Nothing
inst/shiny/server.R
In MesKit: A tool kit for dissecting cancer evolution from multi-region derived tumor biopsies via somatic alterations
# Define server logic required to plot various variables against mpg
shinyServer(function(input, output, session){
observeEvent(input$help, {
updateTabItems(session, "sidername", "home")
})
observeEvent(input$contact, {
updateTabItems(session, "sidername", "home")
})
inputData <- eventReactive(input$submit1, {
if(input$submit1){
if(is.null(input$mafFile$datapath)){
mafFile <- system.file("extdata", "CRC_HZ.maf", package = "MesKit")
clinFile <- system.file("extdata/", "CRC_HZ.clin.txt", package = "MesKit")
if(input$useccffile){
ccfFile <- system.file("extdata", "CRC_HZ.ccf.tsv", package = "MesKit")
}else{
ccfFile <- NULL
}
maf <- readMaf(mafFile = mafFile, clinicalFile = clinFile, ccfFile = ccfFile)
} else {
if(!is.null(input$mafFile)){
if(is.null(input$ccfFile)){
ccfFile <- NULL
}else{
ccfFile <- input$ccfFile$datapath
}
maf <- readMaf(mafFile = input$mafFile$datapath,
clinicalFile = input$clinFile$datapath,
ccfFile = ccfFile,
refBuild = input$ref,
use.indel.ccf = input$ccfFile_use_indel_ccf)
}
else{
maf <- readMaf(mafFile = input$mafFile$datapath,
clinicalFile = input$clinFile$datapath,
refBuild = input$ref)
}
}
return(maf)
}
})
varsMaf <- reactiveValues()
observeEvent(input$submit1,{
withProgress(min = 0, max = 1, value = 0, {
## Rshiny: progress bar
setProgress(message = 'Processing: generating Maf/MafList Class')
varsMaf[['maf']] <- inputData()
incProgress(amount=1)
setProgress(message = "Maf/MafList Generation Done!")
Sys.sleep(1)
})
})
buttonValue <- reactiveValues(maf = 0, ccf = 0, clin = 0, seg = 0)
observeEvent(input$iecontrol01,{
buttonValue$ccf <- 0
buttonValue$clin <- 0
buttonValue$maf <- buttonValue$maf + 1
if(buttonValue$maf == 2){
buttonValue$maf <- 0
}
})
observeEvent(input$iecontrol02,{
buttonValue$maf <- 0
buttonValue$clin <- 0
buttonValue$ccf <- buttonValue$ccf + 1
if(buttonValue$ccf == 2){
buttonValue$ccf <- 0
}
})
observeEvent(input$iecontrol_clin,{
buttonValue$maf <- 0
buttonValue$ccf <- 0
buttonValue$clin <- buttonValue$clin + 1
if(buttonValue$clin == 2){
buttonValue$clin <- 0
}
})
## output Introduction of maf datatable
output$ie1 <- renderUI({
if(buttonValue$maf == 1){
tagList(
div(
h3(strong("The MAF files")),
p("MAF files contain many fields of information about chromosome and gene mutations and
their annotations. The following fields are highly recommended to be contained in
the MAF files.",
style = "font-size:16px; font-weight:500;line-height:30px;"),
p(strong("Mandatory fields"),": Hugo_Symbol, Chromosome, Start_Position, End_Position,
Variant_Classification, Variant_Type, Reference_Allele,
Tumor_Seq_Allele2, Ref_allele_depth, Alt_allele_depth,
VAF, Tumor_Sample_Barcode, Patient_ID, Tumor_ID",
style = "font-size:16px; font-weight:500;line-height:30px;"),
h3(strong("Example MAF file"))
),
DT::dataTableOutput("ied1",width = "100%"),
br()
)
}
})
output$ied1 <- DT::renderDataTable({
if(buttonValue$maf == 1){
mafFile <- system.file("extdata/", "CRC_HZ.maf", package = "MesKit")
maf_data <- data.table::fread(
file = mafFile,
quote = "",
header = TRUE,
data.table = TRUE,
fill = TRUE,
sep = '\t',
skip = "Hugo_Symbol",
stringsAsFactors = FALSE
)
d <- datatable(maf_data,
options = list(searching = TRUE,
pageLength = 5,
lengthMenu = c(5, 10, 15, 18),
scrollX = TRUE, fixedColumns = TRUE,
columnDefs=list(list(width="10em",targets="_all"))),
rownames = FALSE, width=5)
return(d)
}
})
## output Introduction of CCF
output$ie2 <- renderUI({
if(buttonValue$ccf == 1){
tagList(
h3(strong("The CCF file")),
p("CCF files contain cancer cell fraction of each mutation.",
style = "font-size:16px; font-weight:500;line-height:30px;"),
p(strong("Mandatory fields"),": Patient_ID, Tumor_Sample_Barcode, Chromosome, Start_Position, CCF, CCF_std/CCF_CI_High (required when identify clonal/subclonal mutations)",
style = "font-size:16px; font-weight:500;line-height:30px;"),
h3(strong("Example CCF file:")),
DT::dataTableOutput("ied2"),
br()
)
}
})
output$ied2 <- DT::renderDataTable({
if(buttonValue$ccf == 1){
ccfFile <- system.file("extdata/", "CRC_HZ.ccf.tsv", package = "MesKit")
ccf_data <- suppressWarnings(data.table::fread(
ccfFile,
quote = "",
header = TRUE,
fill = TRUE,
sep = '\t',
stringsAsFactors = FALSE
))
