
choices=c("1: After target filtration"=1,
"2: After normalization"=2,
"3: After annotation"=3))})
}
if(minimumProgress==4){
output$checkpointUI1<-renderUI({selectInput('checkpoint',
"",
choices=c("1: After target filtration"=1,
"2: After normalization"=2,
"3: After annotation"=3,
"4: After combination"=4))})
}
if(minimumProgress==5){
output$checkpointUI1<-renderUI({selectInput('checkpoint',
"",
choices=c("1: After target filtration"=1,
"2: After normalization"=2,
"3: After annotation"=3,
"4: After combination"=4,
"5: After coverage and BQ filtration"=5))})
}
if(minimumProgress==6){
output$checkpointUI1<-renderUI({selectInput('checkpoint',
"",
choices=c("1: After target filtration"=1,
"2: After normalization"=2,
"3: After annotation"=3,
"4: After combination"=4,
"5: After coverage and BQ filtration"=5,
"6: After extended set of characteristics"=6))})
}
if(minimumProgress==7){
output$checkpointUI1<-renderUI({selectInput('checkpoint',
"",
choices=c("1: After target filtration"=1,
"2: After normalization"=2,
"3: After annotation"=3,
"4: After combination"=4,
"5: After coverage and BQ filtration"=5,
"6: After extended set of characteristics"=6,
"7: After final filtration"=7))})
}
output$checkpointUI2<-renderUI({actionButton("appreci8Rcheckpoint",
'Start analysis from selected checkpoint')})
}
if(!file.exists(paste(input$output_folder,"/checkpoint.txt",
sep=""))){
output$checkpointUI1<-renderUI({selectInput('checkpoint',"",
choices=c("Sorry, no checkpoint available"=0),
"Sorry, no checkpoint available")})
output$checkpointUI2<-renderUI({NULL})
}
})
#0. Preparation
output$output_folderUI<-renderUI({textInput('output_folder',
'Define output folder',
"/home/documents")})
#3. Annotate
output$locationsUI<-renderUI({checkboxGroupInput("locations",
"What are the locations you are interested in?",
c("coding",
"intron",
"threeUTR",
"fiveUTR",
"intergenic",
"spliceSite",
"promoter"),
c("coding"),
inline=TRUE)})
output$consequencesUI<-renderUI({checkboxGroupInput("consequences",
"What kind of variants are you interested in? (coding only)",
c("synonymous",
"nonsynonymous",
"frameshift",
"nonsense",
"not translated"),
c("nonsynonymous",
"frameshift",
"nonsense"),
inline=TRUE)})
#5. Coverage and BQ
output$bam_folderUI<-renderUI({textInput('bam_folder',
'Define folder containing bam- and bai files',"/home/alignment/")})
output$dpUI<-renderUI({numericInput("dp",
"Minimum coverage [10;9999]",
value=50,min=10,max=9999)})
output$nr_altUI<-renderUI({numericInput("nr_alt",
"Minimum number of reads carrying the alternate allele [3;9999]",
value=20,min=3,max=9999)})
output$vafUI<-renderUI({sliderInput("vaf",
"Minimum allele frequency [%]",
min=1,max=100,value=1)})
output$bqUI<-renderUI({numericInput("bq",
"Minimum base quality [0;40]",
value=15,min=0,max=40)})
output$bq_diffUI<-renderUI({numericInput("bq_diff",
"Maximum difference between Ref_BQ and Alt_BQ [0;40]",
value=7,min=0,max=40)})
#6. Characteristics
output$dbSNPUI<-renderUI({checkboxInput("dbSNP",
"Consider dbSNP? (Hsapiens.dbSNP144.GRCh37 and XtraSNPlocs.Hsapiens.dbSNP144.GRCh37)",
value=TRUE)})
output$"1kgenomesUI"<-renderUI({checkboxInput("1kgenomes",
"Consider 1000 Genomes? (MafDb.1Kgenomes.phase3.hs37d5)",
value=TRUE)})
output$exacUI<-renderUI({checkboxInput("exac",
"Consider ExAC? (MafDb.ExAC.r1.0.hs37d5)",
value=TRUE)})
output$gadUI<-renderUI({checkboxInput("gad",
"Consider Genome Aggregation Database? (MafDb.gnomADex.r2.1.hs37d5)",
value=TRUE)})
output$cosmicUI<-renderUI({checkboxInput("cosmic",
"Consider COSMIC? (COSMIC.67)",
value=TRUE)})
output$clinvarUI<-renderUI({checkboxInput("clinvar",
"Consider ClinVar? (rentrez)",
value=TRUE)})
output$predictUI<-renderUI({radioButtons("predict",
"What source would you like to use for impact prediction?",
c("SIFT","Provean",
"PolyPhen2"),
"Provean",inline=TRUE)})
#7. Filtration
output$stricter_thresholdsUI<-renderUI({radioButtons('stricter_thresholds',
"Do you want to define stricter thresholds for coverage and base quality?",
c("Yes","No"),
"No",
inline=TRUE)})
output$stricter_thresholdsUI2<-renderUI({conditionalPanel(
condition="input.stricter_thresholds=='Yes'",
numericInput("dp2","Minimum coverage [10;9999]",
value=50,min=10,max=9999),
numericInput("nr_alt2",
"Minimum number of reads carrying the alternate allele [3;9999]",
value=20,min=3,max=9999),
sliderInput("vaf2","Minimum allele frequency [%]",
min=1,max=100,value=1),
numericInput("bq2","Minimum base quality [0;36]",
value=15,min=0,max=36),
numericInput("bq_diff2",
"Maximum difference between Ref_BQ and Alt_BQ [0;36]",
value=7,min=0,max=36)
)})
output$nr_samplesUI<-renderUI({numericInput("nr_samples",
"Detection in more than how many samples makes a call striking?",
value=3,min=1,
max=9999)})
output$predictionUI1<-renderUI({conditionalPanel(
condition="input.predict=='SIFT'",
sliderInput("damaging_safe1",
"SIFT: When is a damaging prediction reliable? (internal threshold <=0.05)",
min=0,max=1.0,value=0.05),
sliderInput("tolerated_safe1",
"SIFT: When is a tolerated prediction reliable? (internal threshold >0.05)",
min=0,max=1.0,value=0.05)
)})
output$predictionUI2<-renderUI({conditionalPanel(
condition="input.predict=='Provean'",
sliderInput("damaging_safe2",
"Provean: When is a damaging prediction reliable? (internal threshold <=-2.5)",
min=-20,max=10,value=-3),
sliderInput("tolerated_safe2",
"Provean: When is a tolerated prediction reliable? (internal threshold >-2.5)",
min=-20,max=10,value=-1.5)
)})
output$predictionUI3<-renderUI({conditionalPanel(
condition="input.predict=='PolyPhen2'",
sliderInput("damaging_safe3",
"PolyPhen2: When is a damaging prediction reliable? (>=0.5)",
min=0,max=1,value=0.5),
sliderInput("tolerated_safe3",
"PolyPhen2: When is a tolerated prediction reliable? (<0.5)",
min=0,max=1,value=0.5)
)})
output$artifact_scoreUI<-renderUI({radioButtons('artifact_score',
"Would you like to change the default scoring for the artifact score?",
c("Yes","No"),"No",
inline=TRUE)})
output$artifact_scoreUI2<-renderUI({conditionalPanel(
condition="input.artifact_score=='Yes'",
h4("Important note:"),
h5("High score -> artifact"),
h5("Low score -> probably true"),
sliderInput("PolymorphismVAF10",
"Polymorphism (based on polymorphism score) AND VAF<10%",
min=-5,max=5,value=5),
sliderInput("BQ_AltMean","BQ_Alt<(mean(BQ_Alt)-3*sd(BQ_Alt))",
min=-5,max=5,value=4),
sliderInput("detectedHigh","Detected in >50% of all samples",
min=-5,max=5,value=2),
sliderInput("detectedLow",
"Detected in a striking number of samples",
min=-5,max=5,value=2),
sliderInput("detectedLowVAF",
"Detected in a striking number of samples AND VAF>85%",
min=-5,max=5,value=2),
sliderInput("vafLow","VAF<2%",min=-5,max=5,value=2),
sliderInput("PolymorphismVAF20",
"Polymorphism (based on polymorphism score) AND VAF<20%",
min=-5,max=5,value=2),
sliderInput("PolymorphismFrame",
"Polymorphism (based on polymorphism score) AND frameshift",
min=-5,max=5,value=2),
sliderInput("isIndel","Indel",min=-5,max=5,value=1),
sliderInput("isIndelVAF","Indel AND VAF<5%",
min=-5,max=5,value=1),
sliderInput("noPrimerP","No primer (information) AND p<0.001",
min=-5,max=5,value=1),
sliderInput("noPrimerPFwd",
"No primer (information) AND p>=0.001 AND Nr_Ref_fwd>=(Min_DP-Min_Alt)/2 AND Nr_Alt_fwd<=2",
min=-5,max=5,value=1),
sliderInput("noPrimerPRev",
"No primer (information) AND p>=0.001 AND Nr_Ref_rev>=(Min_DP-Min_Alt)/2 AND Nr_Alt_rev<=2",
min=-5,max=5,value=1),
sliderInput("databaseVAF","No database AND VAF<10%",
min=-5,max=5,value=1),
sliderInput("databaseHigh",
"No database AND detected in >50% of all samples",
min=-5,max=5,value=1),
sliderInput("predictionVAF",
"Reliable tolerated prediction AND (VAF<35% OR 65%<VAF<85%)",
min=-5,max=5,value=1),
sliderInput("oneCaller","Reported by only 1 caller",
min=-5,max=5,value=1),
sliderInput("primerLocation","Primer-location",
min=-5,max=5,value=-1),
sliderInput("primerPAlt",
"No primer (information) AND p<0.001 AND Nr_Alt_fwd>=Min_Alt/2 AND Nr_Alt_rev>=Min_Alt/2",
min=-5,max=5,value=-1),
sliderInput("primerPFwd",
"No primer (information) AND p<0.001 AND Nr_Ref_fwd<(Min_DP-Min_Alt)/2 AND Nr_Alt_fwd<=2",
min=-5,max=5,value=-1),
sliderInput("primerPRev",
"No primer (information) AND p<0.001 AND Nr_Ref_rev<(Min_DP-Min_Alt)/2 AND Nr_Alt_rev<=2",
min=-5,max=5,value=-1),
sliderInput("predictionSafe","Reliable damaging prediction",
min=-5,max=5,value=-1),
numericInput("nrcaller4",
"Intermediate number of callers to report the same variant [1;14]",
min=1,max=14,value=4),
sliderInput("reward4","Score",min=-5,max=5,value=-1),
numericInput("nrcaller5",
"High number of callers to report the same variant [1;14]",
min=1,max=14,value=5),
sliderInput("reward5","Score",min=-5,max=5,value=-1),
numericInput("nrcaller6",
"Very high number of callers to report the same variant [1;14]",
min=1,max=14,value=6),
sliderInput("reward6","Score",min=-5,max=5,value=-1),
sliderInput("knownHotspot","Known hotspot",
min=-5,max=5,value=-3),
checkboxGroupInput("overlapTools",
"Overlapping output by which tools shall be rewarded?",
choices=c("GATK","Platypus","VarScan",
"LoFreq","FreeBayes","SNVer",
"SamTools","VarDict","Caller1",
"Caller2","Caller3","Caller4",
"Caller5"),
selected=c("LoFreq","FreeBayes","VarDict"),
inline=TRUE),
sliderInput("overlapReward","Score",min=-5,max=5,value=-3),
hr(),
sliderInput("artifactThreshold",
"Threshold artifact score (still artifact)",
min=-10,max=10,value=0)
)})
output$polymorphism_scoreUI<-renderUI({radioButtons('polymorphism_score',
"Would you like to change the default scoring for the polymorphism score?",
c("Yes","No"),
"No",
inline=TRUE)})
output$polymorphism_scoreUI2<-renderUI({conditionalPanel(
condition="input.polymorphism_score=='Yes'",
h4("Important note:"),
h5("High score -> polymorphism"),
h5("Low score -> no polymorphism"),
sliderInput("polyDetected",
"Detected in a striking number of samples",
min=-5,max=5,value=1),
numericInput("polyDatabases",
"High number of databases to have information on a variant [1;8]",
min=1,max=8,value=6),
sliderInput("polyDatabasesReward","Score",min=-5,max=5,value=1),
numericInput("polyDatabasesPolyLow",
"Intermediate number of polymorphism databases to have information on a variant [1;8]",
min=1,max=8,value=2),
sliderInput("polyDatabasesPolyLowReward","Score",
min=-5,max=5,value=1),
numericInput("polyDatabasesPolyHigh",
"High number of polymorphism databases to have information on a variant [1;8]",
min=1,max=8,value=4),
sliderInput("polyDatabasesPolyHighReward","Score",
min=-5,max=5,value=1),
sliderInput("polyVAF","35%<=VAF>=65% OR 85%<=VAF",
min=-5,max=5,value=1),
sliderInput("polyPrediction","Reliable tolerated prediction",
min=-5,max=5,value=1),
sliderInput("polyEffect",
"No frameshift AND no stop gained AND no stop lost",
min=-5,max=5,value=1),
sliderInput("polyDetectedOnce","Reported in only 1 sample",
min=-5,max=5,value=-1),
numericInput("polyDatabasesMut",
"Critical number of mutation databases to have information on a variant [1;8]",
min=1,max=8,value=2),
sliderInput("polyDatabasesMutReward","Score",
min=-5,max=5,value=-1),
sliderInput("polyNoDatabase",
"Not detected in any polymorphism database",
min=-5,max=5,value=-1),
sliderInput("polyPredictionEffect",
"Reliable damaging prediction OR stop gained OR stop lost",
min=-5,max=5,value=-1),
numericInput("polyCosmic",
"Critical number of Cosmic entries [1;1000]",
min=1,max=1000,value=100),
hr(),
sliderInput("polyThresholdCritical",
"Threshold polymorphism score if number of Cosmic entries is not critical (still polymorphism)",
min=-10,max=10,value=2),
sliderInput("polyThreshold",
"Threshold polymorphism score if number of Cosmic entries is critical (still polymorphism)",
min=-10,max=10,value=3)
)})
observeEvent(input$exportConfig,{
output$exportconfigUI0<-renderUI({h4('Important note:')})
output$exportconfigUI0.1<-renderUI({h5('Information on uploaded files (target region, primer positions or hotspot list) cannot be exported/imported.')})
output$exportconfigUI1<-renderUI({textInput('configFileOut',
'Define file name for your configuration file (will be safed as *.txt file in your output folder)',
"Config1")})
output$exportconfigUI2<-renderUI({actionButton("safeConfig",
'Safe configuration')})
output$messageUI1<-renderUI({NULL})
output$messageUI2<-renderUI({NULL})
output$importconfigUI0<-renderUI({NULL})
output$importconfigUI0.1<-renderUI({NULL})
output$importconfigUI1<-renderUI({NULL})
output$importconfigUI2<-renderUI({NULL})
})
observeEvent(input$importConfig,{
output$importconfigUI0<-renderUI({h4('Important note:')})
output$importconfigUI0.1<-renderUI({h5('Information on uploaded files (target region, primer positions or hotspot list) cannot be exported/imported.')})
output$importconfigUI1<-renderUI({fileInput('configFileIn',
'Upload your configuration file')})
output$importconfigUI2<-renderUI({actionButton("applyConfig",
'Apply configuration')})
output$messageUI2<-renderUI({NULL})
output$messageUI1<-renderUI({NULL})
output$exportconfigUI0<-renderUI({NULL})
output$exportconfigUI0.1<-renderUI({NULL})
output$exportconfigUI1<-renderUI({NULL})
output$exportconfigUI2<-renderUI({NULL})
})
observeEvent(input$safeConfig,{
#check if output-folder really exists
if(file.exists(input$output_folder)==FALSE){
log_info<-c("Your output folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(file.exists(input$output_folder)==TRUE){
log_info<-paste("Saving your current setting as ",
input$configFileOut,".txt<br><br>",sep="")
output$log_info<-renderUI({HTML(log_info)})
config<-data.frame(Variable=NA,Value=NA)
#GATK
config[1,1]<-"gatk_folder"
config[1,2]<-ifelse(!is.null(input$gatk_folder),
input$gatk_folder,NA)
config[2,1]<-"gatk_file_type"
config[2,2]<-ifelse(!is.null(input$gatk_file_type),
input$gatk_file_type,NA)
config[3,1]<-"gatk_chr"
config[3,2]<-ifelse(!is.null(input$gatk_chr),
input$gatk_chr,NA)
config[4,1]<-"gatk_pos"
config[4,2]<-ifelse(!is.null(input$gatk_pos),
input$gatk_pos,NA)
config[5,1]<-"gatk_ref"
config[5,2]<-ifelse(!is.null(input$gatk_ref),
input$gatk_ref,NA)
config[6,1]<-"gatk_alt"
config[6,2]<-ifelse(!is.null(input$gatk_alt),
input$gatk_alt,NA)
config[7,1]<-"gatk_file_names_add"
config[7,2]<-ifelse(!is.null(input$gatk_file_names_add),
input$gatk_file_names_add,NA)
config[8,1]<-"gatk_mnvs"
config[8,2]<-ifelse(!is.null(input$gatk_mnvs),
input$gatk_mnvs,NA)
config[9,1]<-"gatk_snv_indel"
config[9,2]<-ifelse(!is.null(input$gatk_snv_indel),
input$gatk_snv_indel,NA)
config[10,1]<-"gatk_snv_names_add"
config[10,2]<-ifelse(!is.null(input$gatk_snv_names_add),
input$gatk_snv_names_add,NA)
config[11,1]<-"gatk_indel_names_add"
config[11,2]<-ifelse(!is.null(input$gatk_indel_names_add),
input$gatk_indel_names_add,NA)
config[12,1]<-"gatk_indels"
config[12,2]<-ifelse(!is.null(input$gatk_indels),
input$gatk_indels,NA)
#Platypus
config[13,1]<-"platypus_folder"
config[13,2]<-ifelse(!is.null(input$platypus_folder),
input$platypus_folder,NA)
config[14,1]<-"platypus_file_type"
config[14,2]<-ifelse(!is.null(input$platypus_file_type),
input$platypus_file_type,NA)
config[15,1]<-"platypus_chr"
config[15,2]<-ifelse(!is.null(input$platypus_chr),
input$platypus_chr,NA)
config[16,1]<-"platypus_pos"
config[16,2]<-ifelse(!is.null(input$platypus_pos),
input$platypus_pos,NA)
config[17,1]<-"platypus_ref"
config[17,2]<-ifelse(!is.null(input$platypus_ref),
input$platypus_ref,NA)
config[18,1]<-"platypus_alt"
config[18,2]<-ifelse(!is.null(input$platypus_alt),
input$platypus_alt,NA)
config[19,1]<-"platypus_file_names_add"
config[19,2]<-ifelse(!is.null(input$platypus_file_names_add),
input$platypus_file_names_add,NA)
config[20,1]<-"platypus_mnvs"
config[20,2]<-ifelse(!is.null(input$platypus_mnvs),
input$platypus_mnvs,NA)
config[21,1]<-"platypus_snv_indel"
config[21,2]<-ifelse(!is.null(input$platypus_snv_indel),
input$platypus_snv_indel,NA)
config[22,1]<-"platypus_snv_names_add"
config[22,2]<-ifelse(!is.null(input$platypus_snv_names_add),
input$platypus_snv_names_add,NA)
config[23,1]<-"platypus_indel_names_add"
config[23,2]<-ifelse(!is.null(input$platypus_indel_names_add),
input$platypus_indel_names_add,NA)
config[24,1]<-"platypus_indels"
config[24,2]<-ifelse(!is.null(input$platypus_indels),
input$platypus_indels,NA)
#VarScan
config[25,1]<-"varscan_folder"
config[25,2]<-ifelse(!is.null(input$varscan_folder),
input$varscan_folder,NA)
config[26,1]<-"varscan_file_type"
config[26,2]<-ifelse(!is.null(input$varscan_file_type),
input$varscan_file_type,NA)
config[27,1]<-"varscan_chr"
config[27,2]<-ifelse(!is.null(input$varscan_chr),
input$varscan_chr,NA)
config[28,1]<-"varscan_pos"
config[28,2]<-ifelse(!is.null(input$varscan_pos),
input$varscan_pos,NA)
config[29,1]<-"varscan_ref"
config[29,2]<-ifelse(!is.null(input$varscan_ref),
input$varscan_ref,NA)
config[30,1]<-"varscan_alt"
config[30,2]<-ifelse(!is.null(input$varscan_alt),
input$varscan_alt,NA)
config[31,1]<-"varscan_file_names_add"
config[31,2]<-ifelse(!is.null(input$varscan_file_names_add),
input$varscan_file_names_add,NA)
config[32,1]<-"varscan_mnvs"
config[32,2]<-ifelse(!is.null(input$varscan_mnvs),
input$varscan_mnvs,NA)
config[33,1]<-"varscan_snv_indel"
config[33,2]<-ifelse(!is.null(input$varscan_snv_indel),
input$varscan_snv_indel,NA)
config[34,1]<-"varscan_snv_names_add"
config[34,2]<-ifelse(!is.null(input$varscan_snv_names_add),
input$varscan_snv_names_add,NA)
config[35,1]<-"varscan_indel_names_add"
config[35,2]<-ifelse(!is.null(input$varscan_indel_names_add),
input$varscan_indel_names_add,NA)
config[36,1]<-"varscan_indels"
config[36,2]<-ifelse(!is.null(input$varscan_indels),
input$varscan_indels,NA)
#FreeBayes
config[37,1]<-"freebayes_folder"
config[37,2]<-ifelse(!is.null(input$freebayes_folder),
input$freebayes_folder,NA)
config[38,1]<-"freebayes_file_type"
config[38,2]<-ifelse(!is.null(input$freebayes_file_type),
input$freebayes_file_type,NA)
config[39,1]<-"freebayes_chr"
config[39,2]<-ifelse(!is.null(input$freebayes_chr),
input$freebayes_chr,NA)
config[40,1]<-"freebayes_pos"
config[40,2]<-ifelse(!is.null(input$freebayes_pos),
input$freebayes_pos,NA)
config[41,1]<-"freebayes_ref"
config[41,2]<-ifelse(!is.null(input$freebayes_ref),
input$freebayes_ref,NA)
config[42,1]<-"freebayes_alt"
config[42,2]<-ifelse(!is.null(input$freebayes_alt),
input$freebayes_alt,NA)
config[43,1]<-"freebayes_file_names_add"
config[43,2]<-ifelse(!is.null(input$freebayes_file_names_add),
input$freebayes_file_names_add,NA)
config[44,1]<-"freebayes_mnvs"
config[44,2]<-ifelse(!is.null(input$freebayes_mnvs),
input$freebayes_mnvs,NA)
config[45,1]<-"freebayes_snv_indel"
config[45,2]<-ifelse(!is.null(input$freebayes_snv_indel),
input$freebayes_snv_indel,NA)
config[46,1]<-"freebayes_snv_names_add"
config[46,2]<-ifelse(!is.null(input$freebayes_snv_names_add),
input$freebayes_snv_names_add,NA)
config[47,1]<-"freebayes_indel_names_add"
config[47,2]<-ifelse(!is.null(input$freebayes_indel_names_add),
input$freebayes_indel_names_add,NA)
config[48,1]<-"freebayes_indels"
config[48,2]<-ifelse(!is.null(input$freebayes_indels),
input$freebayes_indels,NA)
#LoFreq
config[49,1]<-"lofreq_folder"
config[49,2]<-ifelse(!is.null(input$lofreq_folder),
input$lofreq_folder,NA)
config[50,1]<-"lofreq_file_type"
config[50,2]<-ifelse(!is.null(input$lofreq_file_type),
input$lofreq_file_type,NA)
config[51,1]<-"lofreq_chr"
config[51,2]<-ifelse(!is.null(input$lofreq_chr),
input$lofreq_chr,NA)
config[52,1]<-"lofreq_pos"
config[52,2]<-ifelse(!is.null(input$lofreq_pos),
input$lofreq_pos,NA)
config[53,1]<-"lofreq_ref"
config[53,2]<-ifelse(!is.null(input$lofreq_ref),
input$lofreq_ref,NA)
config[54,1]<-"lofreq_alt"
config[54,2]<-ifelse(!is.null(input$lofreq_alt),
input$lofreq_alt,NA)
config[55,1]<-"lofreq_file_names_add"
config[55,2]<-ifelse(!is.null(input$lofreq_file_names_add),
input$lofreq_file_names_add,NA)
config[56,1]<-"lofreq_mnvs"
config[56,2]<-ifelse(!is.null(input$lofreq_mnvs),
input$lofreq_mnvs,NA)
config[57,1]<-"lofreq_snv_indel"
config[57,2]<-ifelse(!is.null(input$lofreq_snv_indel),
input$lofreq_snv_indel,NA)
config[58,1]<-"lofreq_snv_names_add"
config[58,2]<-ifelse(!is.null(input$lofreq_snv_names_add),
input$lofreq_snv_names_add,NA)
config[59,1]<-"lofreq_indel_names_add"
config[59,2]<-ifelse(!is.null(input$lofreq_indel_names_add),
input$lofreq_indel_names_add,NA)
config[60,1]<-"lofreq_indels"
config[60,2]<-ifelse(!is.null(input$lofreq_indels),
input$lofreq_indels,NA)
#SNVer
config[61,1]<-"snver_folder"
config[61,2]<-ifelse(!is.null(input$snver_folder),
input$snver_folder,NA)
config[62,1]<-"snver_file_type"
config[62,2]<-ifelse(!is.null(input$snver_file_type),
input$snver_file_type,NA)
config[63,1]<-"snver_chr"
config[63,2]<-ifelse(!is.null(input$snver_chr),
input$snver_chr,NA)
config[64,1]<-"snver_pos"
config[64,2]<-ifelse(!is.null(input$snver_pos),
input$snver_pos,NA)
config[65,1]<-"snver_ref"
config[65,2]<-ifelse(!is.null(input$snver_ref),
input$snver_ref,NA)
config[66,1]<-"snver_alt"
config[66,2]<-ifelse(!is.null(input$snver_alt),
input$snver_alt,NA)
config[67,1]<-"snver_file_names_add"
config[67,2]<-ifelse(!is.null(input$snver_file_names_add),
input$snver_file_names_add,NA)
config[68,1]<-"snver_mnvs"
config[68,2]<-ifelse(!is.null(input$snver_mnvs),
input$snver_mnvs,NA)
config[69,1]<-"snver_snv_indel"
config[69,2]<-ifelse(!is.null(input$snver_snv_indel),
input$snver_snv_indel,NA)
config[70,1]<-"snver_snv_names_add"
config[70,2]<-ifelse(!is.null(input$snver_snv_names_add),
input$snver_snv_names_add,NA)
config[71,1]<-"snver_indel_names_add"
config[71,2]<-ifelse(!is.null(input$snver_indel_names_add),
input$snver_indel_names_add,NA)
config[72,1]<-"snver_indels"
config[72,2]<-ifelse(!is.null(input$snver_indels),
input$snver_indels,NA)
#SamTools
config[73,1]<-"samtools_folder"
config[73,2]<-ifelse(!is.null(input$samtools_folder),
input$samtools_folder,NA)
config[74,1]<-"samtools_file_type"
config[74,2]<-ifelse(!is.null(input$samtools_file_type),
input$samtools_file_type,NA)
config[75,1]<-"samtools_chr"
config[75,2]<-ifelse(!is.null(input$samtools_chr),
input$samtools_chr,NA)
config[76,1]<-"samtools_pos"
config[76,2]<-ifelse(!is.null(input$samtools_pos),
input$samtools_pos,NA)
config[77,1]<-"samtools_ref"
config[77,2]<-ifelse(!is.null(input$samtools_ref),
input$samtools_ref,NA)
config[78,1]<-"samtools_alt"
config[78,2]<-ifelse(!is.null(input$samtools_alt),
input$samtools_alt,NA)
config[79,1]<-"samtools_file_names_add"
config[79,2]<-ifelse(!is.null(input$samtools_file_names_add),
input$samtools_file_names_add,NA)
config[80,1]<-"samtools_mnvs"
config[80,2]<-ifelse(!is.null(input$samtools_mnvs),
input$samtools_mnvs,NA)
config[81,1]<-"samtools_snv_indel"
config[81,2]<-ifelse(!is.null(input$samtools_snv_indel),
input$samtools_snv_indel,NA)
config[82,1]<-"samtools_snv_names_add"
config[82,2]<-ifelse(!is.null(input$samtools_snv_names_add),
input$samtools_snv_names_add,NA)
config[83,1]<-"samtools_indel_names_add"
config[83,2]<-ifelse(!is.null(input$samtools_indel_names_add),
input$samtools_indel_names_add,NA)
config[84,1]<-"samtools_indels"
config[84,2]<-ifelse(!is.null(input$samtools_indels),
input$samtools_indels,NA)
#VarDict
config[85,1]<-"vardict_folder"
config[85,2]<-ifelse(!is.null(input$vardict_folder),
input$vardict_folder,NA)
config[86,1]<-"vardict_file_type"
config[86,2]<-ifelse(!is.null(input$vardict_file_type),
input$vardict_file_type,NA)
config[87,1]<-"vardict_chr"
config[87,2]<-ifelse(!is.null(input$vardict_chr),
input$vardict_chr,NA)
config[88,1]<-"vardict_pos"
config[88,2]<-ifelse(!is.null(input$vardict_pos),
input$vardict_pos,NA)
config[89,1]<-"vardict_ref"
config[89,2]<-ifelse(!is.null(input$vardict_ref),
input$vardict_ref,NA)
config[90,1]<-"vardict_alt"
config[90,2]<-ifelse(!is.null(input$vardict_alt),
input$vardict_alt,NA)
config[91,1]<-"vardict_file_names_add"
config[91,2]<-ifelse(!is.null(input$vardict_file_names_add),
input$vardict_file_names_add,NA)
config[92,1]<-"vardict_mnvs"
config[92,2]<-ifelse(!is.null(input$vardict_mnvs),
input$vardict_mnvs,NA)
config[93,1]<-"vardict_snv_indel"
config[93,2]<-ifelse(!is.null(input$vardict_snv_indel),
input$vardict_snv_indel,NA)
config[94,1]<-"vardict_snv_names_add"
config[94,2]<-ifelse(!is.null(input$vardict_snv_names_add),
input$vardict_snv_names_add,NA)
config[95,1]<-"vardict_indel_names_add"
config[95,2]<-ifelse(!is.null(input$vardict_indel_names_add),
input$vardict_indel_names_add,NA)
config[96,1]<-"vardict_indels"
config[96,2]<-ifelse(!is.null(input$vardict_indels),
input$vardict_indels,NA)
#additional callers
#caller1
config[97,1]<-"caller1_h4"
config[97,2]<-ifelse(input$nr_additional>0,"Caller 1:",NA)
config[98,1]<-"caller1_name"
config[98,2]<-ifelse(!is.null(input$caller1_name),
input$caller1_name,NA)
config[99,1]<-"caller1_folder"
config[99,2]<-ifelse(!is.null(input$caller1_folder),
input$caller1_folder,NA)
config[100,1]<-"caller1_file_type"
config[100,2]<-ifelse(!is.null(input$caller1_file_type),
input$caller1_file_type,NA)
config[101,1]<-"caller1_chr"
config[101,2]<-ifelse(!is.null(input$caller1_chr),
input$caller1_chr,NA)
config[102,1]<-"caller1_pos"
config[102,2]<-ifelse(!is.null(input$caller1_pos),
input$caller1_pos,NA)
config[103,1]<-"caller1_ref"
config[103,2]<-ifelse(!is.null(input$caller1_ref),
input$caller1_ref,NA)
config[104,1]<-"caller1_alt"
config[104,2]<-ifelse(!is.null(input$caller1_alt),
input$caller1_alt,NA)
config[105,1]<-"caller1_file_names_add"
config[105,2]<-ifelse(!is.null(input$caller1_file_names_add),
input$caller1_file_names_add,NA)
config[106,1]<-"caller1_mnvs"
config[106,2]<-ifelse(!is.null(input$caller1_mnvs),
input$caller1_mnvs,NA)
config[107,1]<-"caller1_snv_indel"
config[107,2]<-ifelse(!is.null(input$caller1_snv_indel),
input$caller1_snv_indel,NA)
config[108,1]<-"caller1_snv_names_add"
config[108,2]<-ifelse(!is.null(input$caller1_snv_names_add),
input$caller1_snv_names_add,NA)
config[109,1]<-"caller1_indel_names_add"
config[109,2]<-ifelse(!is.null(input$caller1_indel_names_add),
input$caller1_indel_names_add,NA)
config[110,1]<-"caller1_indels"
config[110,2]<-ifelse(!is.null(input$caller1_indels),
input$caller1_indels,NA)
#caller2
config[111,1]<-"caller2_h4"
config[111,2]<-ifelse(input$nr_additional>1,"Caller 2:",NA)
config[112,1]<-"caller2_name"
config[112,2]<-ifelse(!is.null(input$caller2_name),
input$caller2_name,NA)
config[113,1]<-"caller2_folder"
config[113,2]<-ifelse(!is.null(input$caller2_folder),
input$caller2_folder,NA)
config[114,1]<-"caller2_file_type"
config[114,2]<-ifelse(!is.null(input$caller2_file_type),
input$caller2_file_type,NA)
config[115,1]<-"caller2_chr"
config[115,2]<-ifelse(!is.null(input$caller2_chr),
input$caller2_chr,NA)
config[116,1]<-"caller2_pos"
config[116,2]<-ifelse(!is.null(input$caller2_pos),
input$caller2_pos,NA)
config[117,1]<-"caller2_ref"
config[117,2]<-ifelse(!is.null(input$caller2_ref),
input$caller2_ref,NA)
config[118,1]<-"caller2_alt"
config[118,2]<-ifelse(!is.null(input$caller2_alt),
input$caller2_alt,NA)
config[119,1]<-"caller2_file_names_add"
config[119,2]<-ifelse(!is.null(input$caller2_file_names_add),
input$caller2_file_names_add,NA)
config[120,1]<-"caller2_mnvs"
config[120,2]<-ifelse(!is.null(input$caller2_mnvs),
input$caller2_mnvs,NA)
config[121,1]<-"caller2_snv_indel"
config[121,2]<-ifelse(!is.null(input$caller2_snv_indel),
input$caller2_snv_indel,NA)
config[122,1]<-"caller2_snv_names_add"
config[122,2]<-ifelse(!is.null(input$caller2_snv_names_add),
input$caller2_snv_names_add,NA)
config[123,1]<-"caller2_indel_names_add"
config[123,2]<-ifelse(!is.null(input$caller2_indel_names_add),
input$caller2_indel_names_add,NA)
config[124,1]<-"caller2_indels"
config[124,2]<-ifelse(!is.null(input$caller2_indels),
input$caller2_indels,NA)
#caller3
config[125,1]<-"caller3_h4"
config[125,2]<-ifelse(input$nr_additional>2,"Caller 3:",NA)
config[126,1]<-"caller3_name"
config[126,2]<-ifelse(!is.null(input$caller3_name),
input$caller3_name,NA)
config[127,1]<-"caller3_folder"
config[127,2]<-ifelse(!is.null(input$caller3_folder),
input$caller3_folder,NA)
config[128,1]<-"caller3_file_type"
config[128,2]<-ifelse(!is.null(input$caller3_file_type),
input$caller3_file_type,NA)
config[129,1]<-"caller3_chr"
config[129,2]<-ifelse(!is.null(input$caller3_chr),
input$caller3_chr,NA)
config[130,1]<-"caller3_pos"
config[130,2]<-ifelse(!is.null(input$caller3_pos),
input$caller3_pos,NA)
config[131,1]<-"caller3_ref"
config[131,2]<-ifelse(!is.null(input$caller3_ref),
input$caller3_ref,NA)
config[132,1]<-"caller3_alt"
config[132,2]<-ifelse(!is.null(input$caller3_alt),
input$caller3_alt,NA)
config[133,1]<-"caller3_file_names_add"
config[133,2]<-ifelse(!is.null(input$caller3_file_names_add),
input$caller3_file_names_add,NA)
config[134,1]<-"caller3_mnvs"
config[134,2]<-ifelse(!is.null(input$caller3_mnvs),
input$caller3_mnvs,NA)
config[135,1]<-"caller3_snv_indel"
config[135,2]<-ifelse(!is.null(input$caller3_snv_indel),
input$caller3_snv_indel,NA)
config[136,1]<-"caller3_snv_names_add"
config[136,2]<-ifelse(!is.null(input$caller3_snv_names_add),
input$caller3_snv_names_add,NA)
config[137,1]<-"caller3_indel_names_add"
config[137,2]<-ifelse(!is.null(input$caller3_indel_names_add),
input$caller3_indel_names_add,NA)
config[138,1]<-"caller3_indels"
config[138,2]<-ifelse(!is.null(input$caller3_indels),
input$caller3_indels,NA)
#caller4
config[139,1]<-"caller4_h4"
config[139,2]<-ifelse(input$nr_additional>3,"Caller 4:",NA)