d <- datatable(ccf_data, options = list(searching = TRUE, pageLength = 5, lengthMenu = c(5, 10, 15, 18), scrollX = TRUE, fixedColumns = TRUE, columnDefs=list(list(width="10em",targets="_all"))),rownames = FALSE, width=5)
return(d)
}
})
## output Introduction of clinical file
output$ie_clin <- renderUI({
if(buttonValue$clin == 1){
tagList(
h3(strong("The clinical file")),
p("Clinical file store clinical information.",
style = "font-size:16px; font-weight:500;line-height:30px;"),
p(strong("Mandatory fields"),": Tumor_Sample_Barcode, Tumor_ID, Patient_ID, Tumor_Sample_Label(optional)",
style = "font-size:16px; font-weight:500;line-height:30px;"),
h3(strong("Example clinical file:")),
DT::dataTableOutput("ied_clin"),
br()
)
}
})
output$ied_clin <- DT::renderDataTable({
if(buttonValue$clin == 1){
clin.File <- system.file("extdata/", "CRC_HZ.clin.txt", package = "MesKit")
clin_data <- data.table::fread(
file = clin.File,
quote = "",
header = TRUE,
data.table = TRUE,
fill = TRUE,
sep = '\t',
stringsAsFactors = FALSE
)
d <- datatable(clin_data, options = list(searching = TRUE, pageLength = 5, lengthMenu = c(5, 10, 15, 18), scrollX = TRUE, fixedColumns = TRUE, columnDefs=list(list(width="10em",targets="_all"))),rownames = FALSE, width=5)
return(d)
}
})
output$datapreview <- renderUI({
if(input$submit1){
DT::dataTableOutput('maftable', width = '100%')
}
})
output$maftable <- DT::renderDataTable({
if(input$submit1){
maf <- inputData()
if(class(maf) == "Maf"){
t <- datatable(inputData()@data, options = list(searching = TRUE, pageLength = 10, lengthMenu = c(5, 10, 15, 18), scrollX = TRUE, fixedColumns = TRUE, columnDefs=list(list(width="10em",targets="_all"))),rownames = FALSE, width=5)
}else{
t <- datatable(inputData()[[1]]@data, options = list(searching = TRUE, pageLength = 10, lengthMenu = c(5, 10, 15, 18), scrollX = TRUE, fixedColumns = TRUE, columnDefs=list(list(width="10em",targets="_all"))),rownames = FALSE, width=5)
}
return(t)
}
})
output$mathscore_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("mathscore_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "mathscore_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
ms <- eventReactive(input$submit_mathscore, {
maf <- isolate(varsMaf$maf)
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
patientid <- input$mathscore_patientid
progress <- Progress$new(session, min=1, max=15)
on.exit(progress$close())
progress$set(message = 'Processing: calculating MATH score...')
mathScore(maf,
patient.id = patientid,
min.vaf = as.numeric(input$mathscore_minvaf),
withinTumor = input$mathscore_withintumor,
use.adjVAF = input$mathscore_useadjvaf,
use.tumorSampleLabel = input$mathscore_usetumorsamplelabel)
})
getpatient.mathscore <- eventReactive(input$mathscore.patientlist, {
return(input$mathscore.patientlist)
})
output$mathscore.patientlist <- renderUI({
if(!is.null(ms())){
if(length(ms()) > 0){
names <- names(ms())
selectInput("mathscore.patientlist",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
}
}
})
output$mathScore <- DT::renderDataTable({
return(ms()[[getpatient.mathscore()]])
})
# ms_value <- ms()
output$msdb <- renderUI({
if(!is.null(ms())){
fluidRow(
column(
width = 9,
downloadBttn('DownloadMathScore', 'Download')
),
column(
width = 3
)
)
}
})
output$DownloadMathScore <- downloadHandler(
filename = "mathscore.csv",
content = function(file){
data <- ms()
write.csv(data,file,row.names = FALSE)
},
contentType = 'text/csv'
)
output$vafcluster_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("vafcluster_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "vafcluster_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
vafcluster <- eventReactive(input$submit3, {
maf <- isolate(varsMaf$maf)
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
patientid <- input$vafcluster_patientid
withProgress(min = 0, max = 1, value = 0,{
setProgress(message = 'Processing: perform mutation clustering')
vc <- mutCluster(maf,
patient.id = patientid,
withinTumor = input$vafcluster_withintumor,
segFile = input$vafcluster_segfile,
# min.vaf = as.numeric(input$vafcluster_minvaf) ,
# max.vaf = as.numeric(input$vafcluster_maxvaf),
use.adjVAF = input$vafcluster_useadjvaf,
use.ccf = input$vafcluster_useccf,
use.tumorSampleLabel = input$vafcluster_usetumorsamplelabel)
incProgress(amount = 1)
setProgress(message = 'vafCluster done!')
})
return(vc)
})
getpatient.vafcluster <- eventReactive(input$vafcluster.patientlist, {
return(input$vafcluster.patientlist)
})
output$vafcluster.patientlist <- renderUI({
if(!is.null(vafcluster())){
if(!"cluster.plot" %in% names(vafcluster())){
names <- names(vafcluster())
selectInput("vafcluster.patientlist",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
}
}
})
output$vafcluster.samplelist <- renderUI({
if(!is.null(vafcluster())){
if("cluster.plot" %in% names(vafcluster())){
sample.list <- vafcluster()$cluster.plot
names <- names(sample.list)
}else{
sample.list <- vafcluster()[[getpatient.vafcluster()]]$cluster.plot
names <- names(sample.list)
print(names)
}
if(input$vafcluster_withintumor){
tagList(
selectInput("vafcluster.sl",
div(style = "font-size:1.5em; font-weight:600; ", 'Tumor ID'),
choices = names, width = 600)
)
}else{
tagList(
selectInput("vafcluster.sl",
div(style = "font-size:1.5em; font-weight:600; ", 'Tumor Sample Barcode'),
choices = names, width = 600)
)
}
}
})
getsample.vafcluster <- eventReactive(input$vafcluster.sl,{
return(input$vafcluster.sl)
})
vafcluster_width <- reactive({
return(input$vafcluster_width)
})
vafcluster_height <- reactive({
return(input$vafcluster_height)
})
output$vaf <- renderPlot({
if(!is.null(vafcluster())){
if("cluster.plot" %in% names(vafcluster())){
return(vafcluster()$cluster.plot[[getsample.vafcluster()]])
}else{
return(vafcluster()[[getpatient.vafcluster()]]$cluster.plot[[getsample.vafcluster()]])
}
}
},width = vafcluster_width,
height = vafcluster_height,
res = 100)
output$vcdb <- renderUI({
if(!is.null(vafcluster())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'DownloadVafPlotCheck',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('DownloadVafPlot', 'Download')
)
)
}
})
output$DownloadVafPlot <- downloadHandler(
filename = function() {
paste("vafcluster.",input$DownloadVafPlotCheck, sep='')
},
content = function(file) {
if (input$DownloadVafPlotCheck == "png"){
png(file,width = input$vafcluster_width , height = input$vafcluster_height,res = 100)
}
else if (input$DownloadVafPlotCheck == "pdf"){
pdf(file,width = input$vafcluster_width/100 , height = input$vafcluster_height/100)
}
if("cluster.plot" %in% names(vafcluster())){
print(vafcluster()$cluster.plot[[getsample.vafcluster()]])
}else{
print(vafcluster()[[getpatient.vafcluster()]]$cluster.plot[[getsample.vafcluster()]])
}
dev.off()
},
contentType = paste('image/',input$DownloadVafPlotCheck,sep="")
)
output$vafcluster_table <- DT::renderDataTable({
if(!is.null(vafcluster())){
if("cluster.data" %in% names(vafcluster())){
t <- vafcluster()$cluster.data
}else{
t <- vafcluster()[[getpatient.vafcluster()]]$cluster.data
}
dt <- datatable(t, options = list(searching = TRUE, pageLength = 5, lengthMenu = c(5, 10, 15, 18), scrollX = TRUE, fixedColumns = TRUE, columnDefs=list(list(width="10em",targets="_all"))),rownames = FALSE, width=5)
return(dt)
}
})
output$vafcluster_table_ui <- renderUI({
if(!is.null(vafcluster())){
tagList(
div(style = "font-size:1.5em; font-weight:600; ", 'Cluster result'),
br(),
DT::dataTableOutput('vafcluster_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_vafcluster_table', 'Download')
)
),
br()
)
}
})
output$Download_vafcluster_table <- downloadHandler(
filename = "vafcluster.csv",
content = function(file){
if("cluster.data" %in% names(vafcluster())){
t <- vafcluster()$cluster.data
}else{
t <- vafcluster()[[getpatient.vafcluster()]]$cluster.data
}
write.csv(t,file,row.names = FALSE)
},
contentType = 'text/csv'
)
output$ccfauc_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("ccfauc_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "ccfauc_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
ccfauc <- eventReactive(input$submit_ccfauc,{
maf <- varsMaf$maf
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
if(is(maf, "MafList")){
maf_column <- colnames(getMafData(maf[[1]]) )
}else{
maf_column <- colnames(getMafData(maf) )
}
validate(
need("CCF" %in% maf_column, "Please upload ccf data in 'Input Data'!")