config[140,1]<-"caller4_name"
config[140,2]<-ifelse(!is.null(input$caller4_name),
input$caller4_name,NA)
config[141,1]<-"caller4_folder"
config[141,2]<-ifelse(!is.null(input$caller4_folder),
input$caller4_folder,NA)
config[142,1]<-"caller4_file_type"
config[142,2]<-ifelse(!is.null(input$caller4_file_type),
input$caller4_file_type,NA)
config[143,1]<-"caller4_chr"
config[143,2]<-ifelse(!is.null(input$caller4_chr),
input$caller4_chr,NA)
config[144,1]<-"caller4_pos"
config[144,2]<-ifelse(!is.null(input$caller4_pos),
input$caller4_pos,NA)
config[145,1]<-"caller4_ref"
config[145,2]<-ifelse(!is.null(input$caller4_ref),
input$caller4_ref,NA)
config[146,1]<-"caller4_alt"
config[146,2]<-ifelse(!is.null(input$caller4_alt),
input$caller4_alt,NA)
config[147,1]<-"caller4_file_names_add"
config[147,2]<-ifelse(!is.null(input$caller4_file_names_add),
input$caller4_file_names_add,NA)
config[148,1]<-"caller4_mnvs"
config[148,2]<-ifelse(!is.null(input$caller4_mnvs),
input$caller4_mnvs,NA)
config[149,1]<-"caller4_snv_indel"
config[149,2]<-ifelse(!is.null(input$caller4_snv_indel),
input$caller4_snv_indel,NA)
config[150,1]<-"caller4_snv_names_add"
config[150,2]<-ifelse(!is.null(input$caller4_snv_names_add),
input$caller4_snv_names_add,NA)
config[151,1]<-"caller4_indel_names_add"
config[151,2]<-ifelse(!is.null(input$caller4_indel_names_add),
input$caller4_indel_names_add,NA)
config[152,1]<-"caller4_indels"
config[152,2]<-ifelse(!is.null(input$caller4_indels),
input$caller4_indels,NA)
#caller5
config[153,1]<-"caller5_h4"
config[153,2]<-ifelse(input$nr_additional>4,"Caller 5:",NA)
config[154,1]<-"caller5_name"
config[154,2]<-ifelse(!is.null(input$caller5_name),
input$caller5_name,NA)
config[155,1]<-"caller5_folder"
config[155,2]<-ifelse(!is.null(input$caller5_folder),
input$caller5_folder,NA)
config[156,1]<-"caller5_file_type"
config[156,2]<-ifelse(!is.null(input$caller5_file_type),
input$caller5_file_type,NA)
config[157,1]<-"caller5_chr"
config[157,2]<-ifelse(!is.null(input$caller5_chr),
input$caller5_chr,NA)
config[158,1]<-"caller5_pos"
config[158,2]<-ifelse(!is.null(input$caller5_pos),
input$caller5_pos,NA)
config[159,1]<-"caller5_ref"
config[159,2]<-ifelse(!is.null(input$caller5_ref),
input$caller5_ref,NA)
config[160,1]<-"caller5_alt"
config[160,2]<-ifelse(!is.null(input$caller5_alt),
input$caller5_alt,NA)
config[161,1]<-"caller5_file_names_add"
config[161,2]<-ifelse(!is.null(input$caller5_file_names_add),
input$caller5_file_names_add,NA)
config[162,1]<-"caller5_mnvs"
config[162,2]<-ifelse(!is.null(input$caller5_mnvs),
input$caller5_mnvs,NA)
config[163,1]<-"caller5_snv_indel"
config[163,2]<-ifelse(!is.null(input$caller5_snv_indel),
input$caller5_snv_indel,NA)
config[164,1]<-"caller5_snv_names_add"
config[164,2]<-ifelse(!is.null(input$caller5_snv_names_add),
input$caller5_snv_names_add,NA)
config[165,1]<-"caller5_indel_names_add"
config[165,2]<-ifelse(!is.null(input$caller5_indel_names_add),
input$caller5_indel_names_add,NA)
config[166,1]<-"caller5_indels"
config[166,2]<-ifelse(!is.null(input$caller5_indels),
input$caller5_indels,NA)
#3. Annotation
config[167,1]<-"locations"
config[167,2]<-paste(input$locations,collapse=",")
config[168,1]<-"consequences"
config[168,2]<-paste(input$consequences,collapse=",")
#5. Coverage and BQ
config[169,1]<-"bam_folder"
config[169,2]<-input$bam_folder
config[170,1]<-"dp"
config[170,2]<-input$dp
config[171,1]<-"nr_alt"
config[171,2]<-input$nr_alt
config[172,1]<-"vaf"
config[172,2]<-input$vaf
config[173,1]<-"bq"
config[173,2]<-input$bq
config[174,1]<-"bq_diff"
config[174,2]<-input$bq_diff
#6. Characteristics
config[175,1]<-"dbSNP"
config[175,2]<-ifelse(!is.null(input$dbSNP),input$dbSNP,NA)
config[176,1]<-"1kgenomes"
config[176,2]<-ifelse(!is.null(input$"1kgenomes"),
input$"1kgenomes",NA)
config[177,1]<-"exac"
config[177,2]<-ifelse(!is.null(input$exac),input$exac,NA)
config[178,1]<-"esp"
config[178,2]<-NA
config[179,1]<-"gad"
config[179,2]<-ifelse(!is.null(input$gad),input$gad,NA)
config[180,1]<-"cosmic"
config[180,2]<-ifelse(!is.null(input$cosmic),
input$cosmic,NA)
config[181,1]<-"clinvar"
config[181,2]<-ifelse(!is.null(input$clinvar),
input$clinvar,NA)
config[182,1]<-"predict"
config[182,2]<-ifelse(!is.null(input$predict),
input$predict,NA)
#7. Filtration
config[183,1]<-"stricter_thresholds"
config[183,2]<-input$stricter_thresholds
config[184,1]<-"dp2"
config[184,2]<-ifelse(input$stricter_thresholds=="Yes",
input$dp2,NA)
config[185,1]<-"nr_alt2"
config[185,2]<-ifelse(input$stricter_thresholds=="Yes",
input$nr_alt2,NA)
config[186,1]<-"vaf2"
config[186,2]<-ifelse(input$stricter_thresholds=="Yes",
input$vaf2,NA)
config[187,1]<-"bq2"
config[187,2]<-ifelse(input$stricter_thresholds=="Yes",
input$bq2,NA)
config[188,1]<-"bq_diff2"
config[188,2]<-ifelse(input$stricter_thresholds=="Yes",
input$bq_diff2,NA)
config[189,1]<-"nr_samples"
config[189,2]<-input$nr_samples
config[190,1]<-"damaging_safe1"
config[190,2]<-ifelse(!is.null(input$damaging_safe1),
as.character(input$damaging_safe1),
NA)
config[191,1]<-"tolerated_safe1"
config[191,2]<-ifelse(!is.null(input$tolerated_safe1),
as.character(input$tolerated_safe1),
NA)
config[192,1]<-"damaging_safe2"
config[192,2]<-ifelse(!is.null(input$damaging_safe2),
as.character(input$damaging_safe2),
NA)
config[193,1]<-"tolerated_safe2"
config[193,2]<-ifelse(!is.null(input$tolerated_safe2),
as.character(input$tolerated_safe2),
NA)
config[194,1]<-"damaging_safe3"
config[194,2]<-ifelse(!is.null(input$damaging_safe3),
as.character(input$damaging_safe3),
NA)
config[195,1]<-"tolerated_safe3"
config[195,2]<-ifelse(!is.null(input$tolerated_safe3),
as.character(input$tolerated_safe3),
NA)
config[196,1]<-"artifact_score"
config[196,2]<-input$artifact_score
config[197,1]<-"header1"
config[197,2]<-ifelse(input$artifact_score=="Yes",
"Important note:",NA)
config[198,1]<-"header2"
config[198,2]<-ifelse(input$artifact_score=="Yes",
"High score -> artifact",NA)
config[199,1]<-"header3"
config[199,2]<-ifelse(input$artifact_score=="Yes",
"Low score -> probably true",NA)
config[200,1]<-"PolymorphismVAF10"
config[200,2]<-ifelse(input$artifact_score=="Yes",
input$PolymorphismVAF10,NA)
config[201,1]<-"BQ_AltMean"
config[201,2]<-ifelse(input$artifact_score=="Yes",
input$BQ_AltMean,NA)
config[202,1]<-"detectedHigh"
config[202,2]<-ifelse(input$artifact_score=="Yes",
input$detectedHigh,NA)
config[203,1]<-"detectedLow"
config[203,2]<-ifelse(input$artifact_score=="Yes",
input$detectedLow,NA)
config[204,1]<-"detectedLowVAF"
config[204,2]<-ifelse(input$artifact_score=="Yes",
input$detectedLowVAF,NA)
config[205,1]<-"vafLow"
config[205,2]<-ifelse(input$artifact_score=="Yes",
input$vafLow,NA)
config[206,1]<-"PolymorphismVAF20"
config[206,2]<-ifelse(input$artifact_score=="Yes",
input$PolymorphismVAF20,NA)
config[207,1]<-"PolymorphismFrame"
config[207,2]<-ifelse(input$artifact_score=="Yes",
input$PolymorphismFrame,NA)
config[208,1]<-"isIndel"
config[208,2]<-ifelse(input$artifact_score=="Yes",
input$isIndel,NA)
config[209,1]<-"isIndelVAF"
config[209,2]<-ifelse(input$artifact_score=="Yes",
input$isIndelVAF,NA)
config[210,1]<-"noPrimerP"
config[210,2]<-ifelse(input$artifact_score=="Yes",
input$noPrimerP,NA)
config[211,1]<-"noPrimerPFwd"
config[211,2]<-ifelse(input$artifact_score=="Yes",
input$noPrimerPFwd,NA)
config[212,1]<-"noPrimerPRev"
config[212,2]<-ifelse(input$artifact_score=="Yes",
input$noPrimerPRev,NA)
config[213,1]<-"databaseVAF"
config[213,2]<-ifelse(input$artifact_score=="Yes",
input$databaseVAF,NA)
config[214,1]<-"databaseHigh"
config[214,2]<-ifelse(input$artifact_score=="Yes",
input$databaseHigh,NA)
config[215,1]<-"predictionVAF"
config[215,2]<-ifelse(input$artifact_score=="Yes",
input$predictionVAF,NA)
config[216,1]<-"oneCaller"
config[216,2]<-ifelse(input$artifact_score=="Yes",
input$oneCaller,NA)
config[217,1]<-"primerLocation"
config[217,2]<-ifelse(input$artifact_score=="Yes",
input$primerLocation,NA)
config[218,1]<-"primerPAlt"
config[218,2]<-ifelse(input$artifact_score=="Yes",
input$primerPAlt,NA)
config[219,1]<-"primerPFwd"
config[219,2]<-ifelse(input$artifact_score=="Yes",
input$primerPFwd,NA)
config[220,1]<-"primerPRev"
config[220,2]<-ifelse(input$artifact_score=="Yes",
input$primerPRev,NA)
config[221,1]<-"predictionSafe"
config[221,2]<-ifelse(input$artifact_score=="Yes",
input$predictionSafe,NA)
config[222,1]<-"nrcaller4"
config[222,2]<-ifelse(input$artifact_score=="Yes",
input$nrcaller4,NA)
config[223,1]<-"reward4"
config[223,2]<-ifelse(input$artifact_score=="Yes",
input$reward4,NA)
config[224,1]<-"nrcaller5"
config[224,2]<-ifelse(input$artifact_score=="Yes",
input$nrcaller5,NA)
config[225,1]<-"reward5"
config[225,2]<-ifelse(input$artifact_score=="Yes",
input$reward5,NA)
config[226,1]<-"nrcaller6"
config[226,2]<-ifelse(input$artifact_score=="Yes",
input$nrcaller6,NA)
config[227,1]<-"reward6"
config[227,2]<-ifelse(input$artifact_score=="Yes",
input$reward6,NA)
config[228,1]<-"knownHotspot"
config[228,2]<-ifelse(input$artifact_score=="Yes",
input$knownHotspot,NA)
config[229,1]<-"overlapTools"
config[229,2]<-paste(input$overlapTools,collapse=",")
config[230,1]<-"overlapReward"
config[230,2]<-ifelse(input$artifact_score=="Yes",
input$overlapReward,NA)
config[231,1]<-"artifactThreshold"
config[231,2]<-ifelse(input$artifact_score=="Yes",
input$artifactThreshold,NA)
config[232,1]<-"polymorphism_score"
config[232,2]<-input$polymorphism_score
config[233,1]<-"header1"
config[233,2]<-ifelse(input$artifact_score=="Yes",
"Important note:",NA)
config[234,1]<-"header2"
config[234,2]<-ifelse(input$artifact_score=="Yes",
"High score -> polymorphism",NA)
config[235,1]<-"header3"
config[235,2]<-ifelse(input$artifact_score=="Yes",
"Low score -> no polymorphism",NA)
config[236,1]<-"polyDetected"
config[236,2]<-ifelse(input$artifact_score=="Yes",
input$polyDetected,NA)
config[237,1]<-"polyDatabases"
config[237,2]<-ifelse(input$artifact_score=="Yes",
input$polyDatabases,NA)
config[238,1]<-"polyDatabasesReward"
config[238,2]<-ifelse(input$artifact_score=="Yes",
input$polyDatabasesReward,NA)
config[239,1]<-"polyDatabasesPolyLow"
config[239,2]<-ifelse(input$artifact_score=="Yes",
input$polyDatabasesPolyLow,NA)
config[240,1]<-"polyDatabasesPolyLowReward"
config[240,2]<-ifelse(input$artifact_score=="Yes",
input$polyDatabasesPolyLowReward,NA)
config[241,1]<-"polyDatabasesPolyHigh"
config[241,2]<-ifelse(input$artifact_score=="Yes",
input$polyDatabasesPolyHigh,NA)
config[242,1]<-"polyDatabasesPolyHighReward"
config[242,2]<-ifelse(input$artifact_score=="Yes",
input$polyDatabasesPolyHighReward,NA)
config[243,1]<-"polyVAF"
config[243,2]<-ifelse(input$artifact_score=="Yes",
input$polyVAF,NA)
config[244,1]<-"polyPrediction"
config[244,2]<-ifelse(input$artifact_score=="Yes",
input$polyPrediction,NA)
config[245,1]<-"polyEffect"
config[245,2]<-ifelse(input$artifact_score=="Yes",
input$polyEffect,NA)
config[246,1]<-"polyDetectedOnce"
config[246,2]<-ifelse(input$artifact_score=="Yes",
input$polyDetectedOnce,NA)
config[247,1]<-"polyDatabasesMut"
config[247,2]<-ifelse(input$artifact_score=="Yes",
input$polyDatabasesMut,NA)
config[248,1]<-"PolyDatabasesMutReward"
config[248,2]<-ifelse(input$artifact_score=="Yes",
input$polyDatabasesMutReward,NA)
config[249,1]<-"polyNoDatabase"
config[249,2]<-ifelse(input$artifact_score=="Yes",
input$polyNoDatabase,NA)
config[250,1]<-"polyPredictionEffect"
config[250,2]<-ifelse(input$artifact_score=="Yes",
input$polyPredictionEffect,NA)
config[251,1]<-"polyCosmic"
config[251,2]<-ifelse(input$artifact_score=="Yes",
input$polyCosmic,NA)
config[252,1]<-"polyThresholdCritical"
config[252,2]<-ifelse(input$artifact_score=="Yes",
input$polyThresholdCritical,NA)
config[253,1]<-"polyThreshold"
config[253,2]<-ifelse(input$artifact_score=="Yes",
input$polyThreshold,NA)
config[254,1]<-"output_folder"
config[254,2]<-input$output_folder
write.table(config,paste(input$output_folder,"/",
input$configFileOut,".txt",sep=""),
quote=FALSE,row.names=FALSE,sep="\t")
output$messageUI1<-renderUI({h5("Done.")})
return()
}
})
observeEvent(input$applyConfig,{
#check if a file was uploaded
if(is.null(input$configFileIn)){
log_info<-c("Please provide a configuration file<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
config_temp<-input$configFileIn
config<-read.table(config_temp$datapath,header=TRUE,sep="\t",
stringsAsFactors=FALSE)
output$output_folderUI<-renderUI({textInput('output_folder',
'Define output folder',
as.character(config[254,2]))})
if(!is.na(as.character(config[1,2]))){
output$gatkUI1<-renderUI({textInput('gatk_folder',
'Variant calling results',
as.character(config[1,2]))})
output$gatkUI2<-renderUI({radioButtons('gatk_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[2,2]),
inline=TRUE)})
output$gatkUI3<-renderUI({
conditionalPanel(
condition="input.gatk_file_type=='.txt'",
numericInput('gatk_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[3,2])),
numericInput('gatk_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[4,2])),
numericInput('gatk_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[5,2])),
numericInput('gatk_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[6,2])))})
output$gatkUI4<-renderUI({textInput('gatk_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[7,2]))})
output$gatkUI5<-renderUI({radioButtons('gatk_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[8,2]),
inline = TRUE)})
output$gatkUI6<-renderUI({radioButtons('gatk_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[9,2]),
inline = TRUE)})
output$gatkUI7<-renderUI({conditionalPanel(
condition="input.gatk_snv_indel=='No'",
textInput('gatk_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[10,2])),
textInput('gatk_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[11,2])))})
output$gatkUI8<-renderUI({radioButtons('gatk_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[12,2]),
inline = TRUE)})
}
if(is.na(as.character(config[1,2]))){
output$gatkUI1<-renderUI({NULL})
output$gatkUI2<-renderUI({NULL})
output$gatkUI3<-renderUI({NULL})
output$gatkUI4<-renderUI({NULL})
output$gatkUI5<-renderUI({NULL})
output$gatkUI6<-renderUI({NULL})
output$gatkUI7<-renderUI({NULL})
output$gatkUI8<-renderUI({NULL})
}
if(!is.na(as.character(config[13,2]))){
output$platypusUI1<-renderUI({textInput('platypus_folder',
'Variant calling results',
as.character(config[13,2]))})
output$platypusUI2<-renderUI({radioButtons('platypus_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[14,2]),
inline=TRUE)})
output$platypusUI3<-renderUI({
conditionalPanel(
condition="input.platypus_file_type=='.txt'",
numericInput('platypus_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[15,2])),
numericInput('platypus_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[16,2])),
numericInput('platypus_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[17,2])),
numericInput('platypus_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[18,2])))})
output$platypusUI4<-renderUI({textInput('platypus_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[19,2]))})
output$platypusUI5<-renderUI({radioButtons('platypus_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[20,2]),
inline = TRUE)})
output$platypusUI6<-renderUI({radioButtons('platypus_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[21,2]),
inline = TRUE)})
output$platypusUI7<-renderUI({conditionalPanel(
condition="input.platypus_snv_indel=='No'",
textInput('platypus_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[22,2])),
textInput('platypus_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[23,2])))})
output$platypusUI8<-renderUI({radioButtons('platypus_indels',
'How are Indels reported?',
c("CA>C","C>-A","CAAAC>CAAC"),
selected=as.character(config[24,2]),
inline = TRUE)})
}
if(is.na(as.character(config[13,2]))){
output$platypusUI1<-renderUI({NULL})
output$platypusUI2<-renderUI({NULL})
output$platypusUI3<-renderUI({NULL})
output$platypusUI4<-renderUI({NULL})
output$platypusUI5<-renderUI({NULL})
output$platypusUI6<-renderUI({NULL})
output$platypusUI7<-renderUI({NULL})
output$platypusUI8<-renderUI({NULL})
}
if(!is.na(as.character(config[25,2]))){
output$varscanUI1<-renderUI({textInput('varscan_folder',
'Variant calling results',
as.character(config[25,2]))})
output$varscanUI2<-renderUI({radioButtons('varscan_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[26,2]),
inline=TRUE)})
output$varscanUI3<-renderUI({
conditionalPanel(
condition="input.varscan_file_type=='.txt'",
numericInput('varscan_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[27,2])),
numericInput('varscan_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[28,2])),
numericInput('varscan_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[29,2])),
numericInput('varscan_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[30,2])))})
output$varscanUI4<-renderUI({textInput('varscan_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[31,2]))})
output$varscanUI5<-renderUI({radioButtons('varscan_mnvs','MNVs reported?',
c("Yes","No"),
as.character(config[32,2]),
inline = TRUE)})
output$varscanUI6<-renderUI({radioButtons('varscan_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[33,2]),
inline = TRUE)})
output$varscanUI7<-renderUI({conditionalPanel(
condition="input.varscan_snv_indel=='No'",
textInput('varscan_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[34,2])),
textInput('varscan_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[35,2])))})
output$varscanUI8<-renderUI({radioButtons('varscan_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[36,2]),
inline = TRUE)})
}
if(is.na(as.character(config[25,2]))){
output$varscanUI1<-renderUI({NULL})
output$varscanUI2<-renderUI({NULL})
output$varscanUI3<-renderUI({NULL})
output$varscanUI4<-renderUI({NULL})
output$varscanUI5<-renderUI({NULL})
output$varscanUI6<-renderUI({NULL})
output$varscanUI7<-renderUI({NULL})
output$varscanUI8<-renderUI({NULL})
}
if(!is.na(as.character(config[37,2]))){
output$freebayesUI1<-renderUI({textInput('freebayes_folder',
'Variant calling results',
as.character(config[37,2]))})
output$freebayesUI2<-renderUI({radioButtons('freebayes_file_type',
"Output file type",
c(".vcf",
".txt"),
as.character(config[38,2]),
inline=TRUE)})
output$freebayesUI3<-renderUI({
conditionalPanel(
condition="input.freebayes_file_type=='.txt'",
numericInput('freebayes_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[39,2])),
numericInput('freebayes_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[40,2])),
numericInput('freebayes_ref'
,"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[41,2])),
numericInput('freebayes_alt'
,"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[42,2])))})
output$freebayesUI4<-renderUI({textInput('freebayes_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[43,2]))})
output$freebayesUI5<-renderUI({radioButtons('freebayes_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[44,2]),
inline = TRUE)})
output$freebayesUI6<-renderUI({radioButtons('freebayes_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[45,2]),
inline = TRUE)})
output$freebayesUI7<-renderUI({conditionalPanel(
condition="input.freebayes_snv_indel=='No'",
textInput('freebayes_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[46,2])),
textInput('freebayes_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[47,2])))})
output$freebayesUI8<-renderUI({radioButtons('freebayes_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[48,2]),
inline=TRUE)})
}
if(is.na(as.character(config[37,2]))){
output$freebayesUI1<-renderUI({NULL})
output$freebayesUI2<-renderUI({NULL})
output$freebayesUI3<-renderUI({NULL})
output$freebayesUI4<-renderUI({NULL})
output$freebayesUI5<-renderUI({NULL})
output$freebayesUI6<-renderUI({NULL})
output$freebayesUI7<-renderUI({NULL})
output$freebayesUI8<-renderUI({NULL})
}
if(!is.na(as.character(config[49,2]))){
output$lofreqUI1<-renderUI({textInput('lofreq_folder',
'Variant calling results',
as.character(config[49,2]))})
output$lofreqUI2<-renderUI({radioButtons('lofreq_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[50,2]),
inline=TRUE)})
output$lofreqUI3<-renderUI({
conditionalPanel(
condition="input.lofreq_file_type=='.txt'",
numericInput('lofreq_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[51,2])),
numericInput('lofreq_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[52,2])),
numericInput('lofreq_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[53,2])),
numericInput('lofreq_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[54,2])))})
output$lofreqUI4<-renderUI({textInput('lofreq_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[55,2]))})
output$lofreqUI5<-renderUI({radioButtons('lofreq_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[56,2]),
inline = TRUE)})
output$lofreqUI6<-renderUI({radioButtons('lofreq_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[57,2]),
inline = TRUE)})
output$lofreqUI7<-renderUI({conditionalPanel(
condition="input.lofreq_snv_indel=='No'",
textInput('lofreq_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[58,2])),
textInput('lofreq_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[59,2])))})
output$lofreqUI8<-renderUI({radioButtons('lofreq_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[60,2]),
inline = TRUE)})
}
if(is.na(as.character(config[49,2]))){
output$lofreqUI1<-renderUI({NULL})
output$lofreqUI2<-renderUI({NULL})
output$lofreqUI3<-renderUI({NULL})
output$lofreqUI4<-renderUI({NULL})
output$lofreqUI5<-renderUI({NULL})
output$lofreqUI6<-renderUI({NULL})
output$lofreqUI7<-renderUI({NULL})
output$lofreqUI8<-renderUI({NULL})
}
if(!is.na(as.character(config[61,2]))){
output$snverUI1<-renderUI({textInput('snver_folder',
'Variant calling results',
as.character(config[61,2]))})
output$snverUI2<-renderUI({radioButtons('snver_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[62,2]),
inline=TRUE)})
output$snverUI3<-renderUI({
conditionalPanel(
condition="input.snver_file_type=='.txt'",
numericInput('snver_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[63,2])),
numericInput('snver_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[64,2])),
numericInput('snver_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[65,2])),
numericInput('snver_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[66,2])))})
output$snverUI4<-renderUI({textInput('snver_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[67,2]))})
output$snverUI5<-renderUI({radioButtons('snver_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[68,2]),
inline = TRUE)})
output$snverUI6<-renderUI({radioButtons('snver_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[69,2]),
inline = TRUE)})
output$snverUI7<-renderUI({conditionalPanel(
condition="input.snver_snv_indel=='No'",
textInput('snver_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[70,2])),
textInput('snver_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[71,2])))})
output$snverUI8<-renderUI({radioButtons('snver_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[72,2]),
inline = TRUE)})
}
if(is.na(as.character(config[61,2]))){
output$snverUI1<-renderUI({NULL})
output$snverUI2<-renderUI({NULL})
output$snverUI3<-renderUI({NULL})
output$snverUI4<-renderUI({NULL})
output$snverUI5<-renderUI({NULL})
output$snverUI6<-renderUI({NULL})
output$snverUI7<-renderUI({NULL})
output$snverUI8<-renderUI({NULL})
}
if(!is.na(as.character(config[73,2]))){
output$samtoolsUI1<-renderUI({textInput('samtools_folder',
'Variant calling results',
as.character(config[73,2]))})
output$samtoolsUI2<-renderUI({radioButtons('samtools_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[74,2]),
inline=TRUE)})
output$samtoolsUI3<-renderUI({
conditionalPanel(
condition="input.samtools_file_type=='.txt'",
numericInput('samtools_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[75,2])),
numericInput('samtools_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[76,2])),
numericInput('samtools_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[77,2])),
numericInput('samtools_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[78,2])))})
output$samtoolsUI4<-renderUI({textInput('samtools_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[79,2]))})
output$samtoolsUI5<-renderUI({radioButtons('samtools_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[80,2]),
inline = TRUE)})
output$samtoolsUI6<-renderUI({radioButtons('samtools_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[81,2]),
inline = TRUE)})
output$samtoolsUI7<-renderUI({conditionalPanel(
condition="input.samtools_snv_indel=='No'",
textInput('samtools_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[82,2])),
textInput('samtools_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[83,2])))})
output$samtoolsUI8<-renderUI({radioButtons('samtools_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[84,2]),
inline = TRUE)})
}
if(is.na(as.character(config[73,2]))){
output$samtoolsUI1<-renderUI({NULL})
output$samtoolsUI2<-renderUI({NULL})
output$samtoolsUI3<-renderUI({NULL})
output$samtoolsUI4<-renderUI({NULL})
output$samtoolsUI5<-renderUI({NULL})
output$samtoolsUI6<-renderUI({NULL})
output$samtoolsUI7<-renderUI({NULL})
output$samtoolsUI8<-renderUI({NULL})
}
if(!is.na(as.character(config[85,2]))){
output$vardictUI1<-renderUI({textInput('vardict_folder',
'Variant calling results',
as.character(config[85,2]))})
output$vardictUI2<-renderUI({radioButtons('vardict_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[86,2]),
inline=TRUE)})
output$vardictUI3<-renderUI({
conditionalPanel(
condition="input.vardict_file_type=='.txt'",
numericInput('vardict_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[87,2])),
numericInput('vardict_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[88,2])),
numericInput('vardict_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[89,2])),
numericInput('vardict_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[90,2])))})
output$vardictUI4<-renderUI({textInput('vardict_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[91,2]))})
output$vardictUI5<-renderUI({radioButtons('vardict_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[92,2]),
inline = TRUE)})
output$vardictUI6<-renderUI({radioButtons('vardict_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[93,2]),
inline = TRUE)})
output$vardictUI7<-renderUI({conditionalPanel(
condition="input.vardict_snv_indel=='No'",
textInput('vardict_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[94,2])),
textInput('vardict_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[95,2])))})
output$vardictUI8<-renderUI({radioButtons('vardict_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[96,2]),
inline = TRUE)})
}
if(is.na(as.character(config[85,2]))){
output$vardictUI1<-renderUI({NULL})
output$vardictUI2<-renderUI({NULL})
output$vardictUI3<-renderUI({NULL})
output$vardictUI4<-renderUI({NULL})
output$vardictUI5<-renderUI({NULL})
output$vardictUI6<-renderUI({NULL})
output$vardictUI7<-renderUI({NULL})
output$vardictUI8<-renderUI({NULL})
}
if(!is.na(as.character(config[97,2]))){
output$caller1UI0<-renderUI({h4(as.character(config[97,2]))})
output$caller1UI0.1<-renderUI({textInput('caller1_name',
'Name of caller 1',
as.character(config[98,2]))})
output$caller1UI1<-renderUI({textInput('caller1_folder',
'Variant calling results',
as.character(config[99,2]))})
output$caller1UI2<-renderUI({radioButtons('caller1_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[100,2]),
inline=TRUE)})
output$caller1UI3<-renderUI({
conditionalPanel(
condition="input.caller1_file_type=='.txt'",
numericInput('caller1_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[101,2])),
numericInput('caller1_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[102,2])),
numericInput('caller1_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[103,2])),
numericInput('caller1_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[104,2])))})
output$caller1UI4<-renderUI({textInput('caller1_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[105,2]))})
output$caller1UI5<-renderUI({radioButtons('caller1_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[106,2]),
inline = TRUE)})
output$caller1UI6<-renderUI({radioButtons('caller1_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[107,2]),
inline = TRUE)})
output$caller1UI7<-renderUI({conditionalPanel(
condition="input.caller1_snv_indel=='No'",
textInput('caller1_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[108,2])),
textInput('caller1_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[109,2])))})
output$caller1UI8<-renderUI({radioButtons('caller1_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[110,2]),
inline = TRUE)})
}
if(is.na(as.character(config[97,2]))){
output$caller1UI0<-renderUI({NULL})
output$caller1UI0.1<-renderUI({NULL})
output$caller1UI1<-renderUI({NULL})
output$caller1UI2<-renderUI({NULL})
output$caller1UI3<-renderUI({NULL})
output$caller1UI4<-renderUI({NULL})
output$caller1UI5<-renderUI({NULL})
output$caller1UI6<-renderUI({NULL})
output$caller1UI7<-renderUI({NULL})
output$caller1UI8<-renderUI({NULL})
}
if(!is.na(as.character(config[111,2]))){
output$caller2UI0<-renderUI({h4(as.character(config[111,2]))})
output$caller2UI0.1<-renderUI({textInput('caller2_name',
'Name of caller 1',
as.character(config[112,2]))})
output$caller2UI1<-renderUI({textInput('caller2_folder',
'Variant calling results',