)
patientid <- input$ccfauc_patientid
withProgress(min = 0, max = 1, value = 0, {
setProgress(message = 'Processing: calculating AUC...')
validate(
need(!(is.null(maf)), "")
)
cc <- ccfAUC(maf,
patient.id = patientid,
min.ccf = as.numeric(input$ccfauc_minccf) ,
withinTumor = input$ccfauc_withintumor,
# use.adjVAF = input$ccfauc_useadjvaf,
use.tumorSampleLabel = input$ccfauc_usetumorsamplelabel)
incProgress(amount = 1)
setProgress(message = 'ccfAUC done!')
})
return(cc)
})
output$ccfauc.patientlist <- renderUI({
if(!is.null(ccfauc())){
if(!"CCF.density.plot" %in% names(ccfauc())){
cc <- ccfauc()
names <- names(cc)
tagList(
selectInput("auc.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
)
}
}
})
getpatient.ccfauc <- eventReactive(input$auc.pl,{
return(input$auc.pl)
})
ccfauc_width <- reactive({
return(input$ccfauc_width)
})
ccfauc_height <- reactive({
return(input$ccfauc_height)
})
output$ccfauc_plot <- renderPlot({
if(!is.null(ccfauc())){
if("CCF.density.plot" %in% names(ccfauc())){
return(ccfauc()$CCF.density.plot)
}else{
return(ccfauc()[[getpatient.ccfauc()]]$CCF.density.plot)
}
}
},
width = ccfauc_width,
height = ccfauc_height,
res = 100)
output$ccfauc_db_ui <- renderUI({
if(!is.null(ccfauc())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_ccfauc_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_ccfauc_plot', 'Download')
)
)
}
})
output$Download_ccfauc_plot <- downloadHandler(
filename = function() {
paste("ccfauc.",input$Download_ccfauc_plot_check, sep='')
},
content = function(file) {
if (input$Download_ccfauc_plot_check == "png"){
png(file,width = input$ccfauc_width , height = input$ccfauc_height,res = 100)
}
else if (input$Download_ccfauc_plot_check == "pdf"){
pdf(file,width = input$ccfauc_width/100 , height = input$ccfauc_height/100)
}
if("CCF.density.plot" %in% names(ccfauc())){
print(ccfauc()$CCF.density.plot)
}else{
print(ccfauc()[[getpatient.ccfauc()]]$CCF.density.plot)
}
dev.off()
},
contentType = paste('image/',input$Download_ccfauc_plot_check,sep="")
)
output$ccfauc_table <- DT::renderDataTable({
if(!is.null(ccfauc())){
if("CCF.density.plot" %in% names(ccfauc())){
t <- ccfauc()$AUC.value
}else{
t <- ccfauc()[[getpatient.ccfauc()]]$AUC.value
}
dt <- datatable(t,
options = list(searching = TRUE,
pageLength = 10,
scrollX = TRUE,
dom = "t",
fixedHeader = TRUE),
rownames = FALSE)
return(dt)
}
})
output$ccfauc_table_ui <- renderUI({
if(!is.null(ccfauc())){
tagList(
div(style = "font-size:1.5em; font-weight:600; ", 'AUC value'),
br(),
DT::dataTableOutput('ccfauc_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_ccfauc_table', 'Download')
)
),
br()
)
}
})
output$Download_ccfauc_table <- downloadHandler(
filename = "ccfauc.csv",
content = function(file){
if("CCF.density.plot" %in% names(ccfauc())){
t <- ccfauc()$AUC.value
}else{
t <- ccfauc()[[getpatient.ccfauc()]]$AUC.value
}
write.csv(t,file,row.names = FALSE)
},
contentType = 'text/csv'
)
## calfst sever
output$calfst_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("calfst_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "calfst_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
calfst <- eventReactive(input$submit_calfst,{
maf <- varsMaf$maf
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
withProgress(min = 0, max = 1, value = 0, {
setProgress(message = 'Processing: calculating Fst..')
# if(input$calfst_title == ""){
# title <- NULL
# }else{
# title <- input$calfst_title
# }
fst <- calFst(maf,
patient.id = input$calfst_patientid,
min.vaf = as.numeric(input$calfst_minvaf) ,
min.total.depth = as.numeric(input$calfst_mintotaldepth),
withinTumor =input$calfst_withinTumor,
use.adjVAF = input$calfst_useadjvaf,
# title = title,
use.circle = input$calfst_usecircle,
number.cex = as.numeric(input$calfst_numbercex),
number.col = input$calfst_numbercol,
use.tumorSampleLabel = input$calfst_usetumorsamplelabel)
incProgress(amount = 1)
setProgress(message = 'calFst done!')
})
return(fst)
})
output$calfst.patientlist <- renderUI({
if(!is.null(calfst())){
if(!"Fst.plot" %in% names(calfst())){
names <- names(calfst())
tagList(
selectInput("calfst.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
)
}
}
})
getpatient.calfst <- eventReactive(input$calfst.pl,{
return(input$calfst.pl)
})
calfst_width <- reactive({
return(input$calfst_width)
})
calfst_height <- reactive({
return(input$calfst_height)
})
output$calfst_plot <- renderPlot({
if(!is.null(calfst())){
if(!"Fst.plot" %in% names(calfst())){
return(calfst()[[getpatient.calfst()]]$Fst.plot)
}else{
return(calfst()$Fst.plot)
}
}
},
width = calfst_width,
height = calfst_height,
res = 100)
output$calfst_db_ui <- renderUI({
if(!is.null(calfst())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_calfst_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_calfst_plot', 'Download')
)
)
}
})
output$Download_calfst_plot <- downloadHandler(
filename = function() {
paste("calfst.",input$Download_calfst_plot_check, sep='')
},
content = function(file) {
if (input$Download_calfst_plot_check == "png"){
png(file,width = input$calfst_width , height = input$calfst_height,res = 100)
}
else if (input$Download_calfst_plot_check == "pdf"){
pdf(file,width = input$calfst_width/100 , height = input$calfst_height/100)
}
if(!"Fst.plot" %in% names(calfst())){
print(calfst()[[getpatient.calfst()]]$Fst.plot)
}else{
print(calfst()$Fst.plot)
}
dev.off()
},
contentType = paste('image/',input$Download_calfst_plot_check,sep="")
)
output$calfst_pair_table <- DT::renderDataTable({
if(!is.null(calfst())){
if(!"Fst.plot" %in% names(calfst())){
m <- calfst()[[getpatient.calfst()]]$Fst.pair
}else{
m <- calfst()$Fst.pair
}
rownames(m) <- colnames(m)
m <- as.data.frame(m)
colnames(m) <- rownames(m)
dt <- datatable(m,options = list(searching = TRUE,
pageLength = 10,
scrollX = TRUE,
dom = "t",
fixedHeader = TRUE),
rownames = TRUE)
return(dt)
}
})
output$calfst_pair_table_ui <- renderUI({
if(!is.null(calfst())){
tagList(
div(style = "font-size:1.5em; font-weight:600; ", 'Fst pair'),
br(),
DT::dataTableOutput('calfst_pair_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_calfst_pair_table', 'Download')
)
)
)
}
})
output$Download_calfst_pair_table <- downloadHandler(
filename = "calfst.csv",
content = function(file){
if(!"Fst.plot" %in% names(calfst())){
m <- calfst()[[getpatient.calfst()]]$Fst.pair
}else{
m <- calfst()$Fst.pair
}
rownames(m) <- colnames(m)
m <- as.data.frame(m)
colnames(m) <- rownames(m)
write.csv(m,file,row.names = TRUE)
},
contentType = 'text/csv'
)
## neidist sever
output$calneidist_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("calneidist_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "calneidist_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
calneidist <- eventReactive(input$submit_calneidist,{
maf <- varsMaf$maf
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
if(is(maf, "MafList")){
maf_column <- colnames(getMafData(maf[[1]]) )
}else{
maf_column <- colnames(getMafData(maf) )
}
validate(
need("CCF" %in% maf_column, "Please upload ccf data in 'Input Data'!")