as.character(config[113,2]))})
output$caller2UI2<-renderUI({radioButtons('caller2_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[114,2]),
inline=TRUE)})
output$caller2UI3<-renderUI({
conditionalPanel(
condition="input.caller2_file_type=='.txt'",
numericInput('caller2_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[115,2])),
numericInput('caller2_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[116,2])),
numericInput('caller2_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[117,2])),
numericInput('caller2_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[118,2])))})
output$caller2UI4<-renderUI({textInput('caller2_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[119,2]))})
output$caller2UI5<-renderUI({radioButtons('caller2_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[120,2]),
inline = TRUE)})
output$caller2UI6<-renderUI({radioButtons('caller2_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[121,2]),
inline = TRUE)})
output$caller2UI7<-renderUI({conditionalPanel(
condition="input.caller2_snv_indel=='No'",
textInput('caller2_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[122,2])),
textInput('caller2_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[123,2])))})
output$caller2UI8<-renderUI({radioButtons('caller2_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[124,2]),
inline = TRUE)})
}
if(is.na(as.character(config[111,2]))){
output$caller2UI0<-renderUI({NULL})
output$caller2UI0.1<-renderUI({NULL})
output$caller2UI1<-renderUI({NULL})
output$caller2UI2<-renderUI({NULL})
output$caller2UI3<-renderUI({NULL})
output$caller2UI4<-renderUI({NULL})
output$caller2UI5<-renderUI({NULL})
output$caller2UI6<-renderUI({NULL})
output$caller2UI7<-renderUI({NULL})
output$caller2UI8<-renderUI({NULL})
}
if(!is.na(as.character(config[125,2]))){
output$caller3UI0<-renderUI({h4(as.character(config[125,2]))})
output$caller3UI0.1<-renderUI({textInput('caller3_name',
'Name of caller 1',
as.character(config[126,2]))})
output$caller3UI1<-renderUI({textInput('caller3_folder',
'Variant calling results',
as.character(config[127,2]))})
output$caller3UI2<-renderUI({radioButtons('caller3_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[128,2]),
inline=TRUE)})
output$caller3UI3<-renderUI({
conditionalPanel(
condition="input.caller3_file_type=='.txt'",
numericInput('caller3_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[129,2])),
numericInput('caller3_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[130,2])),
numericInput('caller3_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[131,2])),
numericInput('caller3_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[132,2])))})
output$caller3UI4<-renderUI({textInput('caller3_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[133,2]))})
output$caller3UI5<-renderUI({radioButtons('caller3_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[134,2]),
inline = TRUE)})
output$caller3UI6<-renderUI({radioButtons('caller3_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[135,2]),
inline = TRUE)})
output$caller3UI7<-renderUI({conditionalPanel(
condition="input.caller3_snv_indel=='No'",
textInput('caller3_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[136,2])),
textInput('caller3_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[137,2])))})
output$caller3UI8<-renderUI({radioButtons('caller3_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[138,2]),
inline = TRUE)})
}
if(is.na(as.character(config[125,2]))){
output$caller3UI0<-renderUI({NULL})
output$caller3UI0.1<-renderUI({NULL})
output$caller3UI1<-renderUI({NULL})
output$caller3UI2<-renderUI({NULL})
output$caller3UI3<-renderUI({NULL})
output$caller3UI4<-renderUI({NULL})
output$caller3UI5<-renderUI({NULL})
output$caller3UI6<-renderUI({NULL})
output$caller3UI7<-renderUI({NULL})
output$caller3UI8<-renderUI({NULL})
}
if(!is.na(as.character(config[139,2]))){
output$caller4UI0<-renderUI({h4(as.character(config[139,2]))})
output$caller4UI0.1<-renderUI({textInput('caller4_name',
'Name of caller 1',
as.character(config[140,2]))})
output$caller4UI1<-renderUI({textInput('caller4_folder',
'Variant calling results',
as.character(config[141,2]))})
output$caller4UI2<-renderUI({radioButtons('caller4_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[142,2]),
inline=TRUE)})
output$caller4UI3<-renderUI({
conditionalPanel(
condition="input.caller4_file_type=='.txt'",
numericInput('caller4_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[143,2])),
numericInput('caller4_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[144,2])),
numericInput('caller4_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[145,2])),
numericInput('caller4_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[146,2])))})
output$caller4UI4<-renderUI({textInput('caller4_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[147,2]))})
output$caller4UI5<-renderUI({radioButtons('caller4_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[148,2]),
inline = TRUE)})
output$caller4UI6<-renderUI({radioButtons('caller4_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[149,2]),
inline = TRUE)})
output$caller4UI7<-renderUI({conditionalPanel(
condition="input.caller4_snv_indel=='No'",
textInput('caller4_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[150,2])),
textInput('caller4_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[151,2])))})
output$caller4UI8<-renderUI({radioButtons('caller4_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[152,2]),
inline = TRUE)})
}
if(is.na(as.character(config[139,2]))){
output$caller4UI0<-renderUI({NULL})
output$caller4UI0.1<-renderUI({NULL})
output$caller4UI1<-renderUI({NULL})
output$caller4UI2<-renderUI({NULL})
output$caller4UI3<-renderUI({NULL})
output$caller4UI4<-renderUI({NULL})
output$caller4UI5<-renderUI({NULL})
output$caller4UI6<-renderUI({NULL})
output$caller4UI7<-renderUI({NULL})
output$caller4UI8<-renderUI({NULL})
}
if(!is.na(as.character(config[153,2]))){
output$caller5UI0<-renderUI({h4(as.character(config[153,2]))})
output$caller5UI0.1<-renderUI({textInput('caller5_name',
'Name of caller 1',
as.character(config[154,2]))})
output$caller5UI1<-renderUI({textInput('caller5_folder',
'Variant calling results',
as.character(config[155,2]))})
output$caller5UI2<-renderUI({radioButtons('caller5_file_type',
"Output file type",
c(".vcf",".txt"),
as.character(config[156,2]),
inline=TRUE)})
output$caller5UI3<-renderUI({
conditionalPanel(
condition="input.caller5_file_type=='.txt'",
numericInput('caller5_chr',
"In which column do you find Chr?",
min = 1,max=20,
value=as.numeric(config[157,2])),
numericInput('caller5_pos',
"In which column do you find Pos?",
min = 1,max=20,
value=as.numeric(config[158,2])),
numericInput('caller5_ref',
"In which column do you find Ref?",
min = 1,max=20,
value=as.numeric(config[159,2])),
numericInput('caller5_alt',
"In which column do you find Alt?",
min = 1,max=20,
value=as.numeric(config[160,2])))})
output$caller5UI4<-renderUI({textInput('caller5_file_names_add',
'Suffix for naming output? (e.g. \'_rawCalls\' for \'Sample1_rawCalls.vcf)\'',
as.character(config[161,2]))})
output$caller5UI5<-renderUI({radioButtons('caller5_mnvs',
'MNVs reported?',
c("Yes","No"),
as.character(config[162,2]),
inline = TRUE)})
output$caller5UI6<-renderUI({radioButtons('caller5_snv_indel',
'SNVs and Indels reported in one file?',
c("Yes","No"),
as.character(config[163,2]),
inline = TRUE)})
output$caller5UI7<-renderUI({conditionalPanel(
condition="input.caller5_snv_indel=='No'",
textInput('caller5_snv_names_add',
'Suffix for SNV files? (e.g. \'_SNVs\' for \'Sample1_SNVs.vcf\')',
as.character(config[164,2])),
textInput('caller5_indel_names_add',
'Suffix for Indel files? (e.g. \'_Indels\' for \'Sample1_Indels.vcf\')',
as.character(config[165,2])))})
output$caller5UI8<-renderUI({radioButtons('caller5_indels',
'How are Indels reported?',
c("CA>C","C>-A",
"CAAAC>CAAC"),
selected=as.character(config[166,2]),
inline = TRUE)})
}
if(is.na(as.character(config[153,2]))){
output$caller5UI0<-renderUI({NULL})
output$caller5UI0.1<-renderUI({NULL})
output$caller5UI1<-renderUI({NULL})
output$caller5UI2<-renderUI({NULL})
output$caller5UI3<-renderUI({NULL})
output$caller5UI4<-renderUI({NULL})
output$caller5UI5<-renderUI({NULL})
output$caller5UI6<-renderUI({NULL})
output$caller5UI7<-renderUI({NULL})
output$caller5UI8<-renderUI({NULL})
}
if(!is.na(as.character(config[167,2]))){
output$locationsUI<-renderUI({checkboxGroupInput("locations",
"What are the locations you are interested in?",
c("coding",
"intron",
"threeUTR",
"fiveUTR",
"intergenic",
"spliceSite",
"promoter"),
strsplit(as.character(config[167,2]),split=",")[[1]],
inline=TRUE)})
}
if(is.na(as.character(config[167,2]))){
output$locationsUI<-renderUI({checkboxGroupInput("locations",
"What are the locations you are interested in?",
c("coding",
"intron",
"threeUTR",
"fiveUTR",
"intergenic",
"spliceSite",
"promoter"),
c("coding"),
inline=TRUE)})
}
if(!is.na(as.character(config[168,2]))){
output$consequencesUI<-renderUI({checkboxGroupInput("consequences",
"What kind of variants are you interested in? (coding only)",
c("synonymous",
"nonsynonymous",
"frameshift",
"nonsense",
"not translated"),
strsplit(as.character(config[168,2]),split=",")[[1]],
inline=TRUE)})
}
if(is.na(as.character(config[168,2]))){
output$consequencesUI<-renderUI({checkboxGroupInput("consequences",
"What kind of variants are you interested in? (coding only)",
c("synonymous",
"nonsynonymous",
"frameshift",
"nonsense","not translated"),
c("nonsynonymous",
"frameshift",
"nonsense"),
inline=TRUE)})
}
output$bam_folderUI<-renderUI({textInput('bam_folder',
'Define folder containing bam- and bai files',
as.character(config[169,2]))})
output$dpUI<-renderUI({numericInput("dp",
"Minimum coverage [10;9999]",
value=as.numeric(config[170,2]),
min=10,max=9999)})
output$nr_altUI<-renderUI({numericInput("nr_alt",
"Minimum number of reads carrying the alternate allele [3;9999]",
value=as.numeric(config[171,2]),
min=3,max=9999)})
output$vafUI<-renderUI({sliderInput("vaf",
"Minimum allele frequency [%]",
min=1,max=100,
value=as.numeric(config[172,2]))})
output$bqUI<-renderUI({numericInput("bq",
"Minimum base quality [0;36]",
value=as.numeric(config[173,2]),
min=0,max=36)})
output$bq_diffUI<-renderUI({numericInput("bq_diff",
"Maximum difference between Ref_BQ and Alt_BQ [0;36]",
value=as.numeric(config[174,2]),
min=0,max=36)})
output$dbSNPUI<-renderUI({checkboxInput("dbSNP",
"Consider dbSNP? (Hsapiens.dbSNP144.GRCh37 and XtraSNPlocs.Hsapiens.dbSNP144.GRCh37)",
value=as.character(config[175,2])=="TRUE")})
output$"1kgenomesUI"<-renderUI({checkboxInput("1kgenomes",
"Consider 1000 Genomes? (MafDb.1Kgenomes.phase3.hs37d5)",
value=as.character(config[176,2])=="TRUE")})
output$exacUI<-renderUI({checkboxInput("exac",
"Consider ExAC? (MafDb.ExAC.r1.0.hs37d5)",
value=as.character(config[177,2])=="TRUE")})
output$gadUI<-renderUI({checkboxInput("gad",
"Consider Genome Aggregation Database? (MafDb.gnomADex.r2.1.hs37d5)",
value=as.character(config[179,2])=="TRUE")})
output$cosmicUI<-renderUI({checkboxInput("cosmic",
"Consider COSMIC? (COSMIC.67)",
value=as.character(config[180,2])=="TRUE")})
output$clinvarUI<-renderUI({checkboxInput("clinvar",
"Consider ClinVar? (rentrez)",
value=as.character(config[181,2])=="TRUE")})
output$predictUI<-renderUI({radioButtons("predict",
"What source would you like to use for impact prediction?",
c("SIFT","Provean","PolyPhen2"),
as.character(config[182,2]),
inline=TRUE)})
output$stricter_thresholdsUI<-renderUI({radioButtons('stricter_thresholds',
"Do you want to define stricter thresholds for coverage and base quality?",
c("Yes",
"No"),
as.character(config[183,2]),
inline=TRUE)})
if(as.character(config[183,2])=="Yes"){
output$stricter_thresholdsUI2<-renderUI({conditionalPanel(
condition="input.stricter_thresholds=='Yes'",
numericInput("dp2","Minimum coverage [10;9999]",
value=as.numeric(config[184,2]),
min=10,max=9999),
numericInput("nr_alt2",
"Minimum number of reads carrying the alternate allele [3;9999]",
value=as.numeric(config[185,2]),
min=3,max=9999),
sliderInput("vaf2","Minimum allele frequency [%]",
min=1,max=100,
value=as.numeric(config[186,2])),
numericInput("bq2","Minimum base quality [0;36]",
value=as.numeric(config[187,2]),
min=0,max=36),
numericInput("bq_diff2",
"Maximum difference between Ref_BQ and Alt_BQ [0;36]",
value=as.numeric(config[188,2]),
min=0,max=36)
)})
}
if(as.character(config[183,2]=="No")){
output$stricter_thresholdsUI2<-renderUI({NULL})
}
output$nr_samplesUI<-renderUI({numericInput("nr_samples",
"Detection in more than how many samples makes a call striking?",
value=as.numeric(config[189,2]),
min=1,max=9999)})
if(as.character(config[182,2])=="SIFT"){
output$predictionUI1<-renderUI({conditionalPanel(
condition="input.predict=='SIFT'",
sliderInput("damaging_safe1",
"SIFT: When is a damaging prediction reliable? (internal threshold <=0.05)",
min=0,max=1.0,
value=as.numeric(config[190,2])),
sliderInput("tolerated_safe1",
"SIFT: When is a tolerated prediction reliable? (internal threshold >0.05)",
min=0,max=1.0,
value=as.numeric(config[191,2]))
)})
}
if(as.character(config[182,2])!="SIFT"){
output$predictionUI1<-renderUI({NULL})
}
if(as.character(config[182,2])=="Provean"){
output$predictionUI2<-renderUI({conditionalPanel(
condition="input.predict=='Provean'",
sliderInput("damaging_safe2",
"Provean: When is a damaging prediction reliable? (internal threshold <=-2.5)",
min=-20,max=10,
value=as.numeric(config[192,2])),
sliderInput("tolerated_safe2",
"Provean: When is a tolerated prediction reliable? (internal threshold >-2.5)",
min=-20,max=10,
value=as.numeric(config[193,2]))
)})
}
if(as.character(config[182,2])!="Provean"){
output$predictionUI2<-renderUI({NULL})
}
if(as.character(config[182,2])=="PolyPhen2"){
output$predictionUI1<-renderUI({conditionalPanel(
condition="input.predict=='PolyPhen2'",
sliderInput("damaging_safe3",
"PolyPhen2: When is a damaging prediction reliable? (>=0.5)",
min=0,max=1,
value=as.numeric(config[194,2])),
sliderInput("tolerated_safe3",
"PolyPhen2: When is a tolerated prediction reliable? (<0.5)",
min=0,max=1,
value=as.numeric(config[195,2]))
)})
}
if(as.character(config[182,2])!="PolyPhen2"){
output$predictionUI3<-renderUI({NULL})
}
output$artifact_scoreUI<-renderUI({radioButtons('artifact_score',
"Would you like to change the default scoring for the artifact score?",
c("Yes","No"),
config[196,2],
inline=TRUE)})
if(as.character(config[196,2])=="Yes"){
output$artifact_scoreUI2<-renderUI({conditionalPanel(
condition="input.artifact_score=='Yes'",
h4(as.character(config[197,2])),
h5(as.character(config[198,2])),
h5(as.character(config[199,2])),
sliderInput("PolymorphismVAF10",
"Polymorphism (based on polymorphism score) AND VAF<10%",
min=-5,max=5,
value=as.numeric(config[200,2])),
sliderInput("BQ_AltMean",
"BQ_Alt<(mean(BQ_Alt)-3*sd(BQ_Alt))",
min=-5,max=5,
value=as.numeric(config[201,2])),
sliderInput("detectedHigh",
"Detected in >50% of all samples",
min=-5,max=5,
value=as.numeric(config[202,2])),
sliderInput("detectedLow",
"Detected in a striking number of samples",
min=-5,max=5,
value=as.numeric(config[203,2])),
sliderInput("detectedLowVAF",
"Detected in a striking number of samples AND VAF>85%",
min=-5,max=5,
value=as.numeric(config[204,2])),
sliderInput("vafLow","VAF<2%",min=-5,max=5,
value=as.numeric(config[205,2])),
sliderInput("PolymorphismVAF20",
"Polymorphism (based on polymorphism score) AND VAF<20%",
min=-5,max=5,
value=as.numeric(config[206,2])),
sliderInput("PolymorphismFrame",
"Polymorphism (based on polymorphism score) AND frameshift",
min=-5,max=5,
value=as.numeric(config[207,2])),
sliderInput("isIndel","Indel",min=-5,max=5,
value=as.numeric(config[208,2])),
sliderInput("isIndelVAF",
"Indel AND VAF<5%",min=-5,max=5,
value=as.numeric(config[209,2])),
sliderInput("noPrimerP",
"No primer (information) AND p<0.001",
min=-5,max=5,
value=as.numeric(config[210,2])),
sliderInput("noPrimerPFwd",
"No primer (information) AND p>=0.001 AND Nr_Ref_fwd>=(Min_DP-Min_Alt)/2 AND Nr_Alt_fwd<=2",
min=-5,max=5,
value=as.numeric(config[211,2])),
sliderInput("noPrimerPRev",
"No primer (information) AND p>=0.001 AND Nr_Ref_rev>=(Min_DP-Min_Alt)/2 AND Nr_Alt_rev<=2",
min=-5,max=5,
value=as.numeric(config[212,2])),
sliderInput("databaseVAF",
"No database AND VAF<10%",
min=-5,max=5,
value=as.numeric(config[213,2])),
sliderInput("databaseHigh",
"No database AND detected in >50% of all samples",
min=-5,max=5,
value=as.numeric(config[214,2])),
sliderInput("predictionVAF",
"Reliable tolerated prediction AND (VAF<35% OR 65%<VAF<85%)",
min=-5,max=5,
value=as.numeric(config[215,2])),
sliderInput("oneCaller",
"Reported by only 1 caller",
min=-5,max=5,
value=as.numeric(config[216,2])),
sliderInput("primerLocation",
"Primer-location",
min=-5,max=5,
value=as.numeric(config[217,2])),
sliderInput("primerPAlt",
"No primer (information) AND p<0.001 AND Nr_Alt_rev>=Min_Alt/2 AND Nr_Alt_rev>=Min_Alt/2",
min=-5,max=5,
value=as.numeric(config[218,2])),
sliderInput("primerPFwd",
"No primer (information) AND p<0.001 AND Nr_Ref_fwd<(Min_DP-Min_Alt)/2 AND Nr_Alt_fwd<=2",
min=-5,max=5,
value=as.numeric(config[219,2])),
sliderInput("primerPRev",
"No primer (information) AND p<0.001 AND Nr_Ref_rev<(Min_DP-Min_Alt)/2 AND Nr_Alt_rev<=2",
min=-5,max=5,
value=as.numeric(config[220,2])),
sliderInput("predictionSafe",
"Reliable damaging prediction",
min=-5,max=5,
value=as.numeric(config[221,2])),
numericInput("nrcaller4",
"Intermediate number of callers to report the same variant [1;14]",
min=1,max=14,
value=as.numeric(config[222,2])),
sliderInput("reward4","Score",min=-5,max=5,
value=as.numeric(config[223,2])),
numericInput("nrcaller5",
"High number of callers to report the same variant [1;14]",
min=1,max=14,value=as.numeric(config[224,2])),
sliderInput("reward5","Score",min=-5,max=5,
value=as.numeric(config[225,2])),
numericInput("nrcaller6",
"Very high number of callers to report the same variant [1;14]",
min=1,max=14,
value=as.numeric(config[226,2])),
sliderInput("reward6","Score",min=-5,max=5,
value=as.numeric(config[227,2])),
sliderInput("knownHotspot","Known hotspot",min=-5,max=5,
value=as.numeric(config[228,2])),
checkboxGroupInput("overlapTools","Overlapping output by which tools shall be rewarded?",
choices=c("GATK","Platypus","VarScan","LoFreq","FreeBayes","SNVer","SamTools","VarDict",
"Caller1","Caller2","Caller3","Caller4","Caller5"),
selected=strsplit(as.character(config[229,2]),split=",")[[1]],
inline=TRUE),
sliderInput("overlapReward","Score",min=-5,max=5,
value=as.numeric(config[230,2])),
hr(),
sliderInput("artifactThreshold",
"Threshold artifact score (still artifact)",
min=-10,max=10,
value=as.numeric(config[231,2]))
)})
}
if(as.character(config[196,2])=="No"){
output$artifact_scoreUI2<-renderUI({NULL})
}
output$polymorphism_scoreUI<-renderUI({radioButtons('polymorphism_score',
"Would you like to change the default scoring for the polymorphism score?",
c("Yes","No"),
config[232,2],
inline=TRUE)})
if(as.character(config[232,2])=="Yes"){
output$polymorphism_scoreUI2<-renderUI({conditionalPanel(
condition="input.polymorphism_score=='Yes'",
h4(as.character(config[233,2])),
h5(as.character(config[234,2])),
h5(as.character(config[235,2])),
sliderInput("polyDetected",
"Detected in a striking number of samples",
min=-5,max=5,
value=as.numeric(config[236,2])),
numericInput("polyDatabases",
"High number of databases to have information on a variant [1;8]",
min=1,max=8,
value=as.numeric(config[237,2])),
sliderInput("polyDatabasesReward","Score",
min=-5,max=5,
value=as.numeric(config[238,2])),
numericInput("polyDatabasesPolyLow",
"Intermediate number of polymorphism databases to have information on a variant [1;8]",
min=1,max=8,
value=as.numeric(config[239,2])),
sliderInput("polyDatabasesPolyLowReward",
"Score",min=-5,max=5,
value=as.numeric(config[240,2])),
numericInput("polyDatabasesPolyHigh",
"High number of polymorphism databases to have information on a variant [1;8]",
min=1,max=8,
value=as.numeric(config[241,2])),
sliderInput("polyDatabasesPolyHighReward","Score",
min=-5,max=5,
value=as.numeric(config[242,2])),
sliderInput("polyVAF","35%<=VAF>=65% OR 85%<=VAF",
min=-5,max=5,
value=as.numeric(config[243,2])),
sliderInput("polyPrediction",
"Reliable tolerated prediction",
min=-5,max=5,
value=as.numeric(config[244,2])),
sliderInput("polyEffect",
"No frameshift AND no stop gained AND no stop lost",
min=-5,max=5,
value=as.numeric(config[245,2])),
sliderInput("polyDetectedOnce",
"Reported by only 1 caller",min=-5,max=5,
value=as.numeric(config[246,2])),
numericInput("polyDatabasesMut",
"Critical number of mutation databases to have information on a variant [1;8]",
min=1,max=8,
value=as.numeric(config[247,2])),
sliderInput("polyDatabasesMutReward","Score",
min=-5,max=5,
value=as.numeric(config[248,2])),
sliderInput("polyNoDatabase",
"Not detected in any polymorphism database",
min=-5,max=5,
value=as.numeric(config[249,2])),
sliderInput("polyPredictionEffect",
"Reliable damaging prediction OR stop gained OR stop lost",
min=-5,max=5,
value=as.numeric(config[250,2])),
numericInput("polyCosmic",
"Critical number of Cosmic entries [1;1000]",
min=1,max=1000,
value=as.numeric(config[251,2])),
hr(),
sliderInput("polyThresholdCritical",
"Threshold polymorphism score if number of Cosmic entries is not critical (still polymorphism)",
min=-10,max=10,
value=as.numeric(config[252,2])),
sliderInput("polyThreshold",
"Threshold polymorphism score if number of Cosmic entries is critical (still polymorphism)",
min=-10,max=10,
value=as.numeric(config[253,2]))
)})
}
if(as.character(config[232,2])=="No"){
output$polymorphism_scoreUI2<-renderUI({NULL})
}
output$messageUI2<-renderUI({h5("Done. Please make sure that everything is correct.")})
return()
})
observeEvent(input$appreci8R,{
log_info<-c()
log_info[1]<-"Starting analysis with the appreci8R...<br><br>"
output$log_info<-renderUI({HTML(log_info)})
#check if input really exists
if(file.exists(input$output_folder)==FALSE){
log_info<-c(log_info,
"Your output folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$gatk_folder)&&
file.exists(input$gatk_folder)==FALSE){
log_info<-c(log_info,
"You want to analyze GATK output, but the folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$platypus_folder)&&
file.exists(input$platypus_folder)==FALSE){
log_info<-c(log_info,
"You want to analyze Platypus output, but the folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$varscan_folder)&&
file.exists(input$varscan_folder)==FALSE){
log_info<-c(log_info,
"You want to analyze VarScan output, but the folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$freebayes_folder)&&
file.exists(input$freebayes_folder)==FALSE){
log_info<-c(log_info,"You want to analyze FreeBayes output, but the folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$lofreq_folder)&&
file.exists(input$lofreq_folder)==FALSE){
log_info<-c(log_info,
"You want to analyze LoFreq output, but the folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$snver_folder)&&
file.exists(input$snver_folder)==FALSE){
log_info<-c(log_info,
"You want to analyze SNVer output, but the folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$samtools_folder)&&
file.exists(input$samtools_folder)==FALSE){
log_info<-c(log_info,
"You want to analyze SamTools output, but the folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$vardict_folder)&&
file.exists(input$vardict_folder)==FALSE){
log_info<-c(log_info,
"You want to analyze VarDict output, but the folder does not exist<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
#test additional callers
if(input$nr_additional>0&&!is.null(input$caller1_folder)&&
file.exists(input$caller1_folder)==FALSE){
log_info<-c(log_info,paste("The output folder of ",
input$caller1_name,
" does not exist<br>",sep=""))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(input$nr_additional>1&&!is.null(input$caller2_folder)&&
file.exists(input$caller2_folder)==FALSE){
log_info<-c(log_info,paste("The output folder of ",
input$caller1_name,
" does not exist<br>",sep=""))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(input$nr_additional>2&&!is.null(input$caller3_folder)&&
file.exists(input$caller3_folder)==FALSE){
log_info<-c(log_info,paste("The output folder of ",
input$caller1_name,
" does not exist<br>",sep=""))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(input$nr_additional>3&&!is.null(input$caller4_folder)&&
file.exists(input$caller4_folder)==FALSE){
log_info<-c(log_info,paste("The output folder of ",
input$caller1_name,
" does not exist<br>",sep=""))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(input$nr_additional>4&&!is.null(input$caller5_folder)&&
file.exists(input$caller5_folder)==FALSE){
log_info<-c(log_info,paste("The output folder of ",
input$caller1_name,
" does not exist<br>",sep=""))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(is.null(input$gatk_folder)&&is.null(input$platypus_folder)&&
is.null(input$varscan_folder)&&
is.null(input$freebayes_folder)
&&is.null(input$lofreq_folder)&&is.null(input$snver_folder)&&
is.null(input$samtools_folder)&&is.null(input$vardict_folder)
&&(input$nr_additional==0||
(input$nr_additional>0&&sum(!is.null(input$caller1_folder),
!is.null(input$caller2_folder),
!is.null(input$caller3_folder),
!is.null(input$caller4_folder),
!is.null(input$caller5_folder))!=input$nr_additional))){
log_info<-c(log_info,
"Please select at least one variant caller<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
#1. Reading Input
log_info<-c(log_info,"0. Reading input<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "0. Reading input", value = 0)
raw_calls<-list()
overview<-data.frame(SampleID=NA,GATK=NA,Platypus=NA,VarScan=NA,
FreeBayes=NA,LoFreq=NA,SNVer=NA,
SamTools=NA,VarDict=NA)
if(!is.null(input$caller1_name)){
namen_overview<-names(overview)
overview<-cbind(overview,New=NA)
names(overview)<-c(namen_overview,input$caller1_name)
}
if(!is.null(input$caller2_name)){
namen_overview<-names(overview)
overview<-cbind(overview,New=NA)
names(overview)<-c(namen_overview,input$caller2_name)
}
if(!is.null(input$caller3_name)){
namen_overview<-names(overview)
overview<-cbind(overview,New=NA)
names(overview)<-c(namen_overview,input$caller3_name)
}
if(!is.null(input$caller4_name)){
namen_overview<-names(overview)
overview<-cbind(overview,New=NA)
names(overview)<-c(namen_overview,input$caller4_name)
}
if(!is.null(input$caller5_name)){
namen_overview<-names(overview)
overview<-cbind(overview,New=NA)
names(overview)<-c(namen_overview,input$caller5_name)
}
included_callers<-rep(NA,13)
progress$inc(1/13)
raw_calls[[1]]<-list()
if(!is.null(input$gatk_folder)){
included_callers[1]<-"GATK"
raw_calls[[1]]<-readInput(input$gatk_folder,
input$gatk_file_names_add,
input$gatk_file_type,
input$gatk_snv_indel,
input$gatk_snv_names_add,
input$gatk_indel_names_add,
input$gatk_chr,input$gatk_pos,
input$gatk_ref,input$gatk_alt)
sampleNameTest<-getSampleNames(input$gatk_folder,
input$gatk_file_names_add,
input$gatk_file_type,
input$gatk_snv_indel,
input$gatk_snv_names_add,
input$gatk_indel_names_add)
}
if(is.null(input$gatk_folder)){
sampleNameTest<-NA
}
progress$inc(1/13)
raw_calls[[2]]<-list()
if(!is.null(input$platypus_folder)){
included_callers[2]<-"Platypus"
raw_calls[[2]]<-readInput(input$platypus_folder,
input$platypus_file_names_add,
input$platypus_file_type,
input$platypus_snv_indel,
input$platypus_snv_names_add,
input$platypus_indel_names_add,
input$platypus_chr,
input$platypus_pos,
input$platypus_ref,
input$platypus_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$platypus_folder,
input$platypus_file_names_add,
input$platypus_file_type,
input$platypus_snv_indel,
input$platypus_snv_names_add,
input$platypus_indel_names_add))
}
progress$inc(1/13)
raw_calls[[3]]<-list()
if(!is.null(input$varscan_folder)){
included_callers[3]<-"VarScan"
raw_calls[[3]]<-readInput(input$varscan_folder,
input$varscan_file_names_add,
input$varscan_file_type,
input$varscan_snv_indel,
input$varscan_snv_names_add,
input$varscan_indel_names_add,
input$varscan_chr,
input$varscan_pos,
input$varscan_ref,
input$varscan_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$varscan_folder,
input$varscan_file_names_add,
input$varscan_file_type,
input$varscan_snv_indel,
input$varscan_snv_names_add,
input$varscan_indel_names_add))
}
progress$inc(1/13)
raw_calls[[4]]<-list()
if(!is.null(input$freebayes_folder)){
included_callers[4]<-"FreeBayes"
raw_calls[[4]]<-readInput(input$freebayes_folder,
input$freebayes_file_names_add
,input$freebayes_file_type,
input$freebayes_snv_indel,
input$freebayes_snv_names_add,
input$freebayes_indel_names_add,
input$freebayes_chr,
input$freebayes_pos,
input$freebayes_ref,
input$freebayes_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$freebayes_folder,
input$freebayes_file_names_add,
input$freebayes_file_type,
input$freebayes_snv_indel,
input$freebayes_snv_names_add,
input$freebayes_indel_names_add))
}
progress$inc(1/13)
raw_calls[[5]]<-list()
if(!is.null(input$lofreq_folder)){
included_callers[5]<-"LoFreq"
raw_calls[[5]]<-readInput(input$lofreq_folder,
input$lofreq_file_names_add,
input$lofreq_file_type,
input$lofreq_snv_indel,
input$lofreq_snv_names_add,