)
withProgress(min = 0, max = 1, value = 0, {
setProgress(message = "Processing: calculating Nei's distance")
# if(input$calneidist_title==""){
# title <- NULL
# }else{
# title <- input$calneidist_title
# }
cc <- calNeiDist(maf,
patient.id = input$calneidist_patientid,
min.ccf = as.numeric(input$calneidist_minccf) ,
withinTumor = input$calneidist_withintumor,
use.adjVAF = input$calneidist_useadjvaf,
use.circle = input$calneidist_usecircle,
number.cex = as.numeric(input$calneidist_numbercex),
number.col = input$calneidist_numbercol,
use.tumorSampleLabel = input$calneidist_usetumorsamplelabel)
incProgress(amount = 1)
setProgress(message = 'calNeiDist done!')
})
return(cc)
})
output$calneidist.patientlist <- renderUI({
if(!is.null(calneidist())){
if(!"Nei.plot" %in% names(calneidist())){
names <- names(calneidist())
tagList(
selectInput("calneidist.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
)
}
}
})
getpatient.calneidist <- eventReactive(input$calneidist.pl,{
return(input$calneidist.pl)
})
calneidist_width <- reactive({
return(input$calneidist_width)
})
calneidist_height <- reactive({
return(input$calneidist_height)
})
output$calneidist_plot <- renderPlot({
if(!is.null(calneidist())){
if(!"Nei.plot" %in% names(calneidist())){
return(calneidist()[[getpatient.calneidist()]]$Nei.plot)
}else{
return(calneidist()$Nei.plot)
}
}
},
width = calneidist_width,
height = calneidist_height,
res = 100)
output$calneidist_db_ui <- renderUI({
if(!is.null(calneidist())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_calneidist_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_calneidist_plot', 'Download')
)
)
}
})
output$Download_calneidist_plot <- downloadHandler(
filename = function() {
paste("calneidist.",input$Download_calneidist_plot_check, sep='')
},
content = function(file) {
if (input$Download_calneidist_plot_check == "png"){
png(file,width = input$calneidist_width , height = input$calneidist_height,res = 100)
}
else if (input$Download_calneidist_plot_check == "pdf"){
pdf(file,width = input$calneidist_width/100 , height = input$calneidist_height/100)
}
if(!"Nei.plot" %in% names(calneidist())){
print(calneidist()[[getpatient.calneidist()]]$Nei.plot)
}else{
print(calneidist()$Nei.plot)
}
dev.off()
},
contentType = paste('image/',input$Download_calneidist_plot_check,sep="")
)
output$calneidist_pair_table <- DT::renderDataTable({
if(!is.null(calneidist())){
if(!"Nei.plot" %in% names(calneidist())){
m <- calneidist()[[getpatient.calneidist()]]$Nei.dist
}else{
m <- calneidist()$Nei.dist
}
rownames(m) <- colnames(m)
m <- as.data.frame(m)
colnames(m) <- rownames(m)
dt <- datatable(m,options = list(searching = TRUE,
pageLength = 10,
scrollX = TRUE,
dom = "t",
fixedHeader = TRUE),
rownames = TRUE)
return(dt)
}
})
output$calneidist_pair_table_ui <- renderUI({
if(!is.null(calneidist())){
tagList(
div(style = "font-size:1.5em; font-weight:600; ", "Nei's distance"),
br(),
DT::dataTableOutput('calneidist_pair_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_calneidist_pair_table', 'Download')
)
)
)
}
})
output$Download_calneidist_pair_table <- downloadHandler(
filename = "calneidist.csv",
content = function(file){
if(!"Nei.plot" %in% names(calneidist())){
m <- calneidist()[[getpatient.calneidist()]]$Nei.dist
}else{
m <- calneidist()$Nei.dist
}
rownames(m) <- colnames(m)
m <- as.data.frame(m)
colnames(m) <- rownames(m)
write.csv(m,file,row.names = TRUE)
},
contentType = 'text/csv'
)
## mutheatmap
output$mutheatmap_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("mutheatmap_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "mutheatmap_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
output$mutheatmap_parameters_ui <- renderUI({
if(!is.null(input$mutheatmap_genelist$datapath)){
tagList(
checkboxInput('mutheatmap_plotgenelist',
value = FALSE,
label = div(style = "font-size:1.5em; font-weight:600; padding-left:12px", 'Plot gene list'),
width = 500),
bsTooltip(id = "mutheatmap_plotgenelist",
title = "If TRUE, plot heatmap with genes on geneList when geneList is not NULL.Default FALSE.",
placement = "top",
trigger = "hover"),
# checkboxInput('mutheatmap_showgene',
# value = FALSE,
# label = div(style = "font-size:1.5em; font-weight:600; padding-left:12px", 'Show gene'),
# width = 500),
# bsTooltip(id = "mutheatmap_showgene",
# title = "Show the name of genes next to the heatmap.Default FALSE.",
# placement = "top",
# trigger = "hover"),
checkboxInput('mutheatmap_showgenelist',
value = TRUE,
label = div(style = "font-size:1.5em; font-weight:600; padding-left:12px", 'Show gene list'),
width = 500),
bsTooltip(id = "mutheatmap_showgenelist",
title = "Show the names of gene on the geneList.Default TRUE.",
placement = "top",
trigger = "hover"),
tags$table(
tags$tr(id = "inline",
width = "100%",
tags$td(width = "50%", div(style = "font-size:1.5em; font-weight:600; ", "Gene text size: ")),
tags$td(width = "50%", textInput(inputId = "mutheatmap_genetextsize", value = 9, label = NULL)))
),
bsTooltip(id = "mutheatmap_genetextsize",
title = "Size of gene name.Default 9.",
placement = "top",
trigger = "hover"),
br()
)
}
})
mutheatmap <- eventReactive(input$submit_mutheatmap,{
maf <- varsMaf$maf
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
if(!is.null(input$mutheatmap_genelist$datapath)){
genelist <- as.character(read.table(input$mutheatmap_genelist$datapath)$V1)
}else{
genelist <- NULL
}
withProgress(min = 0, max = 1, value = 0, {
setProgress(message = 'Processing: ploting heatmap of somatic mutations.')
if(is.null(input$mutheatmap_plotgenelist)){
plot.geneList <- FALSE
# show.gene <- FALSE
show.geneList <- FALSE
gene.text.size <- 9
}else{
plot.geneList <- input$mutheatmap_plotgenelist
# show.gene <- input$mutheatmap_showgene
show.geneList <- input$mutheatmap_showgenelist
gene.text.size <- as.numeric(input$mutheatmap_genetextsize)
}
hm <- mutHeatmap(maf,
patient.id = input$mutheatmap_patientid,
geneList = genelist,
min.vaf = as.numeric(input$mutheatmap_minvaf),
min.ccf = as.numeric(input$mutheatmap_minccf),
use.ccf = input$mutheatmap_useccf,
plot.geneList = plot.geneList,
# show.gene = show.gene,
show.geneList = show.geneList,
mut.threshold = as.numeric(input$mutheatmap_mutthreshold),
sample.text.size = as.numeric(input$mutheatmap_sampletextsize),
legend.title.size = as.numeric(input$mutheatmap_legendtitlesize),
gene.text.size = gene.text.size,
use.adjVAF = input$mutheatmap_useadjvaf,
classByTumor = input$mutheatmap_classByTumor,
use.tumorSampleLabel = input$mutheatmap_usetumorsamplelabel)
incProgress(amount = 1)
setProgress(message = 'mutHeatmap done!')
})
return(hm)
})
output$mutheatmap.patientlist <- renderUI({
if(!is.null(mutheatmap())){
if(!identical(c("gg","ggplot"),class(mutheatmap()))){
names <- names(mutheatmap())
tagList(
selectInput("mutheatmap.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
)
}
}
})
getpatient.mutheatmap <- eventReactive(input$mutheatmap.pl,{
return(input$mutheatmap.pl)
})
mutheatmap_width <- reactive({
return(input$mutheatmap_width)
})
mutheatmap_height <- reactive({
return(input$mutheatmap_height)
})
output$mutheatmap_plot <- renderPlot({
if(!is.null(mutheatmap())){
if(!identical(c("gg","ggplot"),class(mutheatmap()))){
return(mutheatmap()[[getpatient.mutheatmap()]])
}else{
return(mutheatmap())
}
}
},
width = mutheatmap_width,
height = mutheatmap_height,
res = 100)
output$mutheatmap_db_ui <- renderUI({
if(!is.null(mutheatmap())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_mutheatmap_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_mutheatmap_plot', 'Download')
)
)
}
})
output$Download_mutheatmap_plot <- downloadHandler(
filename = function() {
paste("mutheatmap.",input$Download_mutheatmap_plot_check, sep='')
},
content = function(file) {
if (input$Download_mutheatmap_plot_check == "png"){
png(file,width = input$mutheatmap_width , height = input$mutheatmap_height,res = 100)
}
else if (input$Download_mutheatmap_plot_check == "pdf"){
pdf(file,width = input$mutheatmap_width/100 , height = input$mutheatmap_height/100)
}
if(!identical(c("gg","ggplot"),class(mutheatmap()))){
print(mutheatmap()[[getpatient.mutheatmap()]])
}else{
print(mutheatmap())
}
dev.off()
},
contentType = paste('image/',input$Download_mutheatmap_plot_check,sep="")
)
## caljsi sever
output$caljsi_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("caljsi_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "caljsi_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
output$caljsi_pairbytumor_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList" & !is.null(input$caljsi_patientid)){
if(length(input$caljsi_patientid) == 1){
x <- maf[[which(names(maf) == input$caljsi_patientid) ]]@data
if(length(unique(x$Tumor_ID)) <= 1){
return(NULL)
}
}
}else if(class(maf) == "Maf"){
x <- maf@data
if(length(unique(x$Tumor_ID)) <= 1){
return(NULL)
}
}
tagList(
checkboxInput('caljsi_pairbytumor',
value = FALSE,
label = div(style = "font-size:1.5em; font-weight:600; padding-left:12px", 'Pair by tumor'),
width = 500),
bsTooltip(id = "caljsi_pairbytumor",
title = "calculate JSI by tumor",
placement = "top",
trigger = "hover")
)
}
})
caljsi <- eventReactive(input$submit_caljsi,{
maf <- varsMaf$maf
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
if(is(maf, "MafList")){
maf_column <- colnames(getMafData(maf[[1]]) )
}else{
maf_column <- colnames(getMafData(maf) )
}
validate(
need("CCF" %in% maf_column, "Please upload ccf data in 'Input Data'!")