input$lofreq_indel_names_add,
input$lofreq_chr,
input$lofreq_pos,
input$lofreq_ref,
input$lofreq_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$lofreq_folder,
input$lofreq_file_names_add,
input$lofreq_file_type,
input$lofreq_snv_indel,
input$lofreq_snv_names_add,
input$lofreq_indel_names_add))
}
progress$inc(1/13)
raw_calls[[6]]<-list()
if(!is.null(input$snver_folder)){
included_callers[6]<-"SNVer"
raw_calls[[6]]<-readInput(input$snver_folder,
input$snver_file_names_add,
input$snver_file_type,
input$snver_snv_indel,
input$snver_snv_names_add,
input$snver_indel_names_add,
input$snver_chr,
input$snver_pos,
input$snver_ref,input$snver_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$snver_folder,
input$snver_file_names_add,
input$snver_file_type,
input$snver_snv_indel,
input$snver_snv_names_add,
input$snver_indel_names_add))
}
progress$inc(1/13)
raw_calls[[7]]<-list()
if(!is.null(input$samtools_folder)){
included_callers[7]<-"SamTools"
raw_calls[[7]]<-readInput(input$samtools_folder,
input$samtools_file_names_add,
input$samtools_file_type,
input$samtools_snv_indel,
input$samtools_snv_names_add,
input$samtools_indel_names_add,
input$samtools_chr,
input$samtools_pos,
input$samtools_ref,
input$samtools_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$samtools_folder,
input$samtools_file_names_add,
input$samtools_file_type,
input$samtools_snv_indel,
input$samtools_snv_names_add,
input$samtools_indel_names_add))
}
progress$inc(1/13)
raw_calls[[8]]<-list()
if(!is.null(input$vardict_folder)){
included_callers[8]<-"VarDict"
raw_calls[[8]]<-readInput(input$vardict_folder,
input$vardict_file_names_add,
input$vardict_file_type,
input$vardict_snv_indel,
input$vardict_snv_names_add,
input$vardict_indel_names_add,
input$vardict_chr,
input$vardict_pos,
input$vardict_ref,
input$vardict_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$vardict_folder,
input$vardict_file_names_add,
input$vardict_file_type,
input$vardict_snv_indel,
input$vardict_snv_names_add,
input$vardict_indel_names_add))
}
if(is.null(input$caller1_folder)){
progress$inc(5/13)
}
if(!is.null(input$caller1_folder)){
progress$inc(1/13)
raw_calls[[9]]<-list()
included_callers[9]<-input$caller1_name
raw_calls[[9]]<-readInput(input$caller1_folder,
input$caller1_file_names_add,
input$caller1_file_type,
input$caller1_snv_indel,
input$caller1_snv_names_add,
input$caller1_indel_names_add,
input$caller1_chr,
input$caller1_pos,
input$caller1_ref,
input$caller1_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$caller1_folder,
input$caller1_file_names_add,
input$caller1_file_type,
input$caller1_snv_indel,
input$caller1_snv_names_add,
input$caller1_indel_names_add))
if(is.null(input$caller2_folder)){
progress$inc(4/13)
}
if(!is.null(input$caller2_folder)){
progress$inc(1/13)
raw_calls[[10]]<-list()
included_callers[10]<-input$caller2_name
raw_calls[[10]]<-readInput(input$caller2_folder,
input$caller2_file_names_add,
input$caller2_file_type,
input$caller2_snv_indel,
input$caller2_snv_names_add,
input$caller2_indel_names_add,
input$caller2_chr,
input$caller2_pos,
input$caller2_ref,
input$caller2_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$caller2_folder,
input$caller2_file_names_add,
input$caller2_file_type,
input$caller2_snv_indel,
input$caller2_snv_names_add,
input$caller2_indel_names_add))
if(is.null(input$caller3_folder)){
progress$inc(3/13)
}
if(!is.null(input$caller3_folder)){
progress$inc(1/13)
raw_calls[[11]]<-list()
included_callers[11]<-input$caller3_name
raw_calls[[11]]<-readInput(input$caller3_folder,
input$caller3_file_names_add,
input$caller3_file_type,
input$caller3_snv_indel,
input$caller3_snv_names_add,
input$caller3_indel_names_add,
input$caller3_chr,
input$caller3_pos,
input$caller3_ref,
input$caller3_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$caller3_folder,
input$caller3_file_names_add,
input$caller3_file_type,
input$caller3_snv_indel,
input$caller3_snv_names_add,
input$caller3_indel_names_add))
if(is.null(input$caller4_folder)){
progress$inc(2/13)
}
if(!is.null(input$caller4_folder)){
progress$inc(1/13)
raw_calls[[12]]<-list()
included_callers[12]<-input$caller4_name
raw_calls[[12]]<-readInput(input$caller4_folder,
input$caller4_file_names_add,
input$caller4_file_type,
input$caller4_snv_indel,
input$caller4_snv_names_add,
input$caller4_indel_names_add,
input$caller4_chr,
input$caller4_pos,
input$caller4_ref,
input$caller4_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$caller4_folder,
input$caller4_file_names_add,
input$caller4_file_type,
input$caller4_snv_indel,
input$caller4_snv_names_add,
input$caller4_indel_names_add))
if(is.null(input$caller5_folder)){
progress$inc(1/13)
}
if(!is.null(input$caller5_folder)){
progress$inc(1/13)
raw_calls[[13]]<-list()
included_callers[13]<-input$caller5_name
raw_calls[[13]]<-readInput(input$caller5_folder,
input$caller5_file_names_add,
input$caller5_file_type,
input$caller5_snv_indel,
input$caller5_snv_names_add,
input$caller5_indel_names_add,
input$caller5_chr,
input$caller5_pos,
input$caller5_ref,
input$caller5_alt)
sampleNameTest<-cbind(sampleNameTest,
getSampleNames(input$caller5_folder,
input$caller5_file_names_add,
input$caller5_file_type,
input$caller5_snv_indel,
input$caller5_snv_names_add,
input$caller5_indel_names_add))
}
}
}
}
}
#Test for sample names
sampleNameTest<-as.data.frame(sampleNameTest[,!is.na(sampleNameTest[1,])])
if(length(sampleNameTest[1,])==0){
log_info<-c(log_info,"Please check your input files<br>")
output$log_info<-renderUI({HTML(log_info)})
}
if(length(sampleNameTest[1,])==1){
for(i in seq_along(sampleNameTest[,1])){
overview[i,1]<-as.character(sampleNameTest[i,1])
}
output$table <- renderDataTable(datatable(overview))
}
if(length(sampleNameTest[1,])>1){
for(i in seq_along(sampleNameTest[,1])){
compareSample<-sampleNameTest[i,1]
flag<-TRUE
for(j in 2:length(sampleNameTest[1,])){
if(compareSample!=sampleNameTest[i,j]){
flag<-FALSE
}
if(flag==TRUE){
overview[i,1]<-compareSample
}
if(flag==FALSE){
log_info<-c(log_info,
"At least one output file is missing<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
}
}
output$table <- renderDataTable(datatable(overview))
}
#Report raw calls
for(i in seq_along(raw_calls)){
for(j in seq_along(overview[,1])){
if(length(raw_calls[[i]])>0&&
!is.na(raw_calls[[i]][[j]][1,2])){
overview[j,i+1]<-length(raw_calls[[i]][[j]][,1])
}
}
}
progress$close()
#1. Target filtration
log_info<-c(log_info,"1. Target filtration<br>")
output$log_info<-renderUI({HTML(log_info)})
if(is.null(input$targetRegions)){
log_info<-c(log_info,
"Please provide a target regions file<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
progress <- shiny::Progress$new()
progress$set(message = "1. Target filtration", value = 0)
if(!is.null(input$targetRegions)){
for(i in seq_along(overview[,1])){
overview[i,1]<-as.character(overview[i,1])
}
overview2<-overview
overview2[c(seq_along(overview[,1])),c(2:length(overview[1,]))]<-NA
checkpoint<-overview
checkpoint[c(seq_along(overview[,1])),c(2:length(overview[1,]))]<-NA
target_calls<-list()
target_temp<-input$targetRegions
target<-read.table(target_temp$datapath,
header=FALSE,sep="\t",
stringsAsFactors=FALSE)
for(i in seq_along(raw_calls)){
progress$inc(1/length(raw_calls),
detail=paste("->",
as.character(names(overview[i+1]))))
target_calls[[i]]<-list()
if(length(raw_calls[[i]])>0){
for(j in seq_along(overview[,1])){
checkpoint[j,i+1]<-1
if(!is.na(raw_calls[[i]][[j]][1,2])){
include<-rep(FALSE,length(raw_calls[[i]][[j]][,1]))
for(k in seq_along(raw_calls[[i]][[j]][,1])){
flag1<-as.character(raw_calls[[i]][[j]][k,2])==as.character(target[,1])
flag2<-raw_calls[[i]][[j]][k,3]>target[,2]
flag3<-raw_calls[[i]][[j]][k,3]<=target[,3]
if(sum(rowSums(cbind(flag1,flag2,flag3))==3)>0){
include[k]<-TRUE
}
}
target_calls[[i]][[j]]<-raw_calls[[i]][[j]][include,]
names(target_calls[[i]][[j]])<-c("SampleID",
"Chr",
"Pos",
"Ref",
"Alt")
write.table(target_calls[[i]][[j]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".",overview[j,1],
".target.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
overview2[j,i+1]<-length(target_calls[[i]][[j]][,1])
}
if(is.na(raw_calls[[i]][[j]][1,2])){
noCallsAvailable<-data.frame(noCalls=NA)
write.table(noCallsAvailable,
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".",overview[j,1],
".target.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
}
}
}
output$table2 <- renderDataTable(datatable(overview2))
write.table(checkpoint,paste(input$output_folder,
"/checkpoint.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
progress$close()
#2. Normalization
log_info<-c(log_info,"2. Normalization<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "2. Normalization", value = 0)
normalized_calls<-list()
for(i in seq_along(target_calls)){
progress$inc(1/length(target_calls),
detail=paste("->",
as.character(names(overview[i+1]))))
normalized_calls[[i]]<-list()
if(length(target_calls[[i]])>0){
temp<-target_calls[[i]][[1]]
checkpoint[1,i+1]<-2
if(!is.na(temp[1,2])&&length(overview[,1])>1){
for(j in 2:length(overview[,1])){
temp<-rbind(temp,target_calls[[i]][[j]])
checkpoint[j,i+1]<-2
}
}
#GATK
if(i==1){
if(input$gatk_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$gatk_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#Platypus
if(i==2){
if(input$platypus_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$platypus_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#VarScan
if(i==3){
if(input$varscan_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$varscan_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#FreeBayes
if(i==4){
if(input$freebayes_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$freebayes_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#LoFreq
if(i==5){
if(input$lofreq_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$lofreq_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#SNVer
if(i==6){
if(input$snver_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$snver_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#SamTools
if(i==7){
if(input$samtools_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$samtools_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#VarDict
if(i==8){
if(input$vardict_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$vardict_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
if(length(target_calls)>8){
#Caller 1
if(i==9){
if(input$caller1_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller1_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
if(length(target_calls)>9){
#Caller 2
if(i==10){
if(input$caller2_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller2_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
if(length(target_calls)>10){
#Caller 3
if(i==11){
if(input$caller3_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller3_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,
"/",
as.character(names(overview)[i+1]),
".normalized.txt",
sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
if(length(target_calls)>11){
#Caller 4
if(i==12){
if(input$caller4_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller4_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,
"/",
as.character(names(overview)[i+1]),
".normalized.txt",
sep=""),
row.names=FALSE,
quote=FALSE,
sep="\t")
}
if(length(target_calls)>12){
#Caller 5
if(i==13){
if(input$caller5_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller5_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,
"/",
as.character(names(overview)[i+1]),
".normalized.txt",
sep=""),
row.names=FALSE,
quote=FALSE,
sep="\t")
}
}
}
}
}
}
}
}
write.table(checkpoint,paste(input$output_folder,
"/checkpoint.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
progress$close()
#3. Annotate
log_info<-c(log_info,"3. Annotate<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "3. Annotate", value = 0)
annotated_calls<-list()
overview3<-overview
overview3[c(seq_along(overview[,1])),c(2:length(overview[1,]))]<-NA
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
connection_txid_symbol<-transcripts(Homo.sapiens,
columns=c("TXID","SYMBOL"))
for(i in seq_along(normalized_calls)){
progress$inc(1/length(normalized_calls))
annotated_calls[[i]]<-data.frame()
if(length(normalized_calls[[i]])>0){
progress_small <- shiny::Progress$new()
progress_small$set(message = as.character(names(overview[i+1])), value = 0)
test<-VCF(rowRanges=GRanges(seqnames=paste("chr",
as.character(normalized_calls[[i]][,2]),
sep=""),
ranges=IRanges(as.numeric(normalized_calls[[i]][,3]),
(as.numeric(normalized_calls[[i]][,3])+nchar(normalized_calls[[i]][,4])-1))),
fixed=DataFrame(REF=DNAStringSet(normalized_calls[[i]][,4]),
ALT=DNAStringSetList(strsplit(normalized_calls[[i]][,5],",",fixed=TRUE)),
QUAL=1,
FILTER=as.character(normalized_calls[[i]][,1])))
if(is.null(input$locations)){
log_info<-c(log_info,"Please pick at least one location<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$locations)){
located<-locateVariants(test,txdb,AllVariants())
for(j in seq_along(input$locations)){
if(j==1){
of_interest<-data.frame(located$LOCATION==input$locations[j])
}
if(j>1){
of_interest<-data.frame(of_interest,
located$LOCATION==input$locations[j])
}
}
if(length(input$locations)==1){
located<-located[of_interest[,1]>0,]
}
if(length(input$locations)>1){
located<-located[rowSums(of_interest)>0,]
}
}
if(sum(input$locations=="coding")>0&&
is.null(input$consequences)){
log_info<-c(log_info,"Please pick at least one consequence<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$consequences)){
predicted<-predictCoding(query=test,subject=txdb,
seqSource=Hsapiens)
for(j in seq_along(predicted[,1])){
if(as.character(predicted$REFCODON[j])=="CTG"){
if(as.character(predicted$VARCODON[j])=="ATG"){
predicted$CONSEQUENCE[j]<-"nonsynonymous"
}
if(as.character(predicted$VARCODON[j])=="CTA"||
as.character(predicted$VARCODON[j])=="CTC"||
as.character(predicted$VARCODON[j])=="CTT"||
as.character(predicted$VARCODON[j])=="TTA"||
as.character(predicted$VARCODON[j])=="TTG"){
predicted$CONSEQUENCE[j]<-"synonymous"
}
}
if(as.character(predicted$VARCODON[j])=="CTG"){
if(as.character(predicted$REFCODON[j])=="ATG"){
predicted$CONSEQUENCE[j]<-"nonsynonymous"
}
if(as.character(predicted$REFCODON[j])=="CTA"||
as.character(predicted$REFCODON[j])=="CTC"||
as.character(predicted$REFCODON[j])=="CTT"||
as.character(predicted$REFCODON[j])=="TTA"||
as.character(predicted$REFCODON[j])=="TTG"){
predicted$CONSEQUENCE[j]<-"synonymous"
}
}
if(as.character(predicted$REFCODON[j])=="TTG"){
if(as.character(predicted$VARCODON[j])=="ATG"){
predicted$CONSEQUENCE[j]<-"nonsynonymous"
}
if(as.character(predicted$VARCODON[j])=="CTA"||
as.character(predicted$VARCODON[j])=="CTC"||
as.character(predicted$VARCODON[j])=="CTT"||
as.character(predicted$VARCODON[j])=="TTA"||
as.character(predicted$VARCODON[j])=="CTG"){
predicted$CONSEQUENCE[j]<-"synonymous"
}
}
if(as.character(predicted$VARCODON[j])=="TTG"){
if(as.character(predicted$REFCODON[j])=="ATG"){
predicted$CONSEQUENCE[j]<-"nonsynonymous"
}
if(as.character(predicted$REFCODON[j])=="CTA"||
as.character(predicted$REFCODON[j])=="CTC"||
as.character(predicted$REFCODON[j])=="CTT"||
as.character(predicted$REFCODON[j])=="TTA"||
as.character(predicted$REFCODON[j])=="CTG"){
predicted$CONSEQUENCE[j]<-"synonymous"
}
}
}
for(j in seq_along(input$consequences)){
if(j==1){
of_interest<-data.frame(predicted$CONSEQUENCE==input$consequences[j])
}
if(j>1){
of_interest<-data.frame(of_interest,
predicted$CONSEQUENCE==input$consequences[j])
}
}
if(length(input$consequences)==1){
predicted<-predicted[of_interest[,1]>0,]
}
if(length(input$consequences)>1){
predicted<-predicted[rowSums(of_interest)>0,]
}
}
annotated_calls[[i]]<-data.frame(normalized_calls[[i]],
Location=NA,c.=NA,
p.=NA,AA_ref=NA,
AA_alt=NA,Codon_ref=NA,
Codon_alt=NA,
Consequence=NA,Gene=NA,
GeneID=NA,
TranscriptID=NA)
counter_located<-1
counter_predicted<-1
keep<-rep(TRUE,length(annotated_calls[[i]][,1]))
for(k in seq_along(annotated_calls[[i]][,1])){
progress_small$inc(1/length(annotated_calls[[i]][,1]),
detail=paste("-> Call",k,
"out of",
length(annotated_calls[[i]][,1])))
while(counter_located<=length(ranges(located))&&
start(ranges(located))[counter_located]==annotated_calls[[i]][k,3]){
if(!is.na(annotated_calls[[i]][k,6])){
annotated_calls[[i]][k,6]<-paste(annotated_calls[[i]][k,6],
as.character(located$LOCATION[counter_located]),
sep=",")
annotated_calls[[i]][k,7]<-paste(annotated_calls[[i]][k,7],
as.character(located$LOCSTART[counter_located]),
sep=",")
}
if(is.na(annotated_calls[[i]][k,6])){
annotated_calls[[i]][k,6]<-as.character(located$LOCATION[counter_located])
annotated_calls[[i]][k,7]<-as.character(located$LOCSTART[counter_located])
}
counter_located<-counter_located+1
}
if(!is.na(annotated_calls[[i]][k,6])&&
!is.null(input$consequences)){
for(j in seq_along(strsplit(annotated_calls[[i]][k,6],",")[[1]])){
if(counter_predicted>length(ranges(predicted))||
strsplit(annotated_calls[[i]][k,6],",")[[1]][j]!="coding"){
if(!is.na(annotated_calls[[i]][k,8])){
annotated_calls[[i]][k,8]<-paste(annotated_calls[[i]][k,8],"NA",sep=",")
annotated_calls[[i]][k,9]<-paste(annotated_calls[[i]][k,9],"NA",sep=",")
annotated_calls[[i]][k,10]<-paste(annotated_calls[[i]][k,10],"NA",sep=",")
annotated_calls[[i]][k,11]<-paste(annotated_calls[[i]][k,11],"NA",sep=",")
annotated_calls[[i]][k,12]<-paste(annotated_calls[[i]][k,12],"NA",sep=",")
annotated_calls[[i]][k,13]<-paste(annotated_calls[[i]][k,13],"NA",sep=",")
annotated_calls[[i]][k,14]<-paste(annotated_calls[[i]][k,14],"NA",sep=",")
annotated_calls[[i]][k,15]<-paste(annotated_calls[[i]][k,15],"NA",sep=",")
annotated_calls[[i]][k,16]<-paste(annotated_calls[[i]][k,16],"NA",sep=",")
}
if(is.na(annotated_calls[[i]][k,8])){
annotated_calls[[i]][k,8]<-annotated_calls[[i]][k,9]<-"NA"
annotated_calls[[i]][k,10]<-annotated_calls[[i]][k,11]<-"NA"
annotated_calls[[i]][k,12]<-annotated_calls[[i]][k,13]<-"NA"
annotated_calls[[i]][k,14]<-"NA"
annotated_calls[[i]][k,15]<-annotated_calls[[i]][k,16]<-"NA"
}
}
if(counter_predicted<=length(ranges(predicted))&&
strsplit(annotated_calls[[i]][k,6],",")[[1]][j]=="coding"){
if(start(ranges(predicted))[counter_predicted]==annotated_calls[[i]][k,3]){
if(!is.na(annotated_calls[[i]][k,8])){
annotated_calls[[i]][k,8]<-paste(annotated_calls[[i]][k,8],
as.character(predicted$PROTEINLOC[counter_predicted][[1]][1]),
sep=",")
if(as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])!="frameshift"){
if(as.character(predicted$REFCODON[counter_predicted])!="CTG"){
annotated_calls[[i]][k,9]<-paste(annotated_calls[[i]][k,9],
as.character(predicted$REFAA[counter_predicted][[1]][1]),
sep=",")
}
if(as.character(predicted$REFCODON[counter_predicted])=="CTG"){
annotated_calls[[i]][k,9]<-paste(annotated_calls[[i]][k,9],
"L",
sep=",")
}
if(as.character(predicted$VARCODON[counter_predicted])!="CTG"){
annotated_calls[[i]][k,10]<-paste(annotated_calls[[i]][k,10],
as.character(predicted$VARAA[counter_predicted][[1]][1]),
sep=",")
}
if(as.character(predicted$VARCODON[counter_predicted])=="CTG"){
annotated_calls[[i]][k,10]<-paste(annotated_calls[[i]][k,10],"L",sep=",")
}
}
if(as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])=="frameshift"){
annotated_calls[[i]][k,9]<-paste(annotated_calls[[i]][k,9],"NA",sep=",")
annotated_calls[[i]][k,10]<-paste(annotated_calls[[i]][k,10],"NA",sep=",")
}
annotated_calls[[i]][k,11]<-paste(annotated_calls[[i]][k,11],
as.character(predicted$REFCODON[counter_predicted]),
sep=",")
annotated_calls[[i]][k,12]<-paste(annotated_calls[[i]][k,12],
as.character(predicted$VARCODON[counter_predicted]),
sep=",")
annotated_calls[[i]][k,13]<-paste(annotated_calls[[i]][k,13],
as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1]),
sep=",")
annotated_calls[[i]][k,14]<-paste(annotated_calls[[i]][k,14],
as.character(connection_txid_symbol[as.numeric(predicted$TXID[counter_predicted][[1]][1]),]$SYMBOL),
sep=",")
annotated_calls[[i]][k,15]<-paste(annotated_calls[[i]][k,15],
as.character(predicted$GENEID[counter_predicted][[1]][1]),
sep=",")
annotated_calls[[i]][k,16]<-paste(annotated_calls[[i]][k,16],
as.character(predicted$TXID[counter_predicted][[1]][1]),
sep=",")
}
if(is.na(annotated_calls[[i]][k,8])){
annotated_calls[[i]][k,8]<-as.character(predicted$PROTEINLOC[counter_predicted][[1]][1])
if(as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])!="frameshift"){
if(as.character(predicted$REFCODON[counter_predicted])!="CTG"){
annotated_calls[[i]][k,9]<-as.character(predicted$REFAA[counter_predicted][[1]][1])
}
if(as.character(predicted$REFCODON[counter_predicted])=="CTG"){
annotated_calls[[i]][k,9]<-"L"
}
if(as.character(predicted$VARCODON[counter_predicted])!="CTG"){
annotated_calls[[i]][k,10]<-as.character(predicted$VARAA[counter_predicted][[1]][1])
}
if(as.character(predicted$VARCODON[counter_predicted])=="CTG"){
annotated_calls[[i]][k,10]<-"L"
}
}
if(as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])=="frameshift"){
annotated_calls[[i]][k,9]<-"NA"
annotated_calls[[i]][k,10]<-"NA"
}
annotated_calls[[i]][k,11]<-as.character(predicted$REFCODON[counter_predicted])
annotated_calls[[i]][k,12]<-as.character(predicted$VARCODON[counter_predicted])
annotated_calls[[i]][k,13]<-as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])
annotated_calls[[i]][k,14]<-as.character(connection_txid_symbol[as.numeric(predicted$TXID[counter_predicted][[1]][1]),]$SYMBOL)
annotated_calls[[i]][k,15]<-as.character(predicted$GENEID[counter_predicted][[1]][1])
annotated_calls[[i]][k,16]<-as.character(predicted$TXID[counter_predicted][[1]][1])
}
counter_predicted<-counter_predicted+1
}
}
}
}
if(is.na(annotated_calls[[i]][k,6])){
keep[k]<-FALSE
}
if(!is.null(input$consequences)&&
!is.na(annotated_calls[[i]][k,6])&&
sum(strsplit(annotated_calls[[i]][k,6],",")[[1]]=="coding")>0&&
(is.na(annotated_calls[[i]][k,8])||
sum(strsplit(annotated_calls[[i]][k,8],",")[[1]]=="NA")==length(strsplit(annotated_calls[[i]][k,8],",")[[1]]))){
keep[k]<-FALSE
}
}
annotated_calls[[i]]<-annotated_calls[[i]][keep,]
for(k in seq_along(overview3[,1])){
overview3[k,i+1]<-length(annotated_calls[[i]][annotated_calls[[i]][,1]==overview3[k,1],1])
checkpoint[k,i+1]<-3
}
write.table(annotated_calls[[i]],
paste(input$output_folder,"/",
as.character(names(overview)[i+1]),
".annotated.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
progress_small$close()
}
}
write.table(checkpoint,paste(input$output_folder,
"/checkpoint.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
output$table3 <- renderDataTable(datatable(overview3))
progress$close()
#4. Combine
log_info<-c(log_info,"4. Combine Output<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "4. Combine Output", value = 0)
combined_calls<-data.frame(SampleID=NA,Chr=NA,Pos=NA,Ref=NA,
Alt=NA,Location=NA,c.=NA,p.=NA,
AA_ref=NA,AA_alt=NA,Codon_ref=NA,
Codon_alt=NA,Consequence=NA,Gene=NA,
GeneID=NA,TranscriptID=NA,
GATK=NA,Platypus=NA,VarScan=NA,
FreeBayes=NA,LoFreq=NA,SNVer=NA,
SamTools=NA,VarDict=NA)
if(length(annotated_calls)>8){
combined_calls<-cbind(combined_calls,Caller1=NA)
if(length(annotated_calls)>9){
combined_calls<-cbind(combined_calls,Caller2=NA)
if(length(annotated_calls)>10){
combined_calls<-cbind(combined_calls,Caller3=NA)
if(length(annotated_calls)>11){
combined_calls<-cbind(combined_calls,Caller4=NA)
if(length(annotated_calls)>12){
combined_calls<-cbind(combined_calls,
Caller5=NA)
}
}
}
}
}
combined_calls_temp<-combined_calls
overview4<-cbind(overview[,1],RawCalls=NA)
for(i in seq_along(annotated_calls)){
if(length(annotated_calls[[i]])>0){
temp<-annotated_calls[[i]]
add_to_temp<-matrix(rep(NA,(length(combined_calls[1,])-16)),
ncol=(length(combined_calls[1,])-16))
temp<-cbind(temp,add_to_temp)
names(temp)<-names(combined_calls)
temp[,16+i]<-1
combined_calls_temp<-rbind(combined_calls_temp,temp)
}
}
combined_calls_temp<-combined_calls_temp[2:length(combined_calls_temp[,1]),]
combined_calls_temp_sorted<-combined_calls_temp[order(combined_calls_temp[,2],
combined_calls_temp[,3],
combined_calls_temp[,4],
combined_calls_temp[,5],
combined_calls_temp[,1]),]
combined_calls<-combined_calls_temp_sorted[1,]
counter<-1
for(i in 2:length(combined_calls_temp_sorted[,1])){
progress$inc(1/length(combined_calls_temp_sorted[,1]))
if(combined_calls[counter,1]==combined_calls_temp_sorted[i,1]&&
combined_calls[counter,2]==combined_calls_temp_sorted[i,2]&&
combined_calls[counter,3]==combined_calls_temp_sorted[i,3]&&
combined_calls[counter,4]==combined_calls_temp_sorted[i,4]&&
combined_calls[counter,5]==combined_calls_temp_sorted[i,5]){
for(j in 17:length(combined_calls[1,])){
if(!is.na(combined_calls[counter,j])||
!is.na(combined_calls_temp_sorted[i,j])){
combined_calls[counter,j]<-1
}
}
}
if(combined_calls[counter,1]!=combined_calls_temp_sorted[i,1]||
combined_calls[counter,2]!=combined_calls_temp_sorted[i,2]||
combined_calls[counter,3]!=combined_calls_temp_sorted[i,3]||
combined_calls[counter,4]!=combined_calls_temp_sorted[i,4]||
combined_calls[counter,5]!=combined_calls_temp_sorted[i,5]){
counter<-counter+1
combined_calls<-rbind(combined_calls,
combined_calls_temp_sorted[i,])
}
}
temp<-unique(combined_calls)
combined_calls<-temp
for(i in seq_along(overview4[,1])){
overview4[i,2]<-length(combined_calls[combined_calls[,1]==overview4[i,1],1])
for(j in seq_along(annotated_calls)){
if(length(annotated_calls[[j]])>0){
checkpoint[i,j+1]<-4
}
}
}
write.table(combined_calls,paste(input$output_folder,
"/Results_Raw.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
write.table(checkpoint,paste(input$output_folder,
"/checkpoint.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
output$table4 <- renderDataTable(datatable(overview4))
progress$close()
#5. Pileup
log_info<-c(log_info,"5. Evaluate Coverage and BQ<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "5. Evaluate Coverage and BQ", value = 0)
results<-cbind(combined_calls[,c(1:5)],Nr_Ref=NA,Nr_Alt=NA,
DP=NA,VAF=NA,BQ_REF=NA,BQ_ALT=NA,
Nr_Ref_fwd=NA,Nr_Alt_fwd=NA,DP_fwd=NA,VAF_fwd=NA,
Nr_Ref_rev=NA,Nr_Alt_rev=NA,DP_rev=NA,VAF_rev=NA)
folder<-input$bam_folder
for(i in seq_along(results[,1])){
progress$inc(1/length(results[,1]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
done<-FALSE
#SNVs
if(nchar(results[i,4])==1&&nchar(results[i,5])==1){
results_temp<-getCharacteristicsFreq(results[i,2],
results[i,3],
results[i,3],
results[i,4],
results[i,5],
folder,
results[i,1])
results[i,6:19]<-results_temp[1,6:19]
if(results[i,8]>=input$dp&&results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
results[i,3],
results[i,3],
results[i,4],
results[i,5],
folder,
results[i,1])
results[i,10:11]<-results_temp[1,6:7]
}
done<-TRUE
}
#Deletions
if(done==FALSE&&nchar(results[i,4])>1&&nchar(results[i,5])==1
&&substr(results[i,4],1,1)==results[i,5]){
if(nchar(results[i,4])==2){
results_temp<-getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+1,
as.numeric(results[i,3])+1,
substr(results[i,4],2,2),
"-",folder,
results[i,1])
results[i,6:19]<-results_temp[1,6:19]
if(results[i,8]>=input$dp&&
results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+1,
as.numeric(results[i,3])+1,
substr(results[i,4],2,2),
"-",folder,
results[i,1])
results[i,10:11]<-results_temp[1,6:7]
}
}
if(nchar(results[i,4])>2){
results_temp<-getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+1,
as.numeric(results[i,3])+1,
substr(results[i,4],2,2),
"-",folder,
results[i,1])
for(j in 3:nchar(results[i,4])){
results_temp<-rbind(results_temp,
getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
"-",
folder,results[i,1]))
}
for(j in 6:19){
results[i,j]<-min(results_temp[,j])
}
if(results[i,8]>=input$dp&&
results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+1,
as.numeric(results[i,3])+1,
substr(results[i,4],2,2),
"-",folder,
results[i,1])
for(j in 3:nchar(results[i,4])){
results_temp<-rbind(results_temp,
getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
"-",folder,results[i,1]))
}
for(j in 6:7){
results_temp[1,j]<-min(results_temp[,j])
}
results[i,10:11]<-results_temp[1,6:7]
}
}
done<-TRUE
}
#Insertions (summed up as +)
if(done==FALSE&&nchar(results[i,4])==1&&nchar(results[i,5])>1
&&substr(results[i,5],1,1)==results[i,4]){
results_temp<-getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3]),
as.numeric(results[i,3]),
results[i,4],
"+",folder,
results[i,1])
results[i,6:19]<-results_temp[1,6:19]
if(results[i,8]>=input$dp&&results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3]),
as.numeric(results[i,3]),
results[i,4],
"+",folder,
results[i,1])
results[i,10:11]<-results_temp[1,6:7]
}
done<-TRUE
}
#Complex Indels
if(done==FALSE){
results_temp<-getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3]),
as.numeric(results[i,3]),
substr(results[i,4],1,1),
substr(results[i,5],1,1),
folder,
results[i,1])
for(j in 2:min(nchar(results[i,4]),nchar(results[i,5]))){
results_temp<-rbind(results_temp,
getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
substr(results[i,5],j,j),
folder,
results[i,1]))
}
#Del in the end
if(nchar(results[i,4])>nchar(results[i,5])){
results_temp<-rbind(results_temp,
getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+j,
as.numeric(results[i,3])+j,
substr(results[i,4],j+1,j+1),
"-",
folder,
results[i,1]))
}
#Ins in the end
if(nchar(results[i,4])>nchar(results[i,5])){
results_temp<-rbind(results_temp,
getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
"+",
folder,
results[i,1]))
}
for(j in 6:19){
results[i,j]<-min(results_temp[,j])
}
if(results[i,8]>=input$dp&&results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3]),
as.numeric(results[i,3]),
substr(results[i,4],1,1),
substr(results[i,5],1,1),
folder,
results[i,1])
for(j in 2:min(nchar(results[i,4]),nchar(results[i,5]))){
results_temp<-rbind(results_temp,
getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
substr(results[i,5],j,j),
folder,
results[i,1]))
}
#Del in the end
if(nchar(results[i,4])>nchar(results[i,5])){
results_temp<-rbind(results_temp,
getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+j,
as.numeric(results[i,3])+j,
substr(results[i,4],j+1,j+1),
"-",
folder,
results[i,1]))
}
#Ins in the end
if(nchar(results[i,4])>nchar(results[i,5])){
results_temp<-rbind(results_temp,
getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
"+",
folder,
results[i,1]))
}
for(j in 6:7){
results_temp[1,j]<-min(results_temp[,j])
}
results[i,10:11]<-results_temp[1,6:7]
}
}
}
frequency_calls_temp<-cbind(combined_calls,results[,c(6:19)])
include1<-results[,8]>=input$dp
include2<-results[,7]>=input$nr_alt
include3<-(results[,9]*100)>=input$vaf
include4<-results[,11]>=input$bq
for(i in seq_along(results[,1])){
if(is.na(results[i,10])){
results[i,10]<-0
}
}
include5<-(results[,10]-results[,11])<=input$bq_diff
frequency_calls<-frequency_calls_temp[rowSums(cbind(include1,include2,include3,include4,include5))>=5&!is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
overview4<-cbind(overview4,VAFandBQFiltered=NA)
for(i in seq_along(overview4[,1])){
overview4[i,3]<-length(frequency_calls[frequency_calls[,1]==overview4[i,1],1])
for(j in 2:length(checkpoint[1,])){
if(!is.na(checkpoint[i,j])){
checkpoint[i,j]<-5
}
}
}
write.table(frequency_calls,
paste(input$output_folder,
"/Results_Frequency.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
write.table(checkpoint,
paste(input$output_folder,"/checkpoint.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
output$table4 <- renderDataTable(datatable(overview4))
progress$close()
#6. Extended Characteristics
log_info<-c(log_info,
"6. Determine Extended Set of Characteristics<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message="6. Determine Extended Set of Characteristics (databases)",
value=0)
progress$inc(0,detail="-> Downloading databases ")
results<-data.frame(frequency_calls[,c(1:5)])
results<-cbind(results,dbSNP=NA,dbSNP_MAF=NA)
snps<-SNPlocs.Hsapiens.dbSNP144.GRCh37
indels<-XtraSNPlocs.Hsapiens.dbSNP144.GRCh37
if(!is.null(input$`1kgenomes`)){
results<-cbind(results,G1000_AF=NA)
g1000<-MafDb.1Kgenomes.phase3.hs37d5
}
if(!is.null(input$exac)){
results<-cbind(results,ExAC_AF=NA)
exac<-MafDb.ExAC.r1.0.hs37d5
}
if(!is.null(input$gad)){
results<-cbind(results,GAD_AF=NA)
gad<-MafDb.gnomADex.r2.1.hs37d5
}
if(!is.null(input$cosmic)){
results<-cbind(results,CosmicID=NA,Cosmic_Counts=NA)
cosmic_67<-c()
data(cosmic_67,envir = environment(),package = "COSMIC.67")
}
if(!is.null(input$clinvar)){
results<-cbind(results,ClinVar=NA)
clinvar<-data.frame(Gene=NA,Start=NA,Stop=NA,Ref=NA,Alt=NA,
Sig=NA)
genes_temp<-c()
for(i in seq_along(frequency_calls[,1])){
genes_temp<-c(genes_temp,strsplit(frequency_calls[i,14],
split=",")[[1]])
}
genes<-unique(genes_temp[genes_temp!="NA"])
for(i in seq_along(genes)){
res<-entrez_search("clinvar",term=genes[i])
cv<-entrez_summary("clinvar",id=res$ids)
info<-extract_from_esummary(cv,"variation_set",
simplify=FALSE)
significance<-extract_from_esummary(cv,
"clinical_significance",
simplify=FALSE)
for(j in seq_along(res$ids)){
info2<-info[res$ids[j]][[1]][[1]]
significance2<-significance[res$ids[j]][[1]][[1]]
if(length(info2$variation_loc[[1]])){
for(k in seq_along(info2$variation_loc[[1]][,1])){
if(info2$variation_loc[[1]][k,2]=="GRCh37"){
temp<-data.frame(Gene=NA,Start=NA,
Stop=NA,Ref=NA,Alt=NA)
temp[1,1]<-genes[i]
temp[1,2]<-info2$variation_loc[[1]][k,5]
temp[1,3]<-info2$variation_loc[[1]][k,6]
temp[1,4]<-info2$variation_loc[[1]][k,15]
temp[1,5]<-info2$variation_loc[[1]][k,16]
temp[1,6]<-significance2$description
if(!is.na(clinvar[1,1])){
clinvar<-rbind(clinvar,temp)
}
if(is.na(clinvar[1,1])){
clinvar<-temp
}
}
}
}
}
}
}
c.<-c()
c.complement<-c()
p.<-c()
for(i in seq_along(frequency_calls[,1])){
progress$inc(0,detail="-> Pre-processing of the calls ")
for(j in 1:(length(strsplit(frequency_calls[i,7],
split=",")[[1]]))){
if(j==1){
c.[i]<-paste("c.",strsplit(frequency_calls[i,7],
split=",")[[1]][j],
frequency_calls[i,4],">",
frequency_calls[i,5],sep="")
c.complement[i]<-paste("c.",
strsplit(frequency_calls[i,7],
split=",")[[1]][j],
as.character(complement(DNAString(frequency_calls[i,4]))),
">",
as.character(complement(DNAString(frequency_calls[i,5]))),
sep="")
if(!is.na(strsplit(frequency_calls[i,11],
split=",")[[1]][j])&&
!is.na(strsplit(frequency_calls[i,12],
split=",")[[1]][j])&&
strsplit(frequency_calls[i,11],
split=",")[[1]][j]!="NA"&&
strsplit(frequency_calls[i,12],
split=",")[[1]][j]!="NA"&&
nchar(strsplit(frequency_calls[i,11],
split=",")[[1]][j])==3&&
nchar(strsplit(frequency_calls[i,12],
split=",")[[1]][j])==3){
p.[i]<-paste("p.",strsplit(frequency_calls[i,9],
split=",")[[1]][j],
strsplit(frequency_calls[i,8],
split=",")[[1]][j],
strsplit(frequency_calls[i,10],
split=",")[[1]][j],sep="")
}
if(!is.na(strsplit(frequency_calls[i,11],
split=",")[[1]][j])&&
!is.na(strsplit(frequency_calls[i,12],
split=",")[[1]][j])&&
strsplit(frequency_calls[i,11],
split=",")[[1]][j]!="NA"&&
strsplit(frequency_calls[i,12],
split=",")[[1]][j]!="NA"&&
(nchar(strsplit(frequency_calls[i,11],
split=",")[[1]][j])!=3||
nchar(strsplit(frequency_calls[i,12],
split=",")[[1]][j])!=3)){
if((nchar(strsplit(frequency_calls[i,11],
split=",")[[1]][j])%%3)!=0||
(nchar(strsplit(frequency_calls[i,12],
split=",")[[1]][j])%%3)!=0){
p.[i]<-paste("p.",
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,11],split=",")[[1]][j]))),
strsplit(frequency_calls[i,8],
split=",")[[1]][j],
"fs",sep="")
}
if((nchar(strsplit(frequency_calls[i,11],
split=",")[[1]][j])%%3)==0&&
(nchar(strsplit(frequency_calls[i,12],
split=",")[[1]][j])%%3)==0){
p.[i]<-paste("p.",
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,11],split=",")[[1]][j]))),
strsplit(frequency_calls[i,8],
split=",")[[1]][j],
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,12],split=",")[[1]][j]))),sep="")
}
}
}
if(j>1){
c.[i]<-paste(c.[i],paste("c.",
strsplit(frequency_calls[i,7],
split=",")[[1]][j],
frequency_calls[i,4],">",
frequency_calls[i,5],
sep=""),
sep=",")
c.complement[i]<-paste(c.complement[i],
paste("c.",
strsplit(frequency_calls[i,7],split=",")[[1]][j],
as.character(complement(DNAString(frequency_calls[i,4]))),
">",
as.character(complement(DNAString(frequency_calls[i,5]))),
sep=""),
sep=",")
if(!is.na(strsplit(frequency_calls[i,11],
split=",")[[1]][j])&&
!is.na(strsplit(frequency_calls[i,12],
split=",")[[1]][j])&&
strsplit(frequency_calls[i,11],
split=",")[[1]][j]!="NA"&&
strsplit(frequency_calls[i,12],
split=",")[[1]][j]!="NA"&&
nchar(strsplit(frequency_calls[i,11],
split=",")[[1]][j])==3&&
nchar(strsplit(frequency_calls[i,12],
split=",")[[1]][j])==3){
p.[i]<-paste(p.[i],
paste("p.",
strsplit(frequency_calls[i,9],
split=",")[[1]][j],
strsplit(frequency_calls[i,8],
split=",")[[1]][j],
strsplit(frequency_calls[i,10],
split=",")[[1]][j],
sep=""),sep=",")
}
if(!is.na(strsplit(frequency_calls[i,11],
split=",")[[1]][j])&&
!is.na(strsplit(frequency_calls[i,12],
split=",")[[1]][j])&&
strsplit(frequency_calls[i,11],
split=",")[[1]][j]!="NA"&&
strsplit(frequency_calls[i,12],
split=",")[[1]][j]!="NA"&&
(nchar(strsplit(frequency_calls[i,11],
split=",")[[1]][j])!=3||
nchar(strsplit(frequency_calls[i,12],
split=",")[[1]][j])!=3)){
if((nchar(strsplit(frequency_calls[i,11],
split=",")[[1]][j])%%3)!=0||
(nchar(strsplit(frequency_calls[i,12],
split=",")[[1]][j])%%3)!=0){
p.[i]<-paste(p.[i],
paste("p.",
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,11],split=",")[[1]][j]))),
strsplit(frequency_calls[i,8],
split=",")[[1]][j],
"fs",sep=""),sep=",")
}
if((nchar(strsplit(frequency_calls[i,11],
split=",")[[1]][j])%%3)==0&&
(nchar(strsplit(frequency_calls[i,12],
split=",")[[1]][j])%%3)==0){
p.[i]<-paste(p.[i],
paste("p.",
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,11],split=",")[[1]][j]))),
strsplit(frequency_calls[i,8],
split=",")[[1]][j],
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,12],split=",")[[1]][j]))),sep=""),sep=",")
}
}
}
}
}
for(i in seq_along(frequency_calls[,1])){
progress$inc(1/length(results[,1]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
#SNPs
if(nchar(frequency_calls[i,4])==1&&
nchar(frequency_calls[i,5])==1){
snp_info<-snpsByOverlaps(snps,
paste(frequency_calls[i,2],":",
frequency_calls[i,3],"-",
frequency_calls[i,3],
sep=""))
if(length(snp_info)>0){
snp_info<-snp_info[pos(snp_info)==frequency_calls[i,3],]
if(length(snp_info)>0){
if(length(grep(results[i,5],
IUPAC_CODE_MAP[snp_info$alleles_as_ambig]))>0||
(length(grep(results[i,4],
IUPAC_CODE_MAP[snp_info$alleles_as_ambig]))==0&&
length(grep(as.character(complement(DNAString(results[i,5]))),
IUPAC_CODE_MAP[snp_info$alleles_as_ambig])>0))){
results[i,6]<-snp_info$RefSNP_id
}
}
}
if(!is.null(input$`1kgenomes`)){
snp_info<-gscores(g1000,
GRanges(paste(frequency_calls[i,2],
":",
frequency_calls[i,3],
sep="")))
if(length(snp_info)>0){
results$G1000_AF[i]<-max(snp_info$AF)
}
}
if(!is.null(input$exac)){
snp_info<-gscores(exac,
GRanges(paste(frequency_calls[i,2],
":",
frequency_calls[i,3],
sep="")))
if(length(snp_info)>0){
results$ExAC_AF[i]<-max(snp_info$AF)
}
}
if(!is.null(input$gad)){
snp_info<-gscores(gad,
GRanges(paste(frequency_calls[i,2],
":",
frequency_calls[i,3],
sep="")))
if(length(snp_info)>0){
results$GAD_AF[i]<-max(snp_info$AF)
}
}
if(!is.null(input$cosmic)){
snp_info<-rowRanges(cosmic_67)[as.character(seqnames(rowRanges(cosmic_67)))==frequency_calls[i,2]&start(ranges(rowRanges(cosmic_67)))==frequency_calls[i,3]]
if(length(snp_info)>0){
for(j in seq_along(snp_info[,1])){
if(snp_info$REF==frequency_calls[i,4]&&
snp_info$ALT[[1]]==frequency_calls[i,5]||
(snp_info$REF==as.character(complement(DNAString(frequency_calls[i,4])))&&
snp_info$ALT[[1]]==as.character(complement(DNAString(frequency_calls[i,5]))))){
snp_info2<-info(cosmic_67)[rownames(info(cosmic_67))==names(snp_info[j,]),]
grep_c.<-grep(snp_info2$CDS,
as.character(strsplit(c.[i],split=",")[[1]]))
grep_c.comp<-grep(snp_info2$CDS,
as.character(strsplit(c.complement[i],split=",")[[1]]))
grep_p.<-grep(snp_info2$AA,
as.character(strsplit(p.[i],split=",")[[1]]))
if(length(intersect(grep_c.,grep_p.))>0||
length(intersect(grep_c.comp,grep_p.))>0){
if(!is.na(results$CosmicID[i])){
results$CosmicID[i]<-paste(results$CosmicID[i],
names(snp_info[j,]),
sep=",")
results$Cosmic_Counts[i]<-paste(results$Cosmic_Counts[i],
snp_info2$CNT,sep=",")
}
if(is.na(results$CosmicID[i])){
results$CosmicID[i]<-names(snp_info[j,])
results$Cosmic_Counts[i]<-snp_info2$CNT
}
}
}
}
}
}
if(!is.null(input$clinvar)){
snp_info_temp<-data.frame()
for(j in seq_along(strsplit(frequency_calls[i,14],
split=",")[[1]])){
if(!is.na(strsplit(frequency_calls[i,14],
split=",")[[1]][j])){
temp<-clinvar[grep(strsplit(frequency_calls[i,14],
split=",")[[1]][j],
clinvar[,1]),]
temp2<-temp[nchar(temp[,4])==1&nchar(temp[,5])==1&temp[,4]!="-"&temp[,5]!="-",]
if(length(snp_info_temp)>0){
snp_info_temp<-rbind(snp_info_temp,temp2)
}
if(length(snp_info_temp[1,1])==0){
snp_info_temp<-temp2
}
}
}
snp_info<-unique(snp_info_temp)
if(length(snp_info)>0){
snp_info2<-snp_info[snp_info[,2]==frequency_calls[i,3],]
if(length(snp_info2[,1])>0){
if((snp_info2[1,4]==frequency_calls[i,4]&&
snp_info2[1,5]==frequency_calls[i,5])||
(snp_info2[1,4]==as.character(complement(DNAString(frequency_calls[i,4])))
&&snp_info2[1,5]==as.character(complement(DNAString(frequency_calls[i,5]))))){
results$ClinVar[i]<-snp_info2[1,6]
}
}
}
}
}
#Indels
if(nchar(frequency_calls[i,4])!=1||
nchar(frequency_calls[i,5])!=1){
suppressWarnings(snp_info<-snpsByOverlaps(indels,
paste("ch",
frequency_calls[i,2],
":",
frequency_calls[i,3],
"-",
(as.numeric(frequency_calls[i,3])+nchar(frequency_calls[i,4])-1),
sep="")))
if(length(snp_info)>0){
snp_info_rs<-snp_info$RefSNP_id[(start(ranges(snp_info))<=frequency_calls[i,3])&(end(ranges(snp_info))>=(as.numeric(frequency_calls[i,3])+nchar(frequency_calls[i,4])-1))]
if(length(snp_info_rs)>0){
ncbi<-ncbi_snp_query(snp_info_rs)
for(j in seq_along(ncbi[,1])){
if(nchar(results[i,4])>nchar(results[i,5])){
if(length(grep(substr(results[i,4],2,
nchar(results[i,4])),
ncbi[j,9]))>0){
results[i,6]<-ncbi[j,1]
}
}
if(nchar(results[i,4])<nchar(results[i,5])){
if(length(grep(substr(results[i,5],2,
nchar(results[i,5])),
ncbi[j,9]))>0){
results[i,6]<-ncbi[j,1]
}
}
}
}
}
if(!is.null(input$cosmic)){
snp_info<-rowRanges(cosmic_67)[as.character(seqnames(rowRanges(cosmic_67)))==frequency_calls[i,2]&start(ranges(rowRanges(cosmic_67)))==frequency_calls[i,3]]
if(length(snp_info)>0){
for(j in seq_along(snp_info[,1])){
if(snp_info$REF==frequency_calls[i,4]&&
snp_info$ALT[[1]]==frequency_calls[i,5]||
(snp_info$REF==as.character(complement(DNAString(frequency_calls[i,4])))
&&snp_info$ALT[[1]]==as.character(complement(DNAString(frequency_calls[i,5]))))){
snp_info2<-info(cosmic_67)[rownames(info(cosmic_67))==names(snp_info[j,]),]
grep_c.<-grep(snp_info2$CDS,
as.character(strsplit(c.[i],split=",")[[1]]))
grep_c.comp<-grep(snp_info2$CDS,
as.character(strsplit(c.complement[i],split=",")[[1]]))
grep_p.<-grep(snp_info2$AA,
as.character(strsplit(p.[i],split=",")[[1]]))
if(length(intersect(grep_c.,grep_p.))>0||
length(intersect(grep_c.comp,grep_p.))>0){
if(!is.na(results$CosmicID[i])){
results$CosmicID[i]<-paste(results$CosmicID[i],
names(snp_info[j,]),sep=",")
results$Cosmic_Counts[i]<-paste(results$Cosmic_Counts[i],
snp_info2$CNT,sep=",")
}
if(is.na(results$CosmicID[i])){
results$CosmicID[i]<-names(snp_info[j,])
results$Cosmic_Counts[i]<-snp_info2$CNT
}
}
}
}
}
}
if(!is.null(input$clinvar)){
snp_info_temp<-data.frame()
for(j in seq_along(strsplit(frequency_calls[i,14],
split=",")[[1]])){
if(!is.na(strsplit(frequency_calls[i,14],
split=",")[[1]][j])){
temp<-clinvar[grep(strsplit(frequency_calls[i,14],split=",")[[1]][j],
clinvar[,1]),]
temp2<-temp[nchar(temp[,4])>1|nchar(temp[,5])>1|temp[,4]=="-"|temp[,5]=="-",]
if(length(snp_info_temp)>0){
snp_info_temp<-rbind(snp_info_temp,temp2)
}
if(length(snp_info_temp[1,1])==0){
snp_info_temp<-temp2
}
}
}
snp_info<-unique(snp_info_temp)
if(length(snp_info)>0){
snp_info2<-snp_info[snp_info[,2]==(as.numeric(frequency_calls[i,3])-1),]
if(length(snp_info2[,1])>0){
for(j in seq_along(snp_info2[,1])){
if(snp_info2[j,4]=="-"&&
snp_info2[j,5]==substr(frequency_calls[i,5],2,nchar(frequency_calls[i,5]))){
results$ClinVar[i]<-snp_info2[j,6]
}
if(snp_info2[j,5]=="-"&&
snp_info2[j,4]==substr(frequency_calls[i,4],2,nchar(frequency_calls[i,4]))){
results$ClinVar[i]<-snp_info2[j,6]
}
}
}
}
}
}
}
if(length(results[!is.na(results[,6]),6])<=3){
suppressWarnings(ncbi<-ncbi_snp_query(results[!is.na(results[,6]),6]))
}
if(length(results[!is.na(results[,6]),6])>3){
abfrage<-results[!is.na(results[,6]),6]
if(((length(results[!is.na(results[,6]),6])-1)%%3)==0){
limits<-seq(1,length(results[!is.na(results[,6]),6]),3)
}
if(((length(results[!is.na(results[,6]),6])-1)%%3)!=0){
limits<-c(seq(1,length(results[!is.na(results[,6]),6]),
3),
length(results[!is.na(results[,6]),6]))
}
suppressWarnings(ncbi<-ncbi_snp_query(abfrage[1:3]))
for(i in 2:(length(limits)-1)){
suppressWarnings(temp<-ncbi_snp_query(abfrage[limits[i]:(limits[i+1]-1)]))
ncbi<-rbind(ncbi,temp)
}
}
for(i in seq_along(results[,1])){
if(!is.na(results[i,6])){
results$dbSNP_MAF[i]<-as.numeric(max(ncbi[ncbi[,1]==results[i,6],10]))
if(sum(ncbi[ncbi[,1]==results[i,6],9]==results[i,4],na.rm=TRUE)>0){
if(!is.na(results$dbSNP_MAF[i])){
results$dbSNP_MAF[i]<-1-results$dbSNP_MAF[i]
}
if(!is.na(results$G1000_AF[i])){
results$G1000_AF[i]<-1-results$G1000_AF[i]
}
if(!is.na(results$ExAC_AF[i])){
results$ExAC_AF[i]<-1-results$ExAC_AF[i]
}
if(!is.na(results$GAD_AF[i])){
results$GAD_AF[i]<-1-results$GAD_AF[i]
}
}
}
}
progress$close()
results<-cbind(results,Prediction=NA,Score=NA)
progress <- shiny::Progress$new()
progress$set(message = "6. Determine Extended Set of Characteristics (prediction)",
value = 0)
if(input$predict!="PolyPhen2"){
for(i in seq(1,length(results[,6]))[!is.na(results[,6])]){
progress$inc(1/length(seq(1,length(results[,6]))[!is.na(results[,6])]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
suppressWarnings(info<-select(SIFT.Hsapiens.dbSNP137,
keys=substr(results[i,6],3,nchar(results[i,6]))))
if(length(info)>0){
if(input$predict=="SIFT"){
#score <0.05 -> damaging (else: tolerated)
results$Prediction[i]<-info[which.min(info[,15]),16]
results$Score[i]<-min(info[,15])
}
if(input$predict=="Provean"){
#score <-2.5 -> deleterious (else: neutral)
results$Prediction[i]<-info[which.min(info[,11]),12]
results$Score[i]<-min(info[,11])
}
}
}
}
if(input$predict=="PolyPhen2"){
#Polyphen (probably damaging, possibly damaging, benign, unknown); probability of variant being damaging
for(i in seq(1,length(results[,6]))[!is.na(results[,6])]){
progress$inc(1/length(seq(1,length(results[,6]))[!is.na(results[,6])]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
suppressWarnings(info<-select(PolyPhen.Hsapiens.dbSNP131,
keys=results[i,6]))
if(length(info)>0){
if(is.na(max(info[,19]))){
results$Prediction[i]<-"unknown"
results$Score[i]<-max(info[,19])
}
if(!is.na(max(info[,19]))){
results$Prediction[i]<-info[which.max(info[,19]),15]
results$Score[i]<-max(info[,19])
}
}
}
}
for(i in seq_along(overview4[,1])){
for(j in 2:length(checkpoint[1,])){
if(!is.na(checkpoint[i,j])){
checkpoint[i,j]<-6
}
}
}
if(is.null(input$dbSNP)){
database_calls<-cbind(results[,c(1:5,8:(length(results[1,])))],
c.,c.complement,p.)
}
if(!is.null(input$dbSNP)){
database_calls<-cbind(results,c.,c.complement,p.)
}
write.table(database_calls,
paste(input$output_folder,
"/Results_Databases.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
write.table(checkpoint,
paste(input$output_folder,"/checkpoint.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
progress$close()
#7. Final Filtration
log_info<-c(log_info,"7. Perform Final Filtration<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "7. Perform final filtration", value = 0)
if(input$stricter_thresholds=="No"){
dp<-input$dp
nr_alt<-input$nr_alt
vaf<-input$vaf
low_bq<-input$bq
bq_diff<-input$bq_diff
}
if(input$stricter_thresholds=="Yes"){
dp<-input$dp2
nr_alt<-input$nr_alt2
vaf<-input$vaf2
low_bq<-input$bq2
bq_diff<-input$bq_diff2
}
nrsamples<-input$nr_samples
nrsamples_high<-ceiling(length(overview4[,1])/2)
if(nrsamples_high==1){
nrsamples_high<-2
}
if(input$predict=="SIFT"){
limit_provean<-input$damaging_safe1
limit_provean2<-input$tolerated_safe1
}
if(input$predict=="Provean"){
limit_provean<-input$damaging_safe2
limit_provean2<-input$tolerated_safe2
}
if(input$predict=="PolyPhen2"){
limit_provean<-input$damaging_safe3
limit_provean2<-input$tolerated_safe3
}
if(!is.null(input$primerPositions)){
primer_temp<-input$primerPositions
primer<-read.table(primer_temp$datapath,
header=FALSE,sep="\t",
stringsAsFactors=FALSE)
}
if(!is.null(input$hotspots)){
hotspots_temp<-input$hotspots
hotspots<-read.table(hotspots_temp$datapath,header=TRUE,
sep="\t",stringsAsFactors=FALSE)
}
results<-cbind(frequency_calls[,c(1:5,14:16,6,13)],
database_calls[,c((length(database_calls[1,])-2):length(database_calls[1,]))],
frequency_calls[,c(11,12)],
Nr_Ref=frequency_calls$Nr_Ref,
Nr_Alt=frequency_calls$Nr_Alt,
DP=frequency_calls$DP,
VAF=frequency_calls$VAF,
frequency_calls[,c(17:(length(frequency_calls[1,])-14))],
Called=rowSums(frequency_calls[,c(17:(length(frequency_calls[1,])-14))],na.rm=TRUE),
database_calls[,c(6:(length(database_calls[1,])-3))],
frequency_calls[,c((length(frequency_calls[1,])-9):(length(frequency_calls[1,])))])
artifact_because<-data.frame(nr_samples=rep(NA,length(frequency_calls[,1])),
nr_samples_similar=rep(NA,length(frequency_calls[,1])),
nr_databases=rep(NA,length(frequency_calls[,1])),
polymorphism_db=rep(NA,length(frequency_calls[,1])),
mutation_db=rep(NA,length(frequency_calls[,1])),
cosmic_nr=rep(NA,length(frequency_calls[,1])),
Poly_freq=rep(NA,length(frequency_calls[,1])))
#filter frequency
if(input$stricter_thresholds=="Yes"){
progress$inc(1/13,detail="-> Consider Frequency and Base Quality")
include1<-results$DP>=dp
include2<-results$Nr_Alt>=nr_alt
include3<-(results$VAF*100)>=vaf
include4<-results$BQ_ALT>=low_bq
include5<-(results$BQ_REF-results$BQ_ALT)<=bq_diff
temp<-results[rowSums(cbind(include1,include2,include3,include4,include5))>=5|is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
results<-temp
temp<-frequency_calls[rowSums(cbind(include1,include2,include3,include4,include5))>=5|is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
frequency_calls<-temp
temp<-database_calls[rowSums(cbind(include1,include2,include3,include4,include5))>=5|is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
database_calls<-temp
temp<-artifact_because[rowSums(cbind(include1,include2,include3,include4,include5))>=5|is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
artifact_because<-temp
}
if(input$stricter_thresholds=="No"){
progress$inc(1/13)
}
#nr of samples
progress$inc(1/13,
detail="-> Consider samples with the same call")
progress_small <- shiny::Progress$new()
progress_small$set(message = "", value = 0)
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
artifact_because[i,1]<-length(combined_calls[intersect(intersect(grep(results[i,2],combined_calls[,2]),grep(results[i,3],combined_calls[,3])),intersect(grep(results[i,4],combined_calls[,4]),grep(results[i,5],combined_calls[,5]))),1])
}
progress_small$close()
progress$inc(1/13,
detail="-> Consider samples with a call at the same position")
progress_small <- shiny::Progress$new()
progress_small$set(message = "", value = 0)
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
artifact_because[i,2]<-length(combined_calls[intersect(grep(results[i,2],combined_calls[,2]),grep(results[i,3],combined_calls[,3])),1])
}
progress_small$close()
progress$inc(1/13,detail="-> Consider background information")
background_info<-rep(0,length(results[,1]))
start<-0
ende<-0
neu<-TRUE
i<-1
while(i<=length(results[,1])){
if(neu==TRUE){
start<-ende<-i
}
i<-i+1
if(i<=length(results[,1])&&
as.character(results[i,2])==as.character(results[i-1,2])&&
results[i,3]==results[i-1,3]&&
results[i,4]==results[i-1,4]&&
results[i,5]==results[i-1,5]){
ende<-i
neu<-FALSE
}
if(i>length(results[,1])||
as.character(results[i,2])!=as.character(results[i-1,2])||
results[i,3]!=results[i-1,3]||
results[i,4]!=results[i-1,4]||
results[i,5]!=results[i-1,5]){
for(j in start:ende){
background_info[j]<-ende-start+1
neu<-TRUE
}
}
}
#databases
progress$inc(1/13,detail="-> Consider nr of databases")
if(length(database_calls[1,])>10){
if(length(grep("dbSNP",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$dbSNP[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],
1,na.rm=TRUE)
if(!is.na(results$dbSNP_MAF[i])&&
as.numeric(results$dbSNP_MAF[i])<=0.001){
artifact_because[i,5]<-sum(artifact_because[i,5],
1,na.rm=TRUE)
}
if(!is.na(results$dbSNP_MAF[i])&&
as.numeric(results$dbSNP_MAF[i])>0.001){
artifact_because[i,4]<-sum(artifact_because[i,4],
1,na.rm=TRUE)
}
}
}
}
if(length(grep("G1000_AF",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$G1000_AF[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],
1,na.rm=TRUE)
if(as.numeric(results$G1000_AF[i])<=0.001){
artifact_because[i,5]<-sum(artifact_because[i,5],
1,na.rm=TRUE)
}
if(as.numeric(results$G1000_AF[i])>0.001){
artifact_because[i,4]<-sum(artifact_because[i,4],
1,na.rm=TRUE)
}
}
}
}
if(length(grep("ExAC_AF",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$ExAC_AF[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],
1,na.rm=TRUE)
if(as.numeric(results$ExAC_AF[i])<=0.0005){
artifact_because[i,5]<-sum(artifact_because[i,5],
1,na.rm=TRUE)
}
if(as.numeric(results$ExAC_AF[i])>0.0005){
artifact_because[i,4]<-sum(artifact_because[i,4],
1,na.rm=TRUE)
}
}
}
}
if(length(grep("GAD_AF",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$GAD_AF[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],
1,na.rm=TRUE)
if(as.numeric(results$GAD_AF[i])<=0.001){
artifact_because[i,5]<-sum(artifact_because[i,5],
1,na.rm=TRUE)
}
if(as.numeric(results$GAD_AF[i])>0.001){
artifact_because[i,4]<-sum(artifact_because[i,4],
1,na.rm=TRUE)
}
}
}
}
if(length(grep("CosmicID",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$CosmicID[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],
1,na.rm=TRUE)
artifact_because[i,6]<-sum(as.numeric(strsplit(as.character(database_calls$Cosmic_Counts[i]),split=",")[[1]]))
if(artifact_because[i,6]>20){
artifact_because[i,5]<-sum(artifact_because[i,5],
1,na.rm=TRUE)
}
if(artifact_because[i,6]<=20){
artifact_because[i,4]<-sum(artifact_because[i,4],
1,na.rm=TRUE)
}
}
}
}
if(length(grep("ClinVar",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$ClinVar[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],
1,na.rm=TRUE)
if(length(grep("Pathogenic",results$ClinVar[i],
ignore.case = TRUE))>0){
artifact_because[i,5]<-sum(artifact_because[i,5],
1,na.rm=TRUE)
}
if(length(grep("Benign",results$ClinVar[i],
ignore.case=TRUE))>0){
artifact_because[i,4]<-sum(artifact_because[i,4],
1,na.rm=TRUE)
}
}
}
}
}
#tolerated and freq
progress$inc(1/13,detail="-> Consider VAF when tolerated")
for(i in seq_along(results[,1])){
if(!is.na(results$VAF[i])&&((results$VAF[i]>=0.35&&
results$VAF[i]<=0.65)||
(results$VAF[i]>=0.85))){
artifact_because[i,7]<-1
}
if(!is.na(results$VAF[i])&&(results$VAF[i]<0.35||
(results$VAF[i]>0.65&&
results$VAF[i]<0.85))){
artifact_because[i,7]<-0
}
}
#large number of samples and high VAF
progress$inc(1/13,
detail="-> Consider VAF when high nr of samples")
i<-1
while(i<=length(results[,1])){
subset<-results[i:(i+background_info[i]-1),]
if(length(subset[,1])>nrsamples&&
sum(!is.na(subset$VAF))==length(subset[,1])&&
sum(subset$VAF>0.85)>=floor(0.9*length(subset[,1]))){
artifact_because[i:(i+background_info[i]-1),7]<-2
}
i<-i+background_info[i]
}
#test for strand bias (8 von 15)
progress$inc(1/13,detail="-> Consider strand bias")
strandbias<-rep(NA,length(results[,1]))
for(i in seq_along(results[,1])){
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])){
test<-fisher.test(x=matrix(c(results$Nr_Ref_fwd[i],
results$Nr_Alt_fwd[i],
results$Nr_Ref_rev[i],
results$Nr_Alt_rev[i]),
ncol=2))
strandbias[i]<-test$p.value
}
if(!is.null(input$primerPositions)){
chr<-as.character(results[i,2])==as.character(primer[,1])
start<-results[i,3]>primer[,2]
end<-(as.numeric(results[i,3])+nchar(results[i,4])-1)<=primer[,3]
if(sum(rowSums(cbind(chr,start,end))==3)>0){
strandbias[i]<-2
}
}
}
#check for hotspots
progress$inc(1/13,detail="-> Consider hotspot list")
hotspot<-rep(NA,length(results[,1]))
progress_small <- shiny::Progress$new()
progress_small$set(message = "", value = 0)
if(!is.null(input$hotspots)){
for(i in seq_along(hotspots[,1])){
progress_small$inc(1/length(hotspots[,1]),
detail=paste("-> Hotspot",i,
"out of",
length(hotspots[,1])))
found1<-grep(hotspots[i,1],results$Gene)
if(length(found1)>0){
if(length(grep("fs",hotspots[i,2]))==0&&
length(grep("del",hotspots[i,2]))==0&&
length(grep("ins",hotspots[i,2]))==0){
#Just an SNV
found2<-grep(hotspots[i,2],results$p.,
fixed=TRUE)
flag<-NA
if(length(found2)>0){
flag<-rep(FALSE,length(results[,1]))
if(is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Ref[found2[j]])==1&&nchar(results$Alt[found2[j]])==1
}
}
if(!is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Ref[found2[j]])==1&&nchar(results$Alt[found2[j]])==1&&as.numeric(results$VAF[found2[j]])>=as.numeric(hotspots[i,3])
}
}
}
}
if(length(grep("fs",hotspots[i,2]))>0){
#frameshift
searchstring<-substr(hotspots[i,2],
2,(nchar(hotspots[i,2])-2))
found2<-grep(searchstring,results$p.)
flag<-NA
if(length(found2)>0){
flag<-rep(FALSE,length(results[,1]))
if(is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))!=0&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0
}
}
if(!is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))!=0&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0&&as.numeric(results$VAF[found2[j]])>=as.numeric(hotspots[i,3])
}
}
}
}
if(length(grep("del",hotspots[i,2]))>0){
#deletion
searchstring_temp<-substr(hotspots[i,2],2,
(nchar(hotspots[i,2])-3))
searchstring<-strsplit(searchstring_temp,split="_")[[1]][1]
found2<-grep(searchstring,results$p.)
flag<-NA
if(length(found2)>0){
flag<-rep(FALSE,length(results[,1]))
if(is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Ref[found2[j]])>1&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0
}
}
if(!is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Ref[found2[j]])>1&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0&&as.numeric(results$VAF[found2[j]])>=as.numeric(hotspots[i,3])
}
}
}
}
if(length(grep("ins",hotspots[i,2]))>0){
#deletion
searchstring_temp<-substr(hotspots[i,2],2,
(nchar(hotspots[i,2])-3))
searchstring<-strsplit(searchstring_temp,split="_")[[1]][1]
found2<-grep(searchstring,results$p.)
flag<-NA
if(length(found2)>0){
flag<-rep(FALSE,length(results[,1]))
if(is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Alt[found2[j]])>1&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0
}
}
if(!is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Alt[found2[j]])>1&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0&&as.numeric(results$VAF[found2[j]])>=as.numeric(hotspots[i,3])
}
}
}
}
if(length(intersect(found1,found2))>0){
for(j in intersect(found1,found2)){
if(flag[j]==TRUE){
hotspot[j]<-1
}
}
}
}
}
}
progress_small$close()
##final filtration
results<-cbind(results,strandbias,
artifact_because[,c(1:2)],Category=NA)
#artifact score
progress$inc(1/13,detail="-> Perform final filtration")
artifact_score<-rep(0,length(results[,1]))
progress_small <- shiny::Progress$new()
progress_small$set(message = "Calculate Artifact Score",
value = 0)
if(input$artifact_score=="No"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,"out of",
length(results[,1])))
if(results$nr_samples[i]>nrsamples){
artifact_score[i]<-artifact_score[i]+2
}
if(results$nr_samples[i]>nrsamples_high&&
is.na(hotspot[i])){
artifact_score[i]<-artifact_score[i]+2
}
if((nchar(results$Ref[i])>1||nchar(results$Alt[i])>1)&&
results$nr_samples_similar[i]>results$nr_samples[i]){
artifact_score[i]<-artifact_score[i]+1
}
if((nchar(results$Ref[i])>1||nchar(results$Alt[i])>1)&&
!is.na(results$VAF[i])&&results$VAF[i]<0.05){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(artifact_because[i,7])&&
artifact_because[i,7]==2){
artifact_score[i]<-artifact_score[i]+2
}
if(is.null(input$primerPositions)||
(!is.na(results$strandbias[i])&&
results$strandbias[i]!=2)){
if(!is.na(results$strandbias[i])&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(results$Nr_Alt_fwd[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_fwd[i]>=(nr_alt/2)&&
results$Nr_Alt_rev[i]>=(nr_alt/2))&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]-1
}
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
(results$Nr_Alt_fwd[i]<=2&&
results$Nr_Ref_fwd[i]>=(dp-nr_alt)/2)&&
results$strandbias[i]>=0.001){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
(results$Nr_Alt_fwd[i]<=2&&
results$Nr_Ref_fwd[i]<(dp-nr_alt)/2)&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]-1
}
if(!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_rev[i]<=2&&
results$Nr_Ref_rev[i]>=(dp-nr_alt)/2)&&
results$strandbias[i]>=0.001){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_rev[i]<=2&&
results$Nr_Ref_rev[i]<(dp-nr_alt)/2)&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]-1
}
}
if(!is.null(input$primerPositions)&&
!is.na(results$strandbias[i])&&
results$strandbias[i]==2){
artifact_score[i]<-artifact_score[i]-1
}
if(!is.na(results$VAF[i])&&results$VAF[i]<0.02){
artifact_score[i]<-artifact_score[i]+2
}
if(is.na(artifact_because[i,3])&&
!is.na(results$VAF[i])&&results$VAF[i]<0.10){
artifact_score[i]<-artifact_score[i]+1
}
if(is.na(artifact_because[i,3])&&
results$nr_samples[i]>nrsamples_high){
artifact_score[i]<-artifact_score[i]+1
}
if((!is.na(results$Score[i])&&
results$Score[i]<limit_provean)){
artifact_score[i]<-artifact_score[i]-1
}
if(!is.na(results$Score[i])&&
results$Score[i]>limit_provean2&&
!is.na(artifact_because[i,7])&&
artifact_because[i,7]==0){
artifact_score[i]<-artifact_score[i]+1
}
if(results$Called[i]>=4){
artifact_score[i]<-artifact_score[i]-1
}
if(results$Called[i]>=5){
artifact_score[i]<-artifact_score[i]-1
}
if(results$Called[i]>=6){
artifact_score[i]<-artifact_score[i]-1
}
if(results$Called[i]==1){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(results$BQ_ALT[i])&&
results$BQ_ALT[i]<(mean(results$BQ_ALT,na.rm=TRUE)-3*sd(results$BQ_ALT,na.rm=TRUE))){
artifact_score[i]<-artifact_score[i]+4
}
if(!is.na(hotspot[i])){
artifact_score[i]<-artifact_score[i]-3
}
if(!is.na(results$LoFreq[i])&&
!is.na(results$FreeBayes[i])&&
!is.na(results$VarDict[i])&&
results$LoFreq[i]==1&&results$FreeBayes[i]==1&&
results$VarDict[i]==1){
artifact_score[i]<-artifact_score[i]-3
}
if(artifact_score[i]>-1){
results$Category[i]<-paste("Artifact (",
artifact_score[i],")",
sep="")
}
if(artifact_score[i]<=-1&&is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],")",
sep="")
}
if(artifact_score[i]<=-1&&!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],")",
sep="")
}
}
}
if(input$artifact_score=="Yes"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,"out of",
length(results[,1])))
if(results$nr_samples[i]>nrsamples){
artifact_score[i]<-artifact_score[i]+input$detectedLow
}
if(results$nr_samples[i]>nrsamples_high&&
is.na(hotspot[i])){
artifact_score[i]<-artifact_score[i]+input$detectedHigh
}
if((nchar(results$Ref[i])>1||nchar(results$Alt[i])>1)&&
results$nr_samples_similar[i]>results$nr_samples[i]){
artifact_score[i]<-artifact_score[i]+input$isIndel
}
if((nchar(results$Ref[i])>1||nchar(results$Alt[i])>1)&&
!is.na(results$VAF[i])&&results$VAF[i]<0.05){
artifact_score[i]<-artifact_score[i]+input$isIndelVAF
}
if(!is.na(artifact_because[i,7])&&
artifact_because[i,7]==2){
artifact_score[i]<-artifact_score[i]+input$detectedLowVAF
}
if(is.null(input$primerPositions)||
(!is.na(results$strandbias[i])&&
results$strandbias[i]!=2)){
if(!is.na(results$strandbias[i])&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+input$noPrimerP
}
if(!is.na(results$Nr_Alt_fwd[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_fwd[i]>=(nr_alt/2)&&
results$Nr_Alt_rev[i]>=(nr_alt/2))&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+input$primerPAlt
}
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
(results$Nr_Alt_fwd[i]<=2&&
results$Nr_Ref_fwd[i]>=(dp-nr_alt)/2)&&
results$strandbias[i]>=0.001){
artifact_score[i]<-artifact_score[i]+input$noPrimerPFwd
}
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
(results$Nr_Alt_fwd[i]<=2&&
results$Nr_Ref_fwd[i]<(dp-nr_alt)/2)&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+input$primerPFwd
}
if(!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_rev[i]<=2&&
results$Nr_Ref_rev[i]>=(dp-nr_alt)/2)&&
results$strandbias[i]>=0.001){
artifact_score[i]<-artifact_score[i]+input$noPrimerPRev
}
if(!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_rev[i]<=2&&
results$Nr_Ref_rev[i]<(dp-nr_alt)/2)&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+input$primerPRev
}
}
if(!is.null(input$primerPositions)&&
!is.na(results$strandbias[i])&&
results$strandbias[i]==2){
artifact_score[i]<-artifact_score[i]+input$primerLocation
}
if(!is.na(results$VAF[i])&&results$VAF[i]<0.02){
artifact_score[i]<-artifact_score[i]+input$vafLow
}
if(is.na(artifact_because[i,3])&&
!is.na(results$VAF[i])&&results$VAF[i]<0.10){
artifact_score[i]<-artifact_score[i]+input$databaseVAF
}
if(is.na(artifact_because[i,3])&&
results$nr_samples[i]>nrsamples_high){
artifact_score[i]<-artifact_score[i]+input$databaseHigh
}
if((!is.na(results$Score[i])&&
results$Score[i]<limit_provean)){
artifact_score[i]<-artifact_score[i]+input$predictionSafe
}
if(!is.na(results$Score[i])&&
results$Score[i]>limit_provean2&&
!is.na(artifact_because[i,7])&&
artifact_because[i,7]==0){
artifact_score[i]<-artifact_score[i]+input$predictionVAF
}
if(results$Called[i]>=input$nrcaller4){
artifact_score[i]<-artifact_score[i]+input$reward4
}
if(results$Called[i]>=input$nrcaller5){
artifact_score[i]<-artifact_score[i]+input$reward5
}
if(results$Called[i]>=input$nrcaller6){
artifact_score[i]<-artifact_score[i]+input$reward6
}
if(results$Called[i]==1){
artifact_score[i]<-artifact_score[i]+input$oneCaller
}
if(!is.na(results$BQ_ALT[i])&&
results$BQ_ALT[i]<(mean(results$BQ_ALT,na.rm=TRUE)-3*sd(results$BQ_ALT,na.rm=TRUE))){
artifact_score[i]<-artifact_score[i]+input$BQ_AltMean
}
if(!is.na(hotspot[i])){
artifact_score[i]<-artifact_score[i]+input$knownHotspot
}
temp<-frequency_calls[i,17:(length(frequency_calls[1,])-14)]
temp<-temp[,!is.na(temp)]
if(length(intersect(names(temp),
input$overlapTools))==length(input$overlapTools)){
artifact_score[i]<-artifact_score[i]+input$overlapReward
}
if(artifact_score[i]>=input$artifactThreshold){
results$Category[i]<-paste("Artifact (",
artifact_score[i],")",
sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],")",
sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],")",
sep="")
}
}
}
progress_small$close()
#polymorphism score
progress$inc(1/13,detail="-> Perform final filtration")
poly_score<-rep(0,length(results[,1]))
cosmic_flag<-rep(FALSE,length(results[,1]))
progress_small <- shiny::Progress$new()
progress_small$set(message = "Calculate Polymorphism Score",
value = 0)
if(input$polymorphism_score=="No"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,"out of",
length(results[,1])))
if(!is.na(results$nr_samples[i])&&
results$nr_samples[i]>nrsamples){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(results$nr_samples[i])&&
results$nr_samples[i]==1){
poly_score[i]<-poly_score[i]-1
}
if(!is.na(artifact_because[i,4])&&
artifact_because[i,4]>=2){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(artifact_because[i,4])&&
artifact_because[i,4]>=4){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(artifact_because[i,5])&&
artifact_because[i,5]>=2){
poly_score[i]<-poly_score[i]-1
}
if(is.na(artifact_because[i,4])){
poly_score[i]<-poly_score[i]-1
}
if(results$Called[i]>=6){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(results$Consequence[i])&&
vcountPattern(pattern="frameshift",
as.character(results$Consequence[i]))>0&&
vcountPattern(pattern="*",
as.character(results$p.[i]),
fixed = TRUE)==0){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(artifact_because[i,7])&&
artifact_because[i,7]==1){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(results$Prediction[i])&&
(results$Prediction[i]=="Tolerated"||
results$Prediction[i]=="benign"||
results$Prediction[i]=="Neutral")&&
results$Score[i]>=limit_provean2){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(results$Score[i])&&!is.na(results$p.[i])&&
as.character(results$p.[i])!="NA"
&&(results$Score[i]<=limit_provean||
vcountPattern(pattern="*",
as.character(results$p.[i]),
fixed = TRUE)>0)){
poly_score[i]<-poly_score[i]-1
}
if(!is.na(results$Cosmic_Counts[i])&&
results$Cosmic_Counts[i]>100){
cosmic_flag[i]<-TRUE
}
if(is.na(hotspot[i])&&poly_score[i]>=2&&
cosmic_flag[i]==TRUE){
results$Category[i]<-paste(results$Category[i],
"Likely Polymorphism",
sep="")
}
if(is.na(hotspot[i])&&((poly_score[i]>=2&&
cosmic_flag[i]==FALSE)||
poly_score[i]>=3)){
results$Category[i]<-"Polymorphism"
}
}
}
if(input$polymorphism_score=="Yes"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,"out of",
length(results[,1])))
if(!is.na(results$nr_samples[i])&&
results$nr_samples[i]>nrsamples){
poly_score[i]<-poly_score[i]+input$polyDetected
}
if(!is.na(results$nr_samples[i])&&
results$nr_samples[i]==1){
poly_score[i]<-poly_score[i]+input$polyDetectedOnce
}
if(!is.na(artifact_because[i,4])&&
artifact_because[i,4]>=input$polyDatabasesPolyLow){
poly_score[i]<-poly_score[i]+input$polyDatabasesPolyLowReward
}
if(!is.na(artifact_because[i,4])&&
artifact_because[i,4]>=input$polyDatabasesPolyHigh){
poly_score[i]<-poly_score[i]+input$polyDatabasesPolyHighReward
}
if(!is.na(artifact_because[i,5])&&
artifact_because[i,5]>=input$polyDatabasesMut){
poly_score[i]<-poly_score[i]+input$polyDatabasesMutReward
}
if(is.na(artifact_because[i,4])){
poly_score[i]<-poly_score[i]+input$polyNoDatabase
}
if(results$Called[i]>=input$polyDatabases){
poly_score[i]<-poly_score[i]+input$polyDatabasesReward
}
if(!is.na(results$Consequence[i])&&
vcountPattern(pattern="frameshift",
as.character(results$Consequence[i]))>0
&&vcountPattern(pattern="*",
as.character(results$p.[i]),
fixed = TRUE)==0){
poly_score[i]<-poly_score[i]+input$polyEffect
}
if(!is.na(artifact_because[i,7])&&
artifact_because[i,7]==1){
poly_score[i]<-poly_score[i]+input$polyVAF
}
if(!is.na(results$Prediction[i])&&
(results$Prediction[i]=="Tolerated"||
results$Prediction[i]=="benign"||
results$Prediction[i]=="Neutral")&&
results$Score[i]>=limit_provean2){
poly_score[i]<-poly_score[i]+input$polyPrediction
}
if(!is.na(results$Score[i])&&!is.na(results$p.[i])&&
as.character(results$p.[i])!="NA"&&
(results$Score[i]<=limit_provean||
vcountPattern(pattern="*",
as.character(results$p.[i]),
fixed = TRUE)>0)){
poly_score[i]<-poly_score[i]+input$polyPredictionEffect
}
if(!is.na(results$Cosmic_Counts[i])&&
results$Cosmic_Counts[i]>input$polyCosmic){
cosmic_flag[i]<-TRUE
}
if(is.na(hotspot[i])&&
poly_score[i]>=input$polyThresholdCritical&&
cosmic_flag[i]==TRUE){
results$Category[i]<-paste(results$Category[i],
"Likely Polymorphism",
sep="")
}
if(is.na(hotspot[i])&&
((poly_score[i]>=input$polyThresholdCritical&&
cosmic_flag[i]==FALSE)||
poly_score[i]>=input$polyThreshold)){
results$Category[i]<-"Polymorphism"
}
}
}
progress_small$close()
#corrections
progress$inc(1/13,detail="-> Perform final filtration")
progress_small <- shiny::Progress$new()
progress_small$set(message = "Correct Scores", value = 0)
if(input$artifact_score=="No"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,"out of",
length(results[,1])))
if((poly_score[i]>=2&&cosmic_flag[i]==TRUE&&
is.na(hotspot[i]))||
(is.na(hotspot[i])&&((poly_score[i]>=2&&
cosmic_flag[i]==FALSE)||
poly_score[i]>=3))){
if(!is.na(results$VAF[i])&&results$VAF[i]<=0.1){
artifact_score[i]<-artifact_score[i]+5
if(artifact_score[i]>-1){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
if(!is.na(results$VAF[i])&&results$VAF[i]<=0.2){
artifact_score[i]<-artifact_score[i]+2
if(artifact_score[i]>-1){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
if(!is.na(results$Consequence[i])&&
vcountPattern(pattern="frameshift",
results$Consequence[i])>0){
artifact_score[i]<-artifact_score[i]+2
if(artifact_score[i]>-1){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
}
}
}
if(input$artifact_score=="Yes"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,"out of",
length(results[,1])))
if((poly_score[i]>=2&&cosmic_flag[i]==TRUE&&
is.na(hotspot[i]))||(is.na(hotspot[i])&&
((poly_score[i]>=2&&
cosmic_flag[i]==FALSE)||
poly_score[i]>=3))){
if(!is.na(results$VAF[i])&&results$VAF[i]<=0.1){
artifact_score[i]<-artifact_score[i]+input$PolymorphismVAF10
if(artifact_score[i]>=input$artifactThreshold){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
if(!is.na(results$VAF[i])&&results$VAF[i]<=0.2){
artifact_score[i]<-artifact_score[i]+input$PolymorphismVAF20
if(artifact_score[i]>=input$artifactThreshold){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
if(!is.na(results$Consequence[i])&&
vcountPattern(pattern="frameshift",
results$Consequence[i])>0){
artifact_score[i]<-artifact_score[i]+input$PolymorphismFrame
if(artifact_score[i]>=input$artifactThreshold){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
}
}
}
progress_small$close()
#identical calls as polymorphism
progress$inc(1/13,detail="-> Re-consider polymorphisms")
i<-1
while(i<=length(results[,1])){
subset<-results[i:(i+background_info[i]-1),]
if(sum(subset$Category=="Polymorphism",na.rm=TRUE)>=1){
for(j in i:(i+background_info[i]-1)){
if(!is.na(results$VAF[j])&&results$VAF[j]>0.2){
results$Category[j]<-"Polymorphism"
}
}
}
i<-i+background_info[i]
}
results.artifacts<-results[vcountPattern(results$Category,pattern="Artifact")>0 | is.na(results$VAF) | (results$DP-results$Nr_Ref)<nr_alt,]
results.polymorphisms<-results[vcountPattern(results$Category,pattern="Polymorphism")>0 & !is.na(results$VAF) & (results$DP-results$Nr_Ref)>=nr_alt,]
results.mutations<-results[(vcountPattern(results$Category,pattern="True")>0 | vcountPattern(results$Category,pattern="Hotspot")>0) & !is.na(results$VAF) & (results$DP-results$Nr_Ref)>=nr_alt,]
overview4<-cbind(overview4,Mutations=NA,Polymorphisms=NA,
Artifacts=NA)
for(i in seq_along(overview4[,1])){
overview4[i,4]<-length(results.mutations[results.mutations[,1]==overview4[i,1],1])
overview4[i,5]<-length(results.polymorphisms[results.polymorphisms[,1]==overview4[i,1],1])
overview4[i,6]<-length(results.artifacts[results.artifacts[,1]==overview4[i,1],1])
for(j in 2:length(checkpoint[1,])){
if(!is.na(checkpoint[i,j])){
checkpoint[i,j]<-7
}
}
}
write.table(results,paste(input$output_folder,
"/Results_Final.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
write.table(checkpoint,paste(input$output_folder,
"/checkpoint.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
output$table4 <- renderDataTable(datatable(overview4))
output$table_mutations <- renderDataTable(datatable(results.mutations))
output$table_polymorphisms <- renderDataTable(datatable(results.polymorphisms))
output$table_artifacts <- renderDataTable(datatable(results.artifacts))
results.workbook <- createWorkbook()
addWorksheet(wb=results.workbook,sheetName="Mutations")
addWorksheet(wb=results.workbook,sheetName="Polymorphisms")
addWorksheet(wb=results.workbook,sheetName="Artifacts")
writeData(wb=results.workbook,
x=results.mutations,sheet="Mutations")
writeData(wb=results.workbook,
x=results.polymorphisms,sheet="Polymorphisms")
writeData(wb=results.workbook,
x=results.artifacts,sheet="Artifacts")
saveWorkbook(results.workbook,
paste(input$output_folder,"/Results_Final.xlsx",
sep=""),
overwrite = TRUE)
progress$close()
})
observeEvent(input$appreci8Rcheckpoint,{
log_info<-c()
log_info[1]<-"Starting analysis with the appreci8R...<br><br>"
output$log_info<-renderUI({HTML(log_info)})
checkpoint_state<-input$checkpoint
checkpointFile<-read.table(paste(input$output_folder,
"/checkpoint.txt",sep=""),
stringsAsFactors = FALSE,header=TRUE,
sep="\t")
checkpoint<-checkpointFile
#1: After target filtration
if(checkpoint_state==1){
#1. Reading Input
log_info<-c(log_info,"0. Reading input<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "0. Reading input", value = 0)
target_calls<-list()
for(i in 1:(length(checkpointFile[1,])-1)){
progress$inc(1/(length(checkpointFile[1,])-1),
detail=paste("->",
as.character(names(checkpointFile[i+1]))))
target_calls[[i]]<-list()
for(j in seq_along(checkpointFile[,i+1])){
if(!is.na(checkpointFile[j,i+1])){
target_calls[[i]][[j]]<-read.table(paste(input$output_folder,
"/",
as.character(names(checkpointFile)[i+1]),
".",
checkpointFile[j,1],
".target.txt",sep=""),
stringsAsFactors = FALSE,
header=TRUE,
sep="\t")
}
}
}
progress$close()
#2. Normalization
log_info<-c(log_info,"2. Normalization<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "2. Normalization", value = 0)
normalized_calls<-list()
for(i in seq_along(target_calls)){
progress$inc(1/length(target_calls),
detail=paste("->",
as.character(names(checkpointFile[i+1]))))
normalized_calls[[i]]<-list()
if(length(target_calls[[i]])>0){
temp<-target_calls[[i]][[1]]
checkpoint[1,i+1]<-2
if(!is.na(temp[1,2])&&length(checkpointFile[,1])>1){
for(j in 2:length(checkpointFile[,1])){
temp<-rbind(temp,target_calls[[i]][[j]])
checkpoint[j,i+1]<-2
}
}
#GATK
if(i==1&&is.null(input$gatk_indels)){
log_info<-c(log_info,
"Please add GATK if you want to analyze its output<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==1){
if(input$gatk_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$gatk_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#Platypus
if(i==2&&is.null(input$platypus_indels)){
log_info<-c(log_info,
"Please add Platypus if you want to analyze its output<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==2){
if(input$platypus_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$platypus_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#VarScan
if(i==3&&is.null(input$varscan_indels)){
log_info<-c(log_info,
"Please add VarScan if you want to analyze its output<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==3){
if(input$varscan_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$varscan_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
}
#FreeBayes
if(i==4&&is.null(input$freebayes_indels)){
log_info<-c(log_info,
"Please add FreeBayes if you want to analyze its output<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==4){
if(input$freebayes_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$freebayes_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
#LoFreq
if(i==5&&is.null(input$lofreq_indels)){
log_info<-c(log_info,
"Please add LoFreq if you want to analyze its output<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==5){
if(input$lofreq_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$lofreq_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
#SNVer
if(i==6&&is.null(input$snver_indels)){
log_info<-c(log_info,
"Please add SNVer if you want to analyze its output<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==6){
if(input$snver_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$snver_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
#SamTools
if(i==7&&is.null(input$samtools_indels)){
log_info<-c(log_info,
"Please add samtools if you want to analyze its output<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==7){
if(input$samtools_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$samtools_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
#VarDict
if(i==8&&is.null(input$vardict_indels)){
log_info<-c(log_info,
"Please add VarDict if you want to analyze its output<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==8){
if(input$vardict_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$vardict_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
if(length(target_calls)>8){
#Caller 1
if(i==9&&is.null(input$caller1_indels)){
log_info<-c(log_info,
paste("Please add ",
as.character(names(checkpointFile)[i+1]),
"if you want to analyze its output<br>"))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==9){
if(input$caller1_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller1_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
if(length(target_calls)>9){
#Caller 2
if(i==10&&is.null(input$caller2_indels)){
log_info<-c(log_info,
paste("Please add ",
as.character(names(checkpointFile)[i+1]),
"if you want to analyze its output<br>"))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==10){
if(input$caller2_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller2_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,
"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",
sep=""),
row.names=FALSE,quote=FALSE,
sep="\t")
}
if(length(target_calls)>10){
#Caller 3
if(i==11&&is.null(input$caller11_indels)){
log_info<-c(log_info,
paste("Please add ",
as.character(names(checkpointFile)[i+1]),
"if you want to analyze its output<br>"))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==11){
if(input$caller3_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller3_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,
"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",
sep=""),
row.names=FALSE,
quote=FALSE,
sep="\t")
}
if(length(target_calls)>11){
#Caller 4
if(i==12&&
is.null(input$caller12_indels)){
log_info<-c(log_info,
paste("Please add ",
as.character(names(checkpointFile)[i+1]),
"if you want to analyze its output<br>"))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==12){
if(input$caller4_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller4_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,
"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",
sep=""),
row.names=FALSE,
quote=FALSE,
sep="\t")
}
if(length(target_calls)>12){
#Caller 5
if(i==13&&is.null(input$caller13_indels)){
log_info<-c(log_info,
paste("Please add ",
as.character(names(checkpointFile)[i+1]),
"if you want to analyze its output<br>"))
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(i==13){
if(input$caller5_indels=="C>-A"){
temp2<-indel_converter(temp)
temp<-temp2
}
temp2<-check_alternative_bases(temp)
temp<-temp2
if(input$caller5_mnvs=="Yes"){
temp2<-mnv_converter(temp)
temp<-temp2
}
temp2<-string_diff_finder(temp)
temp<-temp2
normalized_calls[[i]]<-temp
write.table(normalized_calls[[i]],
paste(input$output_folder,
"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",
sep=""),
row.names=FALSE,
quote=FALSE,
sep="\t")
}
}
}
}
}
}
}
}
write.table(checkpoint,paste(input$output_folder,
"/checkpoint.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
checkpoint_state<-2
progress$close()
}
#2: After normalization
if(checkpoint_state==2){
if(exists("normalized_calls")==FALSE){
#1. Reading Input
log_info<-c(log_info,"0. Reading input<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "0. Reading input", value = 0)
normalized_calls<-list()
for(i in 1:(length(checkpointFile[1,])-1)){
progress$inc(1/(length(checkpointFile[1,])-1),
detail=paste("->",
as.character(names(checkpointFile[i+1]))))
normalized_calls[[i]]<-list()
if(!is.na(checkpointFile[1,i+1])){
normalized_calls[[i]]<-read.table(paste(input$output_folder,
"/",
as.character(names(checkpointFile)[i+1]),
".normalized.txt",
sep=""),
stringsAsFactors = FALSE,
header=TRUE,
sep="\t")
}
}
progress$close()
}
#3. Annotate
log_info<-c(log_info,"3. Annotate<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "3. Annotate", value = 0)
annotated_calls<-list()
overview3<-checkpointFile
overview3[c(seq_along(checkpointFile[,1])),c(2:length(checkpointFile[1,]))]<-NA
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
connection_txid_symbol<-transcripts(Homo.sapiens,
columns=c("TXID",
"SYMBOL"))
for(i in seq_along(normalized_calls)){
progress$inc(1/length(normalized_calls))
annotated_calls[[i]]<-data.frame()
if(length(normalized_calls[[i]])>0){
progress_small <- shiny::Progress$new()
progress_small$set(message = as.character(names(checkpointFile[i+1])),
value = 0)
test<-VCF(rowRanges=GRanges(seqnames=paste("chr",
as.character(normalized_calls[[i]][,2]),
sep=""),
ranges=IRanges(as.numeric(normalized_calls[[i]][,3]),
(as.numeric(normalized_calls[[i]][,3])+nchar(normalized_calls[[i]][,4])-1))),
fixed=DataFrame(REF=DNAStringSet(normalized_calls[[i]][,4]),
ALT=DNAStringSetList(strsplit(normalized_calls[[i]][,5],",",fixed=TRUE)),
QUAL=1,
FILTER=as.character(normalized_calls[[i]][,1])))
if(is.null(input$locations)){
log_info<-c(log_info,"Please pick at least one location<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$locations)){
located<-locateVariants(test,txdb,AllVariants())
for(j in seq_along(input$locations)){
if(j==1){
of_interest<-data.frame(located$LOCATION==input$locations[j])
}
if(j>1){
of_interest<-data.frame(of_interest,
located$LOCATION==input$locations[j])
}
}
if(length(input$locations)==1){
located<-located[of_interest[,1]>0,]
}
if(length(input$locations)>1){
located<-located[rowSums(of_interest)>0,]
}
}
if(sum(input$locations=="coding")>0&&
is.null(input$consequences)){
log_info<-c(log_info,"Please pick at least one consequence<br>")
output$log_info<-renderUI({HTML(log_info)})
return()
}
if(!is.null(input$consequences)){
predicted<-predictCoding(query=test,
subject=txdb,
seqSource=Hsapiens)
for(j in seq_along(predicted[,1])){
if(as.character(predicted$REFCODON[j])=="CTG"){
if(as.character(predicted$VARCODON[j])=="ATG"){
predicted$CONSEQUENCE[j]<-"nonsynonymous"
}
if(as.character(predicted$VARCODON[j])=="CTA"||
as.character(predicted$VARCODON[j])=="CTC"||
as.character(predicted$VARCODON[j])=="CTT"||
as.character(predicted$VARCODON[j])=="TTA"||
as.character(predicted$VARCODON[j])=="TTG"){
predicted$CONSEQUENCE[j]<-"synonymous"
}
}
if(as.character(predicted$VARCODON[j])=="CTG"){
if(as.character(predicted$REFCODON[j])=="ATG"){
predicted$CONSEQUENCE[j]<-"nonsynonymous"
}
if(as.character(predicted$REFCODON[j])=="CTA"||
as.character(predicted$REFCODON[j])=="CTC"||
as.character(predicted$REFCODON[j])=="CTT"||
as.character(predicted$REFCODON[j])=="TTA"||
as.character(predicted$REFCODON[j])=="TTG"){
predicted$CONSEQUENCE[j]<-"synonymous"
}
}
if(as.character(predicted$REFCODON[j])=="TTG"){
if(as.character(predicted$VARCODON[j])=="ATG"){
predicted$CONSEQUENCE[j]<-"nonsynonymous"
}
if(as.character(predicted$VARCODON[j])=="CTA"||
as.character(predicted$VARCODON[j])=="CTC"||
as.character(predicted$VARCODON[j])=="CTT"||
as.character(predicted$VARCODON[j])=="TTA"||
as.character(predicted$VARCODON[j])=="CTG"){
predicted$CONSEQUENCE[j]<-"synonymous"
}
}
if(as.character(predicted$VARCODON[j])=="TTG"){
if(as.character(predicted$REFCODON[j])=="ATG"){
predicted$CONSEQUENCE[j]<-"nonsynonymous"
}
if(as.character(predicted$REFCODON[j])=="CTA"||
as.character(predicted$REFCODON[j])=="CTC"||
as.character(predicted$REFCODON[j])=="CTT"||
as.character(predicted$REFCODON[j])=="TTA"||
as.character(predicted$REFCODON[j])=="CTG"){
predicted$CONSEQUENCE[j]<-"synonymous"
}
}
}
for(j in seq_along(input$consequences)){
if(j==1){
of_interest<-data.frame(predicted$CONSEQUENCE==input$consequences[j])
}
if(j>1){
of_interest<-data.frame(of_interest,
predicted$CONSEQUENCE==input$consequences[j])
}
}
if(length(input$consequences)==1){
predicted<-predicted[of_interest[,1]>0,]
}
if(length(input$consequences)>1){
predicted<-predicted[rowSums(of_interest)>0,]
}
}
annotated_calls[[i]]<-data.frame(normalized_calls[[i]],
Location=NA,c.=NA,
p.=NA,AA_ref=NA,
AA_alt=NA,
Codon_ref=NA,
Codon_alt=NA,
Consequence=NA,
Gene=NA,GeneID=NA,
TranscriptID=NA)
counter_located<-1
counter_predicted<-1
keep<-rep(TRUE,length(annotated_calls[[i]][,1]))
for(k in seq_along(annotated_calls[[i]][,1])){
progress_small$inc(1/length(annotated_calls[[i]][,1]),
detail=paste("-> Call",k,
"out of",
length(annotated_calls[[i]][,1])))
while(counter_located<=length(ranges(located))&&
start(ranges(located))[counter_located]==annotated_calls[[i]][k,3]){
if(!is.na(annotated_calls[[i]][k,6])){
annotated_calls[[i]][k,6]<-paste(annotated_calls[[i]][k,6],
as.character(located$LOCATION[counter_located]),
sep=",")
annotated_calls[[i]][k,7]<-paste(annotated_calls[[i]][k,7],
as.character(located$LOCSTART[counter_located]),
sep=",")
}
if(is.na(annotated_calls[[i]][k,6])){
annotated_calls[[i]][k,6]<-as.character(located$LOCATION[counter_located])
annotated_calls[[i]][k,7]<-as.character(located$LOCSTART[counter_located])
}
counter_located<-counter_located+1
}
if(!is.na(annotated_calls[[i]][k,6])&&
!is.null(input$consequences)){
for(j in seq_along(strsplit(annotated_calls[[i]][k,6],",")[[1]])){
if(counter_predicted>length(ranges(predicted))||
strsplit(annotated_calls[[i]][k,6],",")[[1]][j]!="coding"){
if(!is.na(annotated_calls[[i]][k,8])){
annotated_calls[[i]][k,8]<-paste(annotated_calls[[i]][k,8],"NA",sep=",")
annotated_calls[[i]][k,9]<-paste(annotated_calls[[i]][k,9],"NA",sep=",")
annotated_calls[[i]][k,10]<-paste(annotated_calls[[i]][k,10],"NA",sep=",")
annotated_calls[[i]][k,11]<-paste(annotated_calls[[i]][k,11],"NA",sep=",")
annotated_calls[[i]][k,12]<-paste(annotated_calls[[i]][k,12],"NA",sep=",")
annotated_calls[[i]][k,13]<-paste(annotated_calls[[i]][k,13],"NA",sep=",")
annotated_calls[[i]][k,14]<-paste(annotated_calls[[i]][k,14],"NA",sep=",")
annotated_calls[[i]][k,15]<-paste(annotated_calls[[i]][k,15],"NA",sep=",")
annotated_calls[[i]][k,16]<-paste(annotated_calls[[i]][k,16],"NA",sep=",")
}
if(is.na(annotated_calls[[i]][k,8])){
annotated_calls[[i]][k,8]<-annotated_calls[[i]][k,9]<-"NA"
annotated_calls[[i]][k,10]<-annotated_calls[[i]][k,11]<-"NA"
annotated_calls[[i]][k,12]<-annotated_calls[[i]][k,13]<-"NA"
annotated_calls[[i]][k,14]<-"NA"
annotated_calls[[i]][k,15]<-annotated_calls[[i]][k,16]<-"NA"
}
}
if(counter_predicted<=length(ranges(predicted))&&
strsplit(annotated_calls[[i]][k,6],",")[[1]][j]=="coding"){
if(start(ranges(predicted))[counter_predicted]==annotated_calls[[i]][k,3]){
if(!is.na(annotated_calls[[i]][k,8])){
annotated_calls[[i]][k,8]<-paste(annotated_calls[[i]][k,8],
as.character(predicted$PROTEINLOC[counter_predicted][[1]][1]),sep=",")
if(as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])!="frameshift"){
if(as.character(predicted$REFCODON[counter_predicted])!="CTG"){
annotated_calls[[i]][k,9]<-paste(annotated_calls[[i]][k,9],
as.character(predicted$REFAA[counter_predicted][[1]][1]),sep=",")
}
if(as.character(predicted$REFCODON[counter_predicted])=="CTG"){
annotated_calls[[i]][k,9]<-paste(annotated_calls[[i]][k,9],
"L",sep=",")
}
if(as.character(predicted$VARCODON[counter_predicted])!="CTG"){
annotated_calls[[i]][k,10]<-paste(annotated_calls[[i]][k,10],
as.character(predicted$VARAA[counter_predicted][[1]][1]),sep=",")
}
if(as.character(predicted$VARCODON[counter_predicted])=="CTG"){
annotated_calls[[i]][k,10]<-paste(annotated_calls[[i]][k,10],"
L",sep=",")
}
}
if(as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])=="frameshift"){
annotated_calls[[i]][k,9]<-paste(annotated_calls[[i]][k,9],"NA",sep=",")
annotated_calls[[i]][k,10]<-paste(annotated_calls[[i]][k,10],"NA",sep=",")
}
annotated_calls[[i]][k,11]<-paste(annotated_calls[[i]][k,11],
as.character(predicted$REFCODON[counter_predicted]),sep=",")
annotated_calls[[i]][k,12]<-paste(annotated_calls[[i]][k,12],
as.character(predicted$VARCODON[counter_predicted]),sep=",")
annotated_calls[[i]][k,13]<-paste(annotated_calls[[i]][k,13],
as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1]),sep=",")
annotated_calls[[i]][k,14]<-paste(annotated_calls[[i]][k,14],
as.character(connection_txid_symbol[as.numeric(predicted$TXID[counter_predicted][[1]][1]),]$SYMBOL),sep=",")
annotated_calls[[i]][k,15]<-paste(annotated_calls[[i]][k,15],
as.character(predicted$GENEID[counter_predicted][[1]][1]),sep=",")
annotated_calls[[i]][k,16]<-paste(annotated_calls[[i]][k,16],
as.character(predicted$TXID[counter_predicted][[1]][1]),sep=",")
}
if(is.na(annotated_calls[[i]][k,8])){
annotated_calls[[i]][k,8]<-as.character(predicted$PROTEINLOC[counter_predicted][[1]][1])
if(as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])!="frameshift"){
if(as.character(predicted$REFCODON[counter_predicted])!="CTG"){
annotated_calls[[i]][k,9]<-as.character(predicted$REFAA[counter_predicted][[1]][1])
}
if(as.character(predicted$REFCODON[counter_predicted])=="CTG"){
annotated_calls[[i]][k,9]<-"L"
}
if(as.character(predicted$VARCODON[counter_predicted])!="CTG"){
annotated_calls[[i]][k,10]<-as.character(predicted$VARAA[counter_predicted][[1]][1])
}
if(as.character(predicted$VARCODON[counter_predicted])=="CTG"){
annotated_calls[[i]][k,10]<-"L"
}
}
if(as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])=="frameshift"){
annotated_calls[[i]][k,9]<-"NA"
annotated_calls[[i]][k,10]<-"NA"
}
annotated_calls[[i]][k,11]<-as.character(predicted$REFCODON[counter_predicted])
annotated_calls[[i]][k,12]<-as.character(predicted$VARCODON[counter_predicted])
annotated_calls[[i]][k,13]<-as.character(predicted$CONSEQUENCE[counter_predicted][[1]][1])
annotated_calls[[i]][k,14]<-as.character(connection_txid_symbol[as.numeric(predicted$TXID[counter_predicted][[1]][1]),]$SYMBOL)
annotated_calls[[i]][k,15]<-as.character(predicted$GENEID[counter_predicted][[1]][1])
annotated_calls[[i]][k,16]<-as.character(predicted$TXID[counter_predicted][[1]][1])
}
counter_predicted<-counter_predicted+1
}
}
}
}
if(is.na(annotated_calls[[i]][k,6])){
keep[k]<-FALSE
}
if(!is.null(input$consequences)&&
!is.na(annotated_calls[[i]][k,6])&&
sum(strsplit(annotated_calls[[i]][k,6],",")[[1]]=="coding")>0&&
(is.na(annotated_calls[[i]][k,8])||
sum(strsplit(annotated_calls[[i]][k,8],",")[[1]]=="NA")==length(strsplit(annotated_calls[[i]][k,8],",")[[1]]))){
keep[k]<-FALSE
}
}
annotated_calls[[i]]<-annotated_calls[[i]][keep,]
for(k in seq_along(overview3[,1])){
overview3[k,i+1]<-length(annotated_calls[[i]][annotated_calls[[i]][,1]==overview3[k,1],1])
checkpoint[k,i+1]<-3
}
write.table(annotated_calls[[i]],
paste(input$output_folder,"/",
as.character(names(checkpointFile)[i+1]),
".annotated.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
progress_small$close()
}
}
write.table(checkpoint,
paste(input$output_folder,"/checkpoint.txt",
sep=""),row.names=FALSE,quote=FALSE,
sep="\t")
output$table3 <- renderDataTable(datatable(overview3))
checkpoint_state<-3
progress$close()
}
#3: After annotation
if(checkpoint_state==3){
if(exists("annotated_calls")==FALSE){
#1. Reading Input
log_info<-c(log_info,"0. Reading input<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "0. Reading input", value = 0)
annotated_calls<-list()
for(i in 1:(length(checkpointFile[1,])-1)){
progress$inc(1/(length(checkpointFile[1,])-1),
detail=paste("->",
as.character(names(checkpointFile[i+1]))))
annotated_calls[[i]]<-data.frame()
if(!is.na(checkpointFile[1,i+1])){
annotated_calls[[i]]<-read.table(paste(input$output_folder,
"/",
as.character(names(checkpointFile)[i+1]),
".annotated.txt",
sep=""),
stringsAsFactors=FALSE,
header=TRUE,
sep="\t")
}
}
progress$close()
}
#4. Combine
log_info<-c(log_info,"4. Combine Output<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "4. Combine Output", value = 0)
combined_calls<-data.frame(SampleID=NA,Chr=NA,Pos=NA,
Ref=NA,Alt=NA,Location=NA,
c.=NA,p.=NA,AA_ref=NA,AA_alt=NA,
Codon_ref=NA,Codon_alt=NA,
Consequence=NA,Gene=NA,GeneID=NA,
TranscriptID=NA,GATK=NA,
Platypus=NA,VarScan=NA,
FreeBayes=NA,LoFreq=NA,SNVer=NA,
SamTools=NA,VarDict=NA)
if(length(annotated_calls)>8){
combined_calls<-cbind(combined_calls,Caller1=NA)
if(length(annotated_calls)>9){
combined_calls<-cbind(combined_calls,Caller2=NA)
if(length(annotated_calls)>10){
combined_calls<-cbind(combined_calls,Caller3=NA)
if(length(annotated_calls)>11){
combined_calls<-cbind(combined_calls,
Caller4=NA)
if(length(annotated_calls)>12){
combined_calls<-cbind(combined_calls,
Caller5=NA)
}
}
}
}
}
combined_calls_temp<-combined_calls
overview4<-cbind(checkpointFile[,1],RawCalls=NA)
for(i in seq_along(annotated_calls)){
if(length(annotated_calls[[i]])>0){
temp<-annotated_calls[[i]]
add_to_temp<-matrix(rep(NA,
(length(combined_calls[1,])-16)),
ncol=(length(combined_calls[1,])-16))
temp<-cbind(temp,add_to_temp)
names(temp)<-names(combined_calls)
temp[,16+i]<-1
combined_calls_temp<-rbind(combined_calls_temp,temp)
}
}
combined_calls_temp<-combined_calls_temp[2:length(combined_calls_temp[,1]),]
combined_calls_temp_sorted<-combined_calls_temp[order(combined_calls_temp[,2],
combined_calls_temp[,3],
combined_calls_temp[,4],
combined_calls_temp[,5],
combined_calls_temp[,1]),]
combined_calls<-combined_calls_temp_sorted[1,]
counter<-1
for(i in 2:length(combined_calls_temp_sorted[,1])){
progress$inc(1/length(combined_calls_temp_sorted[,1]))
if(combined_calls[counter,1]==combined_calls_temp_sorted[i,1]&&
combined_calls[counter,2]==combined_calls_temp_sorted[i,2]&&
combined_calls[counter,3]==combined_calls_temp_sorted[i,3]&&
combined_calls[counter,4]==combined_calls_temp_sorted[i,4]&&
combined_calls[counter,5]==combined_calls_temp_sorted[i,5]){
for(j in 17:length(combined_calls[1,])){
if(!is.na(combined_calls[counter,j])||
!is.na(combined_calls_temp_sorted[i,j])){
combined_calls[counter,j]<-1
}
}
}
if(combined_calls[counter,1]!=combined_calls_temp_sorted[i,1]||
combined_calls[counter,2]!=combined_calls_temp_sorted[i,2]||
combined_calls[counter,3]!=combined_calls_temp_sorted[i,3]||
combined_calls[counter,4]!=combined_calls_temp_sorted[i,4]||
combined_calls[counter,5]!=combined_calls_temp_sorted[i,5]){
counter<-counter+1
combined_calls<-rbind(combined_calls,
combined_calls_temp_sorted[i,])
}
}
temp<-unique(combined_calls)
combined_calls<-temp
for(i in seq_along(overview4[,1])){
overview4[i,2]<-length(combined_calls[combined_calls[,1]==overview4[i,1],1])
for(j in seq_along(annotated_calls)){
if(length(annotated_calls[[j]])>0){
checkpoint[i,j+1]<-4
}
}
}
write.table(combined_calls,
paste(input$output_folder,"/Results_Raw.txt",
sep=""),row.names=FALSE,quote=FALSE,
sep="\t")
write.table(checkpoint,
paste(input$output_folder,"/checkpoint.txt",
sep=""),row.names=FALSE,quote=FALSE,
sep="\t")
output$table4 <- renderDataTable(datatable(overview4))
checkpoint_state<-4
progress$close()
}
#4: After combination
if(checkpoint_state==4){
if(exists("combined_calls")==FALSE){
#1. Reading Input
log_info<-c(log_info,"0. Reading input<br>")
output$log_info<-renderUI({HTML(log_info)})
combined_calls<-read.table(paste(input$output_folder,
"/Results_Raw.txt",
sep=""),
stringsAsFactors = FALSE,
header=TRUE,sep="\t")
}
#5. Pileup
log_info<-c(log_info,"5. Evaluate Coverage and BQ<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "5. Evaluate Coverage and BQ",
value = 0)
results<-cbind(combined_calls[,c(1:5)],Nr_Ref=NA,Nr_Alt=NA,
DP=NA,VAF=NA,BQ_REF=NA,BQ_ALT=NA,
Nr_Ref_fwd=NA,Nr_Alt_fwd=NA,DP_fwd=NA,
VAF_fwd=NA,Nr_Ref_rev=NA,Nr_Alt_rev=NA,
DP_rev=NA,VAF_rev=NA)
folder<-input$bam_folder
for(i in seq_along(results[,1])){
progress$inc(1/length(results[,1]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
done<-FALSE
#SNVs
if(nchar(results[i,4])==1&&nchar(results[i,5])==1){
results_temp<-getCharacteristicsFreq(results[i,2],
results[i,3],
results[i,3],
results[i,4],
results[i,5],
folder,
results[i,1])
results[i,6:19]<-results_temp[1,6:19]
if(results[i,8]>=input$dp&&
results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
results[i,3],
results[i,3],
results[i,4],
results[i,5],
folder,
results[i,1])
results[i,10:11]<-results_temp[1,6:7]
}
done<-TRUE
}
#Deletions
if(done==FALSE&&nchar(results[i,4])>1&&
nchar(results[i,5])==1
&&substr(results[i,4],1,1)==results[i,5]){
if(nchar(results[i,4])==2){
results_temp<-getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+1,
as.numeric(results[i,3])+1,
substr(results[i,4],2,2),
"-",folder,
results[i,1])
results[i,6:19]<-results_temp[1,6:19]
if(results[i,8]>=input$dp&&
results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+1,
as.numeric(results[i,3])+1,
substr(results[i,4],2,2),
"-",
folder,
results[i,1])
results[i,10:11]<-results_temp[1,6:7]
}
}
if(nchar(results[i,4])>2){
results_temp<-getCharacteristicsFreq(results[i,2],as.numeric(results[i,3])+1,
as.numeric(results[i,3])+1,
substr(results[i,4],2,2),"-",folder,results[i,1])
for(j in 3:nchar(results[i,4])){
results_temp<-rbind(results_temp,
getCharacteristicsFreq(results[i,2],as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),"-",folder,results[i,1]))
}
for(j in 6:19){
results[i,j]<-min(results_temp[,j])
}
if(results[i,8]>=input$dp&&results[i,7]>=input$nr_alt&&(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],as.numeric(results[i,3])+1,
as.numeric(results[i,3])+1,
substr(results[i,4],2,2),"-",folder,results[i,1])
for(j in 3:nchar(results[i,4])){
results_temp<-rbind(results_temp,
getCharacteristicsBQ(results[i,2],as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),"-",folder,results[i,1]))
}
for(j in 6:7){
results_temp[1,j]<-min(results_temp[,j])
}
results[i,10:11]<-results_temp[1,6:7]
}
}
done<-TRUE
}
#Insertions (summed up as +)
if(done==FALSE&&nchar(results[i,4])==1&&nchar(results[i,5])>1
&&substr(results[i,5],1,1)==results[i,4]){
results_temp<-getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3]),
as.numeric(results[i,3]),
results[i,4],
"+",folder,
results[i,1])
results[i,6:19]<-results_temp[1,6:19]
if(results[i,8]>=input$dp&&
results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3]),
as.numeric(results[i,3]),
results[i,4],
"+",folder,
results[i,1])
results[i,10:11]<-results_temp[1,6:7]
}
done<-TRUE
}
#Complex Indels
if(done==FALSE){
results_temp<-getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3]),
as.numeric(results[i,3]),
substr(results[i,4],1,1),
substr(results[i,5],1,1),
folder,results[i,1])
for(j in 2:min(nchar(results[i,4]),nchar(results[i,5]))){
results_temp<-rbind(results_temp,
getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
substr(results[i,5],j,j),
folder,results[i,1]))
}
#Del in the end
if(nchar(results[i,4])>nchar(results[i,5])){
results_temp<-rbind(results_temp,
getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+j,
as.numeric(results[i,3])+j,
substr(results[i,4],j+1,j+1),
"-",
folder,results[i,1]))
}
#Ins in the end
if(nchar(results[i,4])>nchar(results[i,5])){
results_temp<-rbind(results_temp,
getCharacteristicsFreq(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
"+",
folder,results[i,1]))
}
for(j in 6:19){
results[i,j]<-min(results_temp[,j])
}
if(results[i,8]>=input$dp&&
results[i,7]>=input$nr_alt&&
(results[i,9]*100)>=input$vaf){
results_temp<-getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3]),
as.numeric(results[i,3]),
substr(results[i,4],1,1),
substr(results[i,5],1,1),
folder,
results[i,1])
for(j in 2:min(nchar(results[i,4]),nchar(results[i,5]))){
results_temp<-rbind(results_temp,
getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
substr(results[i,5],j,j),
folder,results[i,1]))
}
#Del in the end
if(nchar(results[i,4])>nchar(results[i,5])){
results_temp<-rbind(results_temp,
getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+j,
as.numeric(results[i,3])+j,
substr(results[i,4],j+1,j+1),
"-",
folder,results[i,1]))
}
#Ins in the end
if(nchar(results[i,4])>nchar(results[i,5])){
results_temp<-rbind(results_temp,
getCharacteristicsBQ(results[i,2],
as.numeric(results[i,3])+j-1,
as.numeric(results[i,3])+j-1,
substr(results[i,4],j,j),
"+",
folder,results[i,1]))
}
for(j in 6:7){
results_temp[1,j]<-min(results_temp[,j])
}
results[i,10:11]<-results_temp[1,6:7]
}
}
}
frequency_calls_temp<-cbind(combined_calls,
results[,c(6:19)])
include1<-results[,8]>=input$dp
include2<-results[,7]>=input$nr_alt
include3<-(results[,9]*100)>=input$vaf
include4<-results[,11]>=input$bq
for(i in seq_along(results[,1])){
if(is.na(results[i,10])){
results[i,10]<-0
}
}
include5<-(results[,10]-results[,11])<=input$bq_diff
frequency_calls<-frequency_calls_temp[rowSums(cbind(include1,include2,include3,include4,include5))>=5&!is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
if(exists("overview4")==TRUE){
overview4<-cbind(overview4,VAFandBQFiltered=NA)
}
if(exists("overview4")==FALSE){
overview4<-cbind(checkpointFile[,1],RawCalls=NA,
VAFandBQFiltered=NA)
}
for(i in seq_along(overview4[,1])){
overview4[i,3]<-length(frequency_calls[frequency_calls[,1]==overview4[i,1],1])
for(j in 2:length(checkpoint[1,])){
if(!is.na(checkpoint[i,j])){
checkpoint[i,j]<-5
}
}
}
write.table(frequency_calls,
paste(input$output_folder,
"/Results_Frequency.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
write.table(checkpoint,
paste(input$output_folder,"/checkpoint.txt",
sep=""),row.names=FALSE,quote=FALSE,
sep="\t")
output$table4 <- renderDataTable(datatable(overview4))
checkpoint_state<-5
progress$close()
}
#5: After coverage and BQ filtration
if(checkpoint_state==5){
if(exists("frequency_calls")==FALSE){
#1. Reading Input
log_info<-c(log_info,"0. Reading input<br>")
output$log_info<-renderUI({HTML(log_info)})
frequency_calls<-read.table(paste(input$output_folder,
"/Results_Frequency.txt",
sep=""),
stringsAsFactors = FALSE,
header=TRUE,sep="\t")
}
#6. Extended Characteristics
log_info<-c(log_info,
"6. Determine Extended Set of Characteristics<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "6. Determine Extended Set of Characteristics (databases)",
value = 0)
progress$inc(0,detail="-> Downloading databases ")
results<-data.frame(frequency_calls[,c(1:5)])
results<-cbind(results,dbSNP=NA,dbSNP_MAF=NA)
snps<-SNPlocs.Hsapiens.dbSNP144.GRCh37
indels<-XtraSNPlocs.Hsapiens.dbSNP144.GRCh37
if(!is.null(input$`1kgenomes`)){
results<-cbind(results,G1000_AF=NA)
g1000<-MafDb.1Kgenomes.phase3.hs37d5
}
if(!is.null(input$exac)){
results<-cbind(results,ExAC_AF=NA)
exac<-MafDb.ExAC.r1.0.hs37d5
}
if(!is.null(input$gad)){
results<-cbind(results,GAD_AF=NA)
gad<-MafDb.gnomADex.r2.1.hs37d5
}
if(!is.null(input$cosmic)){
results<-cbind(results,CosmicID=NA,Cosmic_Counts=NA)
cosmic_67<-c()
data(cosmic_67,envir=environment(),package="COSMIC.67")
}
if(!is.null(input$clinvar)){
results<-cbind(results,ClinVar=NA)
clinvar<-data.frame(Gene=NA,Start=NA,Stop=NA,Ref=NA,
Alt=NA,Sig=NA)
genes_temp<-c()
for(i in seq_along(frequency_calls[,1])){
genes_temp<-c(genes_temp,
strsplit(frequency_calls[i,14],
split=",")[[1]])
}
genes<-unique(genes_temp[genes_temp!="NA"])
for(i in seq_along(genes)){
res<-entrez_search("clinvar",term=genes[i])
cv<-entrez_summary("clinvar",id=res$ids)
info<-extract_from_esummary(cv,
"variation_set",
simplify=FALSE)
significance<-extract_from_esummary(cv,
"clinical_significance",
simplify=FALSE)
for(j in seq_along(res$ids)){
info2<-info[res$ids[j]][[1]][[1]]
significance2<-significance[res$ids[j]][[1]][[1]]
if(length(info2$variation_loc[[1]])){
for(k in seq_along(info2$variation_loc[[1]][,1])){
if(info2$variation_loc[[1]][k,2]=="GRCh37"){
temp<-data.frame(Gene=NA,Start=NA,
Stop=NA,Ref=NA,Alt=NA)
temp[1,1]<-genes[i]
temp[1,2]<-info2$variation_loc[[1]][k,5]
temp[1,3]<-info2$variation_loc[[1]][k,6]
temp[1,4]<-info2$variation_loc[[1]][k,15]
temp[1,5]<-info2$variation_loc[[1]][k,16]
temp[1,6]<-significance2$description
if(!is.na(clinvar[1,1])){
clinvar<-rbind(clinvar,temp)
}
if(is.na(clinvar[1,1])){
clinvar<-temp
}
}
}
}
}
}
}
c.<-c()
c.complement<-c()
p.<-c()
for(i in seq_along(frequency_calls[,1])){
progress$inc(0,detail="-> Pre-processing of the calls ")
for(j in 1:(length(strsplit(frequency_calls[i,7],
split=",")[[1]]))){
if(j==1){
c.[i]<-paste("c.",
strsplit(frequency_calls[i,7],
split=",")[[1]][j],
frequency_calls[i,4],">",
frequency_calls[i,5],sep="")
c.complement[i]<-paste("c.",
strsplit(frequency_calls[i,7],
split=",")[[1]][j],
as.character(complement(DNAString(frequency_calls[i,4]))),
">",
as.character(complement(DNAString(frequency_calls[i,5]))),
sep="")
if(!is.na(strsplit(frequency_calls[i,11],split=",")[[1]][j])&&
!is.na(strsplit(frequency_calls[i,12],split=",")[[1]][j])&&
strsplit(frequency_calls[i,11],split=",")[[1]][j]!="NA"&&
strsplit(frequency_calls[i,12],split=",")[[1]][j]!="NA"&&
nchar(strsplit(frequency_calls[i,11],split=",")[[1]][j])==3&&
nchar(strsplit(frequency_calls[i,12],split=",")[[1]][j])==3){
p.[i]<-paste("p.",
strsplit(frequency_calls[i,9],split=",")[[1]][j],
strsplit(frequency_calls[i,8],split=",")[[1]][j],
strsplit(frequency_calls[i,10],split=",")[[1]][j],
sep="")
}
if(!is.na(strsplit(frequency_calls[i,11],split=",")[[1]][j])&&
!is.na(strsplit(frequency_calls[i,12],split=",")[[1]][j])&&
strsplit(frequency_calls[i,11],split=",")[[1]][j]!="NA"&&
strsplit(frequency_calls[i,12],split=",")[[1]][j]!="NA"&&
(nchar(strsplit(frequency_calls[i,11],split=",")[[1]][j])!=3||
nchar(strsplit(frequency_calls[i,12],split=",")[[1]][j])!=3)){
if((nchar(strsplit(frequency_calls[i,11],split=",")[[1]][j])%%3)!=0||
(nchar(strsplit(frequency_calls[i,12],split=",")[[1]][j])%%3)!=0){
p.[i]<-paste("p.",
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,11],split=",")[[1]][j]))),
strsplit(frequency_calls[i,8],split=",")[[1]][j],
"fs",sep="")
}
if((nchar(strsplit(frequency_calls[i,11],split=",")[[1]][j])%%3)==0&&
(nchar(strsplit(frequency_calls[i,12],split=",")[[1]][j])%%3)==0){
p.[i]<-paste("p.",
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,11],split=",")[[1]][j]))),
strsplit(frequency_calls[i,8],split=",")[[1]][j],
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,12],split=",")[[1]][j]))),sep="")
}
}
}
if(j>1){
c.[i]<-paste(c.[i],
paste("c.",
strsplit(frequency_calls[i,7],split=",")[[1]][j],
frequency_calls[i,4],">",
frequency_calls[i,5],sep=""),
sep=",")
c.complement[i]<-paste(c.complement[i],
paste("c.",
strsplit(frequency_calls[i,7],split=",")[[1]][j],
as.character(complement(DNAString(frequency_calls[i,4]))),
">",
as.character(complement(DNAString(frequency_calls[i,5]))),
sep=""),sep=",")
if(!is.na(strsplit(frequency_calls[i,11],split=",")[[1]][j])&&
!is.na(strsplit(frequency_calls[i,12],split=",")[[1]][j])&&
strsplit(frequency_calls[i,11],split=",")[[1]][j]!="NA"&&
strsplit(frequency_calls[i,12],split=",")[[1]][j]!="NA"&&
nchar(strsplit(frequency_calls[i,11],split=",")[[1]][j])==3&&
nchar(strsplit(frequency_calls[i,12],split=",")[[1]][j])==3){
p.[i]<-paste(p.[i],
paste("p.",
strsplit(frequency_calls[i,9],split=",")[[1]][j],
strsplit(frequency_calls[i,8],split=",")[[1]][j],
strsplit(frequency_calls[i,10],split=",")[[1]][j],
sep=""),
sep=",")
}
if(!is.na(strsplit(frequency_calls[i,11],split=",")[[1]][j])&&
!is.na(strsplit(frequency_calls[i,12],split=",")[[1]][j])&&
strsplit(frequency_calls[i,11],split=",")[[1]][j]!="NA"&&
strsplit(frequency_calls[i,12],split=",")[[1]][j]!="NA"&&
(nchar(strsplit(frequency_calls[i,11],split=",")[[1]][j])!=3||
nchar(strsplit(frequency_calls[i,12],split=",")[[1]][j])!=3)){
if((nchar(strsplit(frequency_calls[i,11],split=",")[[1]][j])%%3)!=0||
(nchar(strsplit(frequency_calls[i,12],split=",")[[1]][j])%%3)!=0){
p.[i]<-paste(p.[i],
paste("p.",
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,11],split=",")[[1]][j]))),
strsplit(frequency_calls[i,8],split=",")[[1]][j],
"fs",sep=""),
sep=",")
}
if((nchar(strsplit(frequency_calls[i,11],split=",")[[1]][j])%%3)==0&&
(nchar(strsplit(frequency_calls[i,12],split=",")[[1]][j])%%3)==0){
p.[i]<-paste(p.[i],
paste("p.",
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,11],split=",")[[1]][j]))),
strsplit(frequency_calls[i,8],split=",")[[1]][j],
as.character(Biostrings::translate(DNAString(strsplit(frequency_calls[i,12],split=",")[[1]][j]))),sep=""),sep=",")
}
}
}
}
}
for(i in seq_along(frequency_calls[,1])){
progress$inc(1/length(results[,1]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
#SNPs
if(nchar(frequency_calls[i,4])==1&&
nchar(frequency_calls[i,5])==1){
snp_info<-snpsByOverlaps(snps,
paste(frequency_calls[i,2],
":",
frequency_calls[i,3],
"-",
frequency_calls[i,3],
sep=""))
if(length(snp_info)>0){
snp_info<-snp_info[pos(snp_info)==frequency_calls[i,3],]
if(length(snp_info)>0){
if(length(grep(results[i,5],
IUPAC_CODE_MAP[snp_info$alleles_as_ambig]))>0||
(length(grep(results[i,4],
IUPAC_CODE_MAP[snp_info$alleles_as_ambig]))==0&&
length(grep(as.character(complement(DNAString(results[i,5]))),
IUPAC_CODE_MAP[snp_info$alleles_as_ambig])>0))){
results[i,6]<-snp_info$RefSNP_id
}
}
}
if(!is.null(input$`1kgenomes`)){
snp_info<-gscores(g1000,
GRanges(paste(frequency_calls[i,2],
":",
frequency_calls[i,3],
sep="")))
if(length(snp_info)>0){
results$G1000_AF[i]<-max(snp_info$AF)
}
}
if(!is.null(input$exac)){
snp_info<-gscores(exac,
GRanges(paste(frequency_calls[i,2],
":",
frequency_calls[i,3],
sep="")))
if(length(snp_info)>0){
results$ExAC_AF[i]<-max(snp_info$AF)
}
}
if(!is.null(input$gad)){
snp_info<-gscores(gad,
GRanges(paste(frequency_calls[i,2],
":",
frequency_calls[i,3],
sep="")))
if(length(snp_info)>0){
results$GAD_AF[i]<-max(snp_info$AF)
}
}
if(!is.null(input$cosmic)){
snp_info<-rowRanges(cosmic_67)[as.character(seqnames(rowRanges(cosmic_67)))==frequency_calls[i,2]&start(ranges(rowRanges(cosmic_67)))==frequency_calls[i,3]]
if(length(snp_info)>0){
for(j in seq_along(snp_info[,1])){
if(snp_info$REF==frequency_calls[i,4]&&
snp_info$ALT[[1]]==frequency_calls[i,5]||
(snp_info$REF==as.character(complement(DNAString(frequency_calls[i,4])))&&
snp_info$ALT[[1]]==as.character(complement(DNAString(frequency_calls[i,5]))))){
snp_info2<-info(cosmic_67)[rownames(info(cosmic_67))==names(snp_info[j,]),]
grep_c.<-grep(snp_info2$CDS,
as.character(strsplit(c.[i],split=",")[[1]]))
grep_c.comp<-grep(snp_info2$CDS,
as.character(strsplit(c.complement[i],split=",")[[1]]))
grep_p.<-grep(snp_info2$AA,
as.character(strsplit(p.[i],split=",")[[1]]))
if(length(intersect(grep_c.,grep_p.))>0||
length(intersect(grep_c.comp,grep_p.))>0){
if(!is.na(results$CosmicID[i])){
results$CosmicID[i]<-paste(results$CosmicID[i],
names(snp_info[j,]),sep=",")
results$Cosmic_Counts[i]<-paste(results$Cosmic_Counts[i],
snp_info2$CNT,sep=",")
}
if(is.na(results$CosmicID[i])){
results$CosmicID[i]<-names(snp_info[j,])
results$Cosmic_Counts[i]<-snp_info2$CNT
}
}
}
}
}
}
if(!is.null(input$clinvar)){
snp_info_temp<-data.frame()
for(j in seq_along(strsplit(frequency_calls[i,14],
split=",")[[1]])){
if(!is.na(strsplit(frequency_calls[i,14],split=",")[[1]][j])){
temp<-clinvar[grep(strsplit(frequency_calls[i,14],split=",")[[1]][j],clinvar[,1]),]
temp2<-temp[nchar(temp[,4])==1&nchar(temp[,5])==1&temp[,4]!="-"&temp[,5]!="-",]
if(length(snp_info_temp)>0){
snp_info_temp<-rbind(snp_info_temp,
temp2)
}
if(length(snp_info_temp[1,1])==0){
snp_info_temp<-temp2
}
}
}
snp_info<-unique(snp_info_temp)
if(length(snp_info)>0){
snp_info2<-snp_info[snp_info[,2]==frequency_calls[i,3],]
if(length(snp_info2[,1])>0){
if((snp_info2[1,4]==frequency_calls[i,4]&&
snp_info2[1,5]==frequency_calls[i,5])||
(snp_info2[1,4]==as.character(complement(DNAString(frequency_calls[i,4])))&&
snp_info2[1,5]==as.character(complement(DNAString(frequency_calls[i,5]))))){
results$ClinVar[i]<-snp_info2[1,6]
}
}
}
}
}
#Indels
if(nchar(frequency_calls[i,4])!=1||
nchar(frequency_calls[i,5])!=1){
suppressWarnings(snp_info<-snpsByOverlaps(indels,paste("ch",frequency_calls[i,2],":",frequency_calls[i,3],"-",(as.numeric(frequency_calls[i,3])+nchar(frequency_calls[i,4])-1),sep="")))
if(length(snp_info)>0){
snp_info_rs<-snp_info$RefSNP_id[(start(ranges(snp_info))<=frequency_calls[i,3])&(end(ranges(snp_info))>=(as.numeric(frequency_calls[i,3])+nchar(frequency_calls[i,4])-1))]
if(length(snp_info_rs)>0){
ncbi<-ncbi_snp_query(snp_info_rs)
for(j in seq_along(ncbi[,1])){
if(nchar(results[i,4])>nchar(results[i,5])){
if(length(grep(substr(results[i,4],
2,
nchar(results[i,4])),
ncbi[j,9]))>0){
results[i,6]<-ncbi[j,1]
}
}
if(nchar(results[i,4])<nchar(results[i,5])){
if(length(grep(substr(results[i,5],
2,
nchar(results[i,5])),
ncbi[j,9]))>0){
results[i,6]<-ncbi[j,1]
}
}
}
}
}
if(!is.null(input$cosmic)){
snp_info<-rowRanges(cosmic_67)[as.character(seqnames(rowRanges(cosmic_67)))==frequency_calls[i,2]&start(ranges(rowRanges(cosmic_67)))==frequency_calls[i,3]]
if(length(snp_info)>0){
for(j in seq_along(snp_info[,1])){
if(snp_info$REF==frequency_calls[i,4]&&
snp_info$ALT[[1]]==frequency_calls[i,5]||
(snp_info$REF==as.character(complement(DNAString(frequency_calls[i,4])))&&
snp_info$ALT[[1]]==as.character(complement(DNAString(frequency_calls[i,5]))))){
snp_info2<-info(cosmic_67)[rownames(info(cosmic_67))==names(snp_info[j,]),]
grep_c.<-grep(snp_info2$CDS,
as.character(strsplit(c.[i],split=",")[[1]]))
grep_c.comp<-grep(snp_info2$CDS,
as.character(strsplit(c.complement[i],split=",")[[1]]))
grep_p.<-grep(snp_info2$AA,
as.character(strsplit(p.[i],split=",")[[1]]))
if(length(intersect(grep_c.,grep_p.))>0||
length(intersect(grep_c.comp,grep_p.))>0){
if(!is.na(results$CosmicID[i])){
results$CosmicID[i]<-paste(results$CosmicID[i],names(snp_info[j,]),sep=",")
results$Cosmic_Counts[i]<-paste(results$Cosmic_Counts[i],snp_info2$CNT,sep=",")
}
if(is.na(results$CosmicID[i])){
results$CosmicID[i]<-names(snp_info[j,])
results$Cosmic_Counts[i]<-snp_info2$CNT
}
}
}
}
}
}
if(!is.null(input$clinvar)){
snp_info_temp<-data.frame()
for(j in seq_along(strsplit(frequency_calls[i,14],
split=",")[[1]])){
if(!is.na(strsplit(frequency_calls[i,14],
split=",")[[1]][j])){
temp<-clinvar[grep(strsplit(frequency_calls[i,14],
split=",")[[1]][j],
clinvar[,1]),]
temp2<-temp[nchar(temp[,4])>1|nchar(temp[,5])>1|temp[,4]=="-"|temp[,5]=="-",]
if(length(snp_info_temp)>0){
snp_info_temp<-rbind(snp_info_temp,
temp2)
}
if(length(snp_info_temp[1,1])==0){
snp_info_temp<-temp2
}
}
}
snp_info<-unique(snp_info_temp)
if(length(snp_info)>0){
snp_info2<-snp_info[snp_info[,2]==(as.numeric(frequency_calls[i,3])-1),]
if(length(snp_info2[,1])>0){
for(j in seq_along(snp_info2[,1])){
if(snp_info2[j,4]=="-"&&
snp_info2[j,5]==substr(frequency_calls[i,5],
2,
nchar(frequency_calls[i,5]))){
results$ClinVar[i]<-snp_info2[j,6]
}
if(snp_info2[j,5]=="-"&&
snp_info2[j,4]==substr(frequency_calls[i,4],
2,
nchar(frequency_calls[i,4]))){
results$ClinVar[i]<-snp_info2[j,6]
}
}
}
}
}
}
}
if(length(results[!is.na(results[,6]),6])<=3){
suppressWarnings(ncbi<-ncbi_snp_query(results[!is.na(results[,6]),6]))
}
if(length(results[!is.na(results[,6]),6])>3){
abfrage<-results[!is.na(results[,6]),6]
if(((length(results[!is.na(results[,6]),6])-1)%%3)==0){
limits<-seq(1,
length(results[!is.na(results[,6]),6]),
3)
}
if(((length(results[!is.na(results[,6]),6])-1)%%3)!=0){
limits<-c(seq(1,
length(results[!is.na(results[,6]),6]),
3),
length(results[!is.na(results[,6]),6]))
}
suppressWarnings(ncbi<-ncbi_snp_query(abfrage[1:3]))
for(i in 2:(length(limits)-1)){
suppressWarnings(temp<-ncbi_snp_query(abfrage[limits[i]:(limits[i+1]-1)]))
ncbi<-rbind(ncbi,temp)
}
}
for(i in seq_along(results[,1])){
if(!is.na(results[i,6])){
results$dbSNP_MAF[i]<-as.numeric(max(ncbi[ncbi[,1]==results[i,6],10]))
if(sum(ncbi[ncbi[,1]==results[i,6],9]==results[i,4],na.rm=TRUE)>0){
if(!is.na(results$dbSNP_MAF[i])){
results$dbSNP_MAF[i]<-1-results$dbSNP_MAF[i]
}
if(!is.na(results$G1000_AF[i])){
results$G1000_AF[i]<-1-results$G1000_AF[i]
}
if(!is.na(results$ExAC_AF[i])){
results$ExAC_AF[i]<-1-results$ExAC_AF[i]
}
if(!is.na(results$GAD_AF[i])){
results$GAD_AF[i]<-1-results$GAD_AF[i]
}
}
}
}
progress$close()
results<-cbind(results,Prediction=NA,Score=NA)
progress <- shiny::Progress$new()
progress$set(message = "6. Determine Extended Set of Characteristics (prediction)",
value = 0)
if(input$predict!="PolyPhen2"){
for(i in seq(1,length(results[,6]))[!is.na(results[,6])]){
progress$inc(1/length(seq(1,length(results[,6]))[!is.na(results[,6])]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
suppressWarnings(info<-select(SIFT.Hsapiens.dbSNP137,keys=substr(results[i,6],3,nchar(results[i,6]))))
if(length(info)>0){
if(input$predict=="SIFT"){
#score <0.05 -> damaging (else: tolerated)
results$Prediction[i]<-info[which.min(info[,15]),16]
results$Score[i]<-min(info[,15])
}
if(input$predict=="Provean"){
#score <-2.5 -> deleterious (else: neutral)
results$Prediction[i]<-info[which.min(info[,11]),12]
results$Score[i]<-min(info[,11])
}
}
}
}
if(input$predict=="PolyPhen2"){
#Polyphen (probably damaging, possibly damaging, benign,
#unknown); probability of variant being damaging
for(i in seq(1,length(results[,6]))[!is.na(results[,6])]){
progress$inc(1/length(seq(1,length(results[,6]))[!is.na(results[,6])]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
suppressWarnings(info<-select(PolyPhen.Hsapiens.dbSNP131,keys=results[i,6]))
if(length(info)>0){
if(is.na(max(info[,19]))){
results$Prediction[i]<-"unknown"
results$Score[i]<-max(info[,19])
}
if(!is.na(max(info[,19]))){
results$Prediction[i]<-info[which.max(info[,19]),15]
results$Score[i]<-max(info[,19])
}
}
}
}
for(i in seq_along(checkpoint[,1])){
for(j in 2:length(checkpoint[1,])){
if(!is.na(checkpoint[i,j])){
checkpoint[i,j]<-6
}
}
}
if(is.null(input$dbSNP)){
database_calls<-cbind(results[,c(1:5,8:(length(results[1,])))],
c.,c.complement,p.)
}
if(!is.null(input$dbSNP)){
database_calls<-cbind(results,c.,c.complement,p.)
}
write.table(database_calls,
paste(input$output_folder,
"/Results_Databases.txt",sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
write.table(checkpoint,
paste(input$output_folder,"/checkpoint.txt",
sep=""),
row.names=FALSE,quote=FALSE,sep="\t")
checkpoint_state<-6
progress$close()
}
#6: After Extended Set of Characteristics
if(checkpoint_state==6){
if(exists("frequency_calls")==FALSE||
exists("database_calls")==FALSE||
exists("combined_calls")==FALSE){
#1. Reading Input
log_info<-c(log_info,"0. Reading input<br>")
output$log_info<-renderUI({HTML(log_info)})
frequency_calls<-read.table(paste(input$output_folder,
"/Results_Frequency.txt",
sep=""),
stringsAsFactors = FALSE,
header=TRUE,sep="\t")
database_calls<-read.table(paste(input$output_folder,
"/Results_Databases.txt",
sep=""),
stringsAsFactors = FALSE,
header=TRUE,sep="\t")
combined_calls<-read.table(paste(input$output_folder,
"/Results_Raw.txt",
sep=""),
stringsAsFactors = FALSE,
header=TRUE,sep="\t")
}
#7. Final filtration
log_info<-c(log_info,"7. Perform Final Filtration<br>")
output$log_info<-renderUI({HTML(log_info)})
progress <- shiny::Progress$new()
progress$set(message = "7. Perform final filtration",
value = 0)
if(input$stricter_thresholds=="No"){
dp<-input$dp
nr_alt<-input$nr_alt
vaf<-input$vaf
low_bq<-input$low_bq
bq_diff<-input$bq_diff
}
if(input$stricter_thresholds=="Yes"){
dp<-input$dp2
nr_alt<-input$nr_alt2
vaf<-input$vaf2
low_bq<-input$bq2
bq_diff<-input$bq_diff2
}
nrsamples<-input$nr_samples
nrsamples_high<-ceiling(length(checkpointFile[,1])/2)
if(nrsamples_high==1){
nrsamples_high<-2
}
if(input$predict=="SIFT"){
limit_provean<-input$damaging_safe1
limit_provean2<-input$tolerated_safe1
}
if(input$predict=="Provean"){
limit_provean<-input$damaging_safe2
limit_provean2<-input$tolerated_safe2
}
if(input$predict=="PolyPhen2"){
limit_provean<-input$damaging_safe3
limit_provean2<-input$tolerated_safe3
}
if(!is.null(input$primerPositions)){
primer_temp<-input$primerPositions
primer<-read.table(primer_temp$datapath,
header=FALSE,sep="\t",
stringsAsFactors=FALSE)
}
if(!is.null(input$hotspots)){
hotspots_temp<-input$hotspots
hotspots<-read.table(hotspots_temp$datapath,
header=TRUE,sep="\t",
stringsAsFactors=FALSE)
}
results<-cbind(frequency_calls[,c(1:5,14:16,6,13)],
database_calls[,c((length(database_calls[1,])-2):length(database_calls[1,]))],
frequency_calls[,c(11,12)],
Nr_Ref=frequency_calls$Nr_Ref,
Nr_Alt=frequency_calls$Nr_Alt,
DP=frequency_calls$DP,
VAF=frequency_calls$VAF,
frequency_calls[,c(17:(length(frequency_calls[1,])-14))],
Called=rowSums(frequency_calls[,c(17:(length(frequency_calls[1,])-14))],na.rm=TRUE),
database_calls[,c(6:(length(database_calls[1,])-3))],
frequency_calls[,c((length(frequency_calls[1,])-9):(length(frequency_calls[1,])))])
artifact_because<-data.frame(nr_samples=rep(NA,length(frequency_calls[,1])),
nr_samples_similar=rep(NA,length(frequency_calls[,1])),
nr_databases=rep(NA,length(frequency_calls[,1])),
polymorphism_db=rep(NA,length(frequency_calls[,1])),
mutation_db=rep(NA,length(frequency_calls[,1])),
cosmic_nr=rep(NA,length(frequency_calls[,1])),
Poly_freq=rep(NA,length(frequency_calls[,1])))
#filter frequency
if(input$stricter_thresholds=="Yes"){
progress$inc(1/13,
detail="-> Consider Frequency and Base Quality")
include1<-results$DP>=dp
include2<-results$Nr_Alt>=nr_alt
include3<-(results$VAF*100)>=vaf
include4<-results$BQ_ALT>=low_bq
include5<-(results$BQ_REF-results$BQ_ALT)<=bq_diff
temp<-results[rowSums(cbind(include1,include2,include3,include4,include5))>=5|is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
results<-temp
temp<-frequency_calls[rowSums(cbind(include1,include2,include3,include4,include5))>=5|is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
frequency_calls<-temp
temp<-database_calls[rowSums(cbind(include1,include2,include3,include4,include5))>=5|is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
database_calls<-temp
temp<-artifact_because[rowSums(cbind(include1,include2,include3,include4,include5))>=5|is.na(rowSums(cbind(include1,include2,include3,include4,include5))>=5),]
artifact_because<-temp
}
if(input$stricter_thresholds=="No"){
progress$inc(1/13)
}
#nr of samples
progress$inc(1/13,
detail="-> Consider samples with the same call")
progress_small <- shiny::Progress$new()
progress_small$set(message = "", value = 0)
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
artifact_because[i,1]<-length(combined_calls[intersect(intersect(grep(results[i,2],combined_calls[,2]),grep(results[i,3],combined_calls[,3])),intersect(grep(results[i,4],combined_calls[,4]),grep(results[i,5],combined_calls[,5]))),1])
}
progress_small$close()
progress$inc(1/13,
detail="-> Consider samples with a call at the same position")
progress_small <- shiny::Progress$new()
progress_small$set(message = "", value = 0)
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call ",i," out of ",
length(results[,1])))
artifact_because[i,2]<-length(combined_calls[intersect(grep(results[i,2],combined_calls[,2]),grep(results[i,3],combined_calls[,3])),1])
}
progress_small$close()
progress$inc(1/13,
detail="-> Consider background information")
background_info<-rep(0,length(results[,1]))
start<-0
ende<-0
neu<-TRUE
i<-1
while(i<=length(results[,1])){
if(neu==TRUE){
start<-ende<-i
}
i<-i+1
if(i<=length(results[,1])&&
as.character(results[i,2])==as.character(results[i-1,2])&&
results[i,3]==results[i-1,3]&&
results[i,4]==results[i-1,4]&&
results[i,5]==results[i-1,5]){
ende<-i
neu<-FALSE
}
if(i>length(results[,1])||
as.character(results[i,2])!=as.character(results[i-1,2])||
results[i,3]!=results[i-1,3]||
results[i,4]!=results[i-1,4]||
results[i,5]!=results[i-1,5]){
for(j in start:ende){
background_info[j]<-ende-start+1
neu<-TRUE
}
}
}
#databases
progress$inc(1/13,detail="-> Consider nr of databases")
if(length(database_calls[1,])>10){
if(length(grep("dbSNP",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$dbSNP[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],1,na.rm=TRUE)
if(!is.na(results$dbSNP_MAF[i])&&
as.numeric(results$dbSNP_MAF[i])<=0.001){
artifact_because[i,5]<-sum(artifact_because[i,5],1,na.rm=TRUE)
}
if(!is.na(results$dbSNP_MAF[i])&&
as.numeric(results$dbSNP_MAF[i])>0.001){
artifact_because[i,4]<-sum(artifact_because[i,4],1,na.rm=TRUE)
}
}
}
}
if(length(grep("G1000_AF",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$G1000_AF[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],1,na.rm=TRUE)
if(as.numeric(results$G1000_AF[i])<=0.001){
artifact_because[i,5]<-sum(artifact_because[i,5],1,na.rm=TRUE)
}
if(as.numeric(results$G1000_AF[i])>0.001){
artifact_because[i,4]<-sum(artifact_because[i,4],1,na.rm=TRUE)
}
}
}
}
if(length(grep("ExAC_AF",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$ExAC_AF[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],1,na.rm=TRUE)
if(as.numeric(results$ExAC_AF[i])<=0.0005){
artifact_because[i,5]<-sum(artifact_because[i,5],1,na.rm=TRUE)
}
if(as.numeric(results$ExAC_AF[i])>0.0005){
artifact_because[i,4]<-sum(artifact_because[i,4],1,na.rm=TRUE)
}
}
}
}
if(length(grep("GAD_AF",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$GAD_AF[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],1,na.rm=TRUE)
if(as.numeric(results$GAD_AF[i])<=0.001){
artifact_because[i,5]<-sum(artifact_because[i,5],1,na.rm=TRUE)
}
if(as.numeric(results$GAD_AF[i])>0.001){
artifact_because[i,4]<-sum(artifact_because[i,4],1,na.rm=TRUE)
}
}
}
}
if(length(grep("CosmicID",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$CosmicID[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],1,na.rm=TRUE)
artifact_because[i,6]<-sum(as.numeric(strsplit(as.character(database_calls$Cosmic_Counts[i]),split=",")[[1]]))
if(artifact_because[i,6]>20){
artifact_because[i,5]<-sum(artifact_because[i,5],1,na.rm=TRUE)
}
if(artifact_because[i,6]<=20){
artifact_because[i,4]<-sum(artifact_because[i,4],1,na.rm=TRUE)
}
}
}
}
if(length(grep("ClinVar",names(database_calls)))>0){
for(i in seq_along(database_calls[,1])){
if(!is.na(results$ClinVar[i])){
artifact_because[i,3]<-sum(artifact_because[i,3],1,na.rm=TRUE)
if(length(grep("Pathogenic",
results$ClinVar[i],
ignore.case = TRUE))>0){
artifact_because[i,5]<-sum(artifact_because[i,5],1,na.rm=TRUE)
}
if(length(grep("Benign",
results$ClinVar[i],
ignore.case = TRUE))>0){
artifact_because[i,4]<-sum(artifact_because[i,4],1,na.rm=TRUE)
}
}
}
}
}
#tolerated and freq
progress$inc(1/13,detail="-> Consider VAF when tolerated")
for(i in seq_along(results[,1])){
if(!is.na(results$VAF[i])&&((results$VAF[i]>=0.35&&
results$VAF[i]<=0.65)||
(results$VAF[i]>=0.85))){
artifact_because[i,7]<-1
}
if(!is.na(results$VAF[i])&&(results$VAF[i]<0.35||
(results$VAF[i]>0.65&&
results$VAF[i]<0.85))){
artifact_because[i,7]<-0
}
}
#large number of samples and high VAF
progress$inc(1/13,
detail="-> Consider VAF when high nr of samples")
i<-1
while(i<=length(results[,1])){
subset<-results[i:(i+background_info[i]-1),]
if(length(subset[,1])>nrsamples&&
sum(!is.na(subset$VAF))==length(subset[,1])&&
sum(subset$VAF>0.85)>=floor(0.9*length(subset[,1]))){
artifact_because[i:(i+background_info[i]-1),7]<-2
}
i<-i+background_info[i]
}
#test for strand bias (8 von 15)
progress$inc(1/13,detail="-> Consider strand bias")
strandbias<-rep(NA,length(results[,1]))
for(i in seq_along(results[,1])){
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])){
test<-fisher.test(x=matrix(c(results$Nr_Ref_fwd[i],
results$Nr_Alt_fwd[i],
results$Nr_Ref_rev[i],
results$Nr_Alt_rev[i]),
ncol=2))
strandbias[i]<-test$p.value
}
if(!is.null(input$primerPositions)){
chr<-as.character(results[i,2])==as.character(primer[,1])
start<-results[i,3]>primer[,2]
end<-(as.numeric(results[i,3])+nchar(results[i,4])-1)<=primer[,3]
if(sum(rowSums(cbind(chr,start,end))==3)>0){
strandbias[i]<-2
}
}
}
#check for hotspots
progress$inc(1/13,detail="-> Consider hotspot list")
hotspot<-rep(NA,length(results[,1]))
progress_small <- shiny::Progress$new()
progress_small$set(message = "", value = 0)
if(!is.null(input$hotspots)){
for(i in seq_along(hotspots[,1])){
progress_small$inc(1/length(hotspots[,1]),
detail=paste("-> Hotspot",i,
"out of",
length(hotspots[,1])))
found1<-grep(hotspots[i,1],results$Gene)
if(length(found1)>0){
if(length(grep("fs",hotspots[i,2]))==0&&
length(grep("del",hotspots[i,2]))==0&&
length(grep("ins",hotspots[i,2]))==0){
#Just an SNV
found2<-grep(hotspots[i,2],results$p.,
fixed=TRUE)
flag<-NA
if(length(found2)>0){
flag<-rep(FALSE,length(results[,1]))
if(is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Ref[found2[j]])==1&&
nchar(results$Alt[found2[j]])==1
}
}
if(!is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Ref[found2[j]])==1&&
nchar(results$Alt[found2[j]])==1&&
as.numeric(results$VAF[found2[j]])>=as.numeric(hotspots[i,3])
}
}
}
}
if(length(grep("fs",hotspots[i,2]))>0){
#frameshift
searchstring<-substr(hotspots[i,2],2,
(nchar(hotspots[i,2])-2))
found2<-grep(searchstring,results$p.)
flag<-NA
if(length(found2)>0){
flag<-rep(FALSE,length(results[,1]))
if(is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))!=0&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0
}
}
if(!is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))!=0&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0&&as.numeric(results$VAF[found2[j]])>=as.numeric(hotspots[i,3])
}
}
}
}
if(length(grep("del",hotspots[i,2]))>0){
#deletion
searchstring_temp<-substr(hotspots[i,2],2,
(nchar(hotspots[i,2])-3))
searchstring<-strsplit(searchstring_temp,
split="_")[[1]][1]
found2<-grep(searchstring,results$p.)
flag<-NA
if(length(found2)>0){
flag<-rep(FALSE,length(results[,1]))
if(is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Ref[found2[j]])>1&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0
}
}
if(!is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Ref[found2[j]])>1&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0&&as.numeric(results$VAF[found2[j]])>=as.numeric(hotspots[i,3])
}
}
}
}
if(length(grep("ins",hotspots[i,2]))>0){
#deletion
searchstring_temp<-substr(hotspots[i,2],2,
(nchar(hotspots[i,2])-3))
searchstring<-strsplit(searchstring_temp,split="_")[[1]][1]
found2<-grep(searchstring,results$p.)
flag<-NA
if(length(found2)>0){
flag<-rep(FALSE,length(results[,1]))
if(is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Alt[found2[j]])>1&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0
}
}
if(!is.na(hotspots[i,3])){
for(j in seq_along(found2)){
flag[found2[j]]<-nchar(results$Alt[found2[j]])>1&&(abs(nchar(results$Ref[found2[j]])-nchar(results$Alt[found2[j]]))%%3)!=0&&as.numeric(results$VAF[found2[j]])>=as.numeric(hotspots[i,3])
}
}
}
}
if(length(intersect(found1,found2))>0){
for(j in intersect(found1,found2)){
if(flag[j]==TRUE){
hotspot[j]<-1
}
}
}
}
}
}
progress_small$close()
write.table(cbind(hotspot,results),
paste(input$output_folder,"Hotspot_test.txt"),
sep="\t",quote=FALSE,row.names=FALSE)
##final filtration
results<-cbind(results,strandbias,artifact_because[,c(1:2)],
Category=NA)
#artifact score
progress$inc(1/13,detail="-> Perform final filtration")
artifact_score<-rep(0,length(results[,1]))
progress_small <- shiny::Progress$new()
progress_small$set(message = "Calculate Artifact Score",
value = 0)
if(input$artifact_score=="No"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,
"out of",
length(results[,1])))
if(results$nr_samples[i]>nrsamples){
artifact_score[i]<-artifact_score[i]+2
}
if(results$nr_samples[i]>nrsamples_high&&
is.na(hotspot[i])){
artifact_score[i]<-artifact_score[i]+2
}
if((nchar(results$Ref[i])>1||
nchar(results$Alt[i])>1)&&
results$nr_samples_similar[i]>results$nr_samples[i]){
artifact_score[i]<-artifact_score[i]+1
}
if((nchar(results$Ref[i])>1||
nchar(results$Alt[i])>1)&&
!is.na(results$VAF[i])&&results$VAF[i]<0.05){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(artifact_because[i,7])&&
artifact_because[i,7]==2){
artifact_score[i]<-artifact_score[i]+2
}
if(is.null(input$primerPositions)||
(!is.na(results$strandbias[i])&&
results$strandbias[i]!=2)){
if(!is.na(results$strandbias[i])&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(results$Nr_Alt_fwd[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_fwd[i]>=(nr_alt/2)&&
results$Nr_Alt_rev[i]>=(nr_alt/2))&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]-1
}
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
(results$Nr_Alt_fwd[i]<=2&&
results$Nr_Ref_fwd[i]>=(dp-nr_alt)/2)&&
results$strandbias[i]>=0.001){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
(results$Nr_Alt_fwd[i]<=2&&
results$Nr_Ref_fwd[i]<(dp-nr_alt)/2)&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]-1
}
if(!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_rev[i]<=2&&
results$Nr_Ref_rev[i]>=(dp-nr_alt)/2)&&
results$strandbias[i]>=0.001){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_rev[i]<=2&&
results$Nr_Ref_rev[i]<(dp-nr_alt)/2)&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]-1
}
}
if(!is.null(input$primerPositions)&&
!is.na(results$strandbias[i])&&
results$strandbias[i]==2){
artifact_score[i]<-artifact_score[i]-1
}
if(!is.na(results$VAF[i])&&results$VAF[i]<0.02){
artifact_score[i]<-artifact_score[i]+2
}
if(is.na(artifact_because[i,3])&&
!is.na(results$VAF[i])&&
results$VAF[i]<0.10){
artifact_score[i]<-artifact_score[i]+1
}
if(is.na(artifact_because[i,3])&&
results$nr_samples[i]>nrsamples_high){
artifact_score[i]<-artifact_score[i]+1
}
if((!is.na(results$Score[i])&&
results$Score[i]<limit_provean)){
artifact_score[i]<-artifact_score[i]-1
}
if(!is.na(results$Score[i])&&
results$Score[i]>limit_provean2&&
!is.na(artifact_because[i,7])&&
artifact_because[i,7]==0){
artifact_score[i]<-artifact_score[i]+1
}
if(results$Called[i]>=4){
artifact_score[i]<-artifact_score[i]-1
}
if(results$Called[i]>=5){
artifact_score[i]<-artifact_score[i]-1
}
if(results$Called[i]>=6){
artifact_score[i]<-artifact_score[i]-1
}
if(results$Called[i]==1){
artifact_score[i]<-artifact_score[i]+1
}
if(!is.na(results$BQ_ALT[i])&&
results$BQ_ALT[i]<(mean(results$BQ_ALT,na.rm=TRUE)-3*sd(results$BQ_ALT,na.rm=TRUE))){
artifact_score[i]<-artifact_score[i]+4
}
if(!is.na(hotspot[i])){
artifact_score[i]<-artifact_score[i]-3
}
if(!is.na(results$LoFreq[i])&&
!is.na(results$FreeBayes[i])&&
!is.na(results$VarDict[i])&&
results$LoFreq[i]==1&&
results$FreeBayes[i]==1&&results$VarDict[i]==1){
artifact_score[i]<-artifact_score[i]-3
}
if(artifact_score[i]>-1){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
}
if(input$artifact_score=="Yes"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,
"out of",
length(results[,1])))
if(results$nr_samples[i]>nrsamples){
artifact_score[i]<-artifact_score[i]+input$detectedLow
}
if(results$nr_samples[i]>nrsamples_high&&
is.na(hotspot[i])){
artifact_score[i]<-artifact_score[i]+input$detectedHigh
}
if((nchar(results$Ref[i])>1||
nchar(results$Alt[i])>1)&&
results$nr_samples_similar[i]>results$nr_samples[i]){
artifact_score[i]<-artifact_score[i]+input$isIndel
}
if((nchar(results$Ref[i])>1||
nchar(results$Alt[i])>1)&&
!is.na(results$VAF[i])&&results$VAF[i]<0.05){
artifact_score[i]<-artifact_score[i]+input$isIndelVAF
}
if(!is.na(artifact_because[i,7])&&
artifact_because[i,7]==2){
artifact_score[i]<-artifact_score[i]+input$detectedLowVAF
}
if(is.null(input$primerPositions)||
(!is.na(results$strandbias[i])&&
results$strandbias[i]!=2)){
if(!is.na(results$strandbias[i])&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+input$noPrimerP
}
if(!is.na(results$Nr_Alt_fwd[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_fwd[i]>=(nr_alt/2)&&
results$Nr_Alt_rev[i]>=(nr_alt/2))&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+input$primerPAlt
}
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
(results$Nr_Alt_fwd[i]<=2&&
results$Nr_Ref_fwd[i]>=(dp-nr_alt)/2)&&
results$strandbias[i]>=0.001){
artifact_score[i]<-artifact_score[i]+input$noPrimerPFwd
}
if(!is.na(results$Nr_Ref_fwd[i])&&
!is.na(results$Nr_Alt_fwd[i])&&
(results$Nr_Alt_fwd[i]<=2&&
results$Nr_Ref_fwd[i]<(dp-nr_alt)/2)&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+input$primerPFwd
}
if(!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_rev[i]<=2&&
results$Nr_Ref_rev[i]>=(dp-nr_alt)/2)&&
results$strandbias[i]>=0.001){
artifact_score[i]<-artifact_score[i]+input$noPrimerPRev
}
if(!is.na(results$Nr_Ref_rev[i])&&
!is.na(results$Nr_Alt_rev[i])&&
(results$Nr_Alt_rev[i]<=2&&
results$Nr_Ref_rev[i]<(dp-nr_alt)/2)&&
results$strandbias[i]<0.001){
artifact_score[i]<-artifact_score[i]+input$primerPRev
}
}
if(!is.null(input$primerPositions)&&
!is.na(results$strandbias[i])&&
results$strandbias[i]==2){
artifact_score[i]<-artifact_score[i]+input$primerLocation
}
if(!is.na(results$VAF[i])&&results$VAF[i]<0.02){
artifact_score[i]<-artifact_score[i]+input$vafLow
}
if(is.na(artifact_because[i,3])&&
!is.na(results$VAF[i])&&results$VAF[i]<0.10){
artifact_score[i]<-artifact_score[i]+input$databaseVAF
}
if(is.na(artifact_because[i,3])&&
results$nr_samples[i]>nrsamples_high){
artifact_score[i]<-artifact_score[i]+input$databaseHigh
}
if((!is.na(results$Score[i])&&
results$Score[i]<limit_provean)){
artifact_score[i]<-artifact_score[i]+input$predictionSafe
}
if(!is.na(results$Score[i])&&
results$Score[i]>limit_provean2&&
!is.na(artifact_because[i,7])&&
artifact_because[i,7]==0){
artifact_score[i]<-artifact_score[i]+input$predictionVAF
}
if(results$Called[i]>=input$nrcaller4){
artifact_score[i]<-artifact_score[i]+input$reward4
}
if(results$Called[i]>=input$nrcaller5){
artifact_score[i]<-artifact_score[i]+input$reward5
}
if(results$Called[i]>=input$nrcaller6){
artifact_score[i]<-artifact_score[i]+input$reward6
}
if(results$Called[i]==1){
artifact_score[i]<-artifact_score[i]+input$oneCaller
}
if(!is.na(results$BQ_ALT[i])&&
results$BQ_ALT[i]<(mean(results$BQ_ALT,na.rm=TRUE)-3*sd(results$BQ_ALT,na.rm=TRUE))){
artifact_score[i]<-artifact_score[i]+input$BQ_AltMean
}
if(!is.na(hotspot[i])){
artifact_score[i]<-artifact_score[i]+input$knownHotspot
}
temp<-frequency_calls[i,17:(length(frequency_calls[1,])-14)]
temp<-temp[,!is.na(temp)]
if(length(intersect(names(temp),input$overlapTools))==length(input$overlapTools)){
artifact_score[i]<-artifact_score[i]+input$overlapReward
}
if(artifact_score[i]>=input$artifactThreshold){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
}
progress_small$close()
#polymorphism score
progress$inc(1/13,detail="-> Perform final filtration")
poly_score<-rep(0,length(results[,1]))
cosmic_flag<-rep(FALSE,length(results[,1]))
progress_small <- shiny::Progress$new()
progress_small$set(message = "Calculate Polymorphism Score",
value = 0)
if(input$polymorphism_score=="No"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,
"out of",
length(results[,1])))
if(!is.na(results$nr_samples[i])&&
results$nr_samples[i]>nrsamples){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(results$nr_samples[i])&&
results$nr_samples[i]==1){
poly_score[i]<-poly_score[i]-1
}
if(!is.na(artifact_because[i,4])&&
artifact_because[i,4]>=2){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(artifact_because[i,4])&&
artifact_because[i,4]>=4){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(artifact_because[i,5])&&
artifact_because[i,5]>=2){
poly_score[i]<-poly_score[i]-1
}
if(is.na(artifact_because[i,4])){
poly_score[i]<-poly_score[i]-1
}
if(results$Called[i]>=6){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(results$Consequence[i])&&
vcountPattern(pattern="frameshift",
results$Consequence[i])>0&&
vcountPattern(pattern="*",
as.character(results$p.[i]),
fixed = TRUE)==0){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(artifact_because[i,7])&&
artifact_because[i,7]==1){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(results$Prediction[i])&&
(results$Prediction[i]=="Tolerated"||
results$Prediction[i]=="benign"||
results$Prediction[i]=="Neutral")&&
results$Score[i]>=limit_provean2){
poly_score[i]<-poly_score[i]+1
}
if(!is.na(results$Score[i])&&!is.na(results$p.[i])&&
as.character(results$p.[i])!="NA"&&
(results$Score[i]<=limit_provean||
vcountPattern(pattern="*",
as.character(results$p.[i]),
fixed = TRUE)>0)){
poly_score[i]<-poly_score[i]-1
}
if(!is.na(results$Cosmic_Counts[i])&&
results$Cosmic_Counts[i]>100){
cosmic_flag[i]<-TRUE
}
if(is.na(hotspot[i])&&poly_score[i]>=2&&
cosmic_flag[i]==TRUE){
results$Category[i]<-paste(results$Category[i],
"Likely Polymorphism",
sep="")
}
if(is.na(hotspot[i])&&((poly_score[i]>=2&&
cosmic_flag[i]==FALSE)
||poly_score[i]>=3)){
results$Category[i]<-"Polymorphism"
}
}
}
if(input$polymorphism_score=="Yes"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,
"out of",
length(results[,1])))
if(!is.na(results$nr_samples[i])&&
results$nr_samples[i]>nrsamples){
poly_score[i]<-poly_score[i]+input$polyDetected
}
if(!is.na(results$nr_samples[i])&&
results$nr_samples[i]==1){
poly_score[i]<-poly_score[i]+input$polyDetectedOnce
}
if(!is.na(artifact_because[i,4])&&
artifact_because[i,4]>=input$polyDatabasesPolyLow){
poly_score[i]<-poly_score[i]+input$polyDatabasesPolyLowReward
}
if(!is.na(artifact_because[i,4])&&
artifact_because[i,4]>=input$polyDatabasesPolyHigh){
poly_score[i]<-poly_score[i]+input$polyDatabasesPolyHighReward
}
if(!is.na(artifact_because[i,5])&&
artifact_because[i,5]>=input$polyDatabasesMut){
poly_score[i]<-poly_score[i]+input$polyDatabasesMutReward
}
if(is.na(artifact_because[i,4])){
poly_score[i]<-poly_score[i]+input$polyNoDatabase
}
if(results$Called[i]>=input$polyDatabases){
poly_score[i]<-poly_score[i]+input$polyDatabasesReward
}
if(!is.na(results$Consequence[i])&&
vcountPattern(pattern="frameshift",
results$Consequence[i])>0&&
vcountPattern(pattern="*",
as.character(results$p.[i]),
fixed = TRUE)==0){
poly_score[i]<-poly_score[i]+input$polyEffect
}
if(!is.na(artifact_because[i,7])&&
artifact_because[i,7]==1){
poly_score[i]<-poly_score[i]+input$polyVAF
}
if(!is.na(results$Prediction[i])&&
(results$Prediction[i]=="Tolerated"||
results$Prediction[i]=="benign"||
results$Prediction[i]=="Neutral")&&
results$Score[i]>=limit_provean2){
poly_score[i]<-poly_score[i]+input$polyPrediction
}
if(!is.na(results$Score[i])&&
!is.na(results$p.[i])&&
as.character(results$p.[i])!="NA"&&
(results$Score[i]<=limit_provean||
vcountPattern(pattern="*",
as.character(results$p.[i]),
fixed = TRUE)>0)){
poly_score[i]<-poly_score[i]+input$polyPredictionEffect
}
if(!is.na(results$Cosmic_Counts[i])&&
results$Cosmic_Counts[i]>input$polyCosmic){
cosmic_flag[i]<-TRUE
}
if(is.na(hotspot[i])&&
poly_score[i]>=input$polyThresholdCritical&&
cosmic_flag[i]==TRUE){
results$Category[i]<-paste(results$Category[i],
"Likely Polymorphism",
sep="")
}
if(is.na(hotspot[i])&&
((poly_score[i]>=input$polyThresholdCritical&&
cosmic_flag[i]==FALSE)||
poly_score[i]>=input$polyThreshold)){
results$Category[i]<-"Polymorphism"
}
}
}
progress_small$close()
#corrections
progress$inc(1/13,detail="-> Perform final filtration")
progress_small <- shiny::Progress$new()
progress_small$set(message = "Correct Scores", value = 0)
if(input$artifact_score=="No"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,
"out of",
length(results[,1])))
if((poly_score[i]>=2&&cosmic_flag[i]==TRUE&&
is.na(hotspot[i]))||(is.na(hotspot[i])&&
((poly_score[i]>=2&&
cosmic_flag[i]==FALSE)||
poly_score[i]>=3))){
if(!is.na(results$VAF[i])&&
results$VAF[i]<=0.1){
artifact_score[i]<-artifact_score[i]+5
if(artifact_score[i]>-1){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
if(!is.na(results$VAF[i])&&
results$VAF[i]<=0.2){
artifact_score[i]<-artifact_score[i]+2
if(artifact_score[i]>-1){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
if(!is.na(results$Consequence[i])&&
vcountPattern(pattern="frameshift",
results$Consequence[i])>0){
artifact_score[i]<-artifact_score[i]+2
if(artifact_score[i]>-1){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<=-1&&!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
}
}
}
if(input$artifact_score=="Yes"){
for(i in seq_along(results[,1])){
progress_small$inc(1/length(results[,1]),
detail=paste("-> Call",i,
"out of",
length(results[,1])))
if((poly_score[i]>=2&&cosmic_flag[i]==TRUE&&
is.na(hotspot[i]))||(is.na(hotspot[i])&&
((poly_score[i]>=2&&
cosmic_flag[i]==FALSE)||
poly_score[i]>=3))){
if(!is.na(results$VAF[i])&&results$VAF[i]<=0.1){
artifact_score[i]<-artifact_score[i]+input$PolymorphismVAF10
if(artifact_score[i]>=input$artifactThreshold){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
if(!is.na(results$VAF[i])&&results$VAF[i]<=0.2){
artifact_score[i]<-artifact_score[i]+input$PolymorphismVAF20
if(artifact_score[i]>=input$artifactThreshold){
results$Category[i]<-paste("Artifact (",
artifact_score[i],")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
if(!is.na(results$Consequence[i])&&
vcountPattern(pattern="frameshift",
results$Consequence[i])>0){
artifact_score[i]<-artifact_score[i]+input$PolymorphismFrame
if(artifact_score[i]>=input$artifactThreshold){
results$Category[i]<-paste("Artifact (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
is.na(hotspot[i])){
results$Category[i]<-paste("Probably True (",
artifact_score[i],
")",sep="")
}
if(artifact_score[i]<input$artifactThreshold&&
!is.na(hotspot[i])){
results$Category[i]<-paste("Hotspot (",
artifact_score[i],
")",sep="")
}
}
}
}
}
progress_small$close()
#identical calls as polymorphism
progress$inc(1/13,detail="-> Re-consider polymorphisms")
i<-1
while(i<=length(results[,1])){
subset<-results[i:(i+background_info[i]-1),]
if(sum(subset$Category=="Polymorphism",na.rm=TRUE)>=1){
for(j in i:(i+background_info[i]-1)){
if(!is.na(results$VAF[j])&&results$VAF[j]>0.2){
results$Category[j]<-"Polymorphism"
}
}
}
i<-i+background_info[i]
}
results.artifacts<-results[vcountPattern(results$Category,pattern="Artifact")>0 | is.na(results$VAF) | (results$DP-results$Nr_Ref)<nr_alt,]
results.polymorphisms<-results[vcountPattern(results$Category,pattern="Polymorphism")>0 & !is.na(results$VAF) & (results$DP-results$Nr_Ref)>=nr_alt,]
results.mutations<-results[(vcountPattern(results$Category,pattern="True")>0 | vcountPattern(results$Category,pattern="Hotspot")>0) & !is.na(results$VAF) & (results$DP-results$Nr_Ref)>=nr_alt,]
if(exists("overview4")==TRUE){
overview4<-cbind(overview4,Mutations=NA,
Polymorphisms=NA,Artifacts=NA)
}
if(exists("overview4")==FALSE){
overview4<-cbind(checkpointFile[,1],RawCalls=NA,
VAFandBQFiltered=NA,Mutations=NA,
Polymorphisms=NA,Artifacts=NA)
}
for(i in seq_along(overview4[,1])){
overview4[i,4]<-length(results.mutations[results.mutations[,1]==overview4[i,1],1])
overview4[i,5]<-length(results.polymorphisms[results.polymorphisms[,1]==overview4[i,1],1])
overview4[i,6]<-length(results.artifacts[results.artifacts[,1]==overview4[i,1],1])
for(j in 2:length(checkpoint[1,])){
if(!is.na(checkpoint[i,j])){
checkpoint[i,j]<-7
}
}
}
write.table(results,
paste(input$output_folder,"/Results_Final.txt",
sep=""),row.names=FALSE,quote=FALSE,
sep="\t")
write.table(checkpoint,
paste(input$output_folder,"/checkpoint.txt",
sep=""),row.names=FALSE,quote=FALSE,
sep="\t")
output$table4 <- renderDataTable(datatable(overview4))
output$table_mutations <- renderDataTable(datatable(results.mutations))
output$table_polymorphisms <- renderDataTable(datatable(results.polymorphisms))
output$table_artifacts <- renderDataTable(datatable(results.artifacts))
results.workbook <- createWorkbook()
addWorksheet(wb=results.workbook,sheetName="Mutations")
addWorksheet(wb=results.workbook,sheetName="Polymorphisms")
addWorksheet(wb=results.workbook,sheetName="Artifacts")
writeData(wb=results.workbook,x=results.mutations,
sheet="Mutations")
writeData(wb=results.workbook,x=results.polymorphisms,
sheet="Polymorphisms")
writeData(wb=results.workbook,x=results.artifacts,
sheet="Artifacts")
saveWorkbook(results.workbook,
paste(input$output_folder,
"/Results_Final.xlsx",sep=""),
overwrite = TRUE)
checkpoint_state<-7
progress$close()
}
#7: After Final Filtration
if(checkpoint_state==7){
#1. Reading Input
log_info<-c(log_info,"You are done <br>")
output$log_info<-renderUI({HTML(log_info)})
if(exists("results.artifacts")==FALSE){
results.artifacts<-read.xlsx(paste(input$output_folder,
"/Results_Final.xlsx",
sep=""),
sheet="Artifacts")
results.polymorphisms<-read.xlsx(paste(input$output_folder,
"/Results_Final.xlsx",
sep=""),
sheet="Polymorphisms")
results.mutations<-read.xlsx(paste(input$output_folder,"
/Results_Final.xlsx",
sep=""),
sheet="Mutations")
overview4<-cbind(checkpointFile[,1],RawCalls=NA,
VAFandBQFiltered=NA,Mutations=NA,
Polymorphisms=NA,Artifacts=NA)
for(i in seq_along(overview4[,1])){
overview4[i,4]<-length(results.mutations[results.mutations[,1]==overview4[i,1],1])
overview4[i,5]<-length(results.polymorphisms[results.polymorphisms[,1]==overview4[i,1],1])
overview4[i,6]<-length(results.artifacts[results.artifacts[,1]==overview4[i,1],1])
for(j in 2:length(checkpoint[1,])){
if(!is.na(checkpoint[i,j])){
checkpoint[i,j]<-7
}
}
}
output$table4 <- renderDataTable(datatable(overview4))
output$table_mutations <- renderDataTable(datatable(results.mutations))
output$table_polymorphisms <- renderDataTable(datatable(results.polymorphisms))
output$table_artifacts <- renderDataTable(datatable(results.artifacts))
}
}
})
}
)
}
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