)
withProgress(min = 0, max = 1, value = 0, {
setProgress(message = 'Processing: calculating Jaccard similarity index')
# if(input$caljsi_title==""){
# title <- NULL
# }else{
# title <- input$caljsi_title
# }
if(is.null(input$caljsi_pairbytumor)){
pairbytumor <- FALSE
}else{
pairbytumor <- input$caljsi_pairbytumor
}
cc <- calJSI(maf,
patient.id = input$caljsi_patientid,
min.vaf = as.numeric(input$caljsi_minccf) ,
pairByTumor = pairbytumor,
# title = title,
use.circle = input$caljsi_usecircle,
number.cex = as.numeric(input$caljsi_numbercex),
number.col = input$caljsi_numbercol,
plot = TRUE,
use.tumorSampleLabel = input$caljsi_usetumorsamplelabel)
incProgress(amount = 1)
setProgress(message = 'caljsi done!')
})
return(cc)
})
output$caljsi.patientlist <- renderUI({
if(!is.null(caljsi())){
if(!"JSI.plot" %in% (names(caljsi()))){
names <- names(caljsi())
tagList(
selectInput("caljsi.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
)
}
}
})
getpatient.caljsi <- eventReactive(input$caljsi.pl,{
return(input$caljsi.pl)
})
caljsi_width <- reactive({
return(input$caljsi_width)
})
caljsi_height <- reactive({
return(input$caljsi_height)
})
output$caljsi_plot <- renderPlot({
if(!is.null(caljsi())){
if(!"JSI.plot" %in% names(caljsi())){
return(caljsi()[[getpatient.caljsi()]]$JSI.plot)
}else{
return(caljsi()$JSI.plot)
}
}
},
width = caljsi_width,
height = caljsi_height,
res = 100)
output$caljsi_db_ui <- renderUI({
if(!is.null(caljsi())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_caljsi_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_caljsi_plot', 'Download')
)
)
}
})
output$Download_caljsi_plot <- downloadHandler(
filename = function() {
paste("caljsi.",input$Download_caljsi_plot_check, sep='')
},
content = function(file) {
if (input$Download_caljsi_plot_check == "png"){
png(file,width = input$caljsi_width , height = input$caljsi_height,res = 100)
}
else if (input$Download_caljsi_plot_check == "pdf"){
pdf(file,width = input$caljsi_width/100 , height = input$caljsi_height/100)
}
if(!"JSI.plot" %in% names(caljsi())){
print(caljsi()[[getpatient.caljsi()]]$JSI.plot)
}else{
print(caljsi()$JSI.plot)
}
dev.off()
},
contentType = paste('image/',input$Download_caljsi_plot_check,sep="")
)
output$caljsi_pair_table <- DT::renderDataTable({
if(!is.null(caljsi())){
if(!"JSI.plot" %in% names(caljsi())){
m <- caljsi()[[getpatient.caljsi()]]$JSI.pair
}else{
m <- caljsi()$JSI.pair
}
rownames(m) <- colnames(m)
m <- as.data.frame(m)
colnames(m) <- rownames(m)
dt <- datatable(m,options = list(searching = TRUE,
pageLength = 10,
scrollX = TRUE,
dom = "t",
fixedHeader = TRUE),
rownames = TRUE)
return(dt)
}
})
output$caljsi_pair_table_ui <- renderUI({
if(!is.null(caljsi())){
tagList(
div(style = "font-size:1.5em; font-weight:600; ", "JSI pair"),
br(),
DT::dataTableOutput('caljsi_pair_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_caljsi_pair_table', 'Download')
)
)
)
}
})
output$Download_caljsi_pair_table <- downloadHandler(
filename = "caljsi.csv",
content = function(file){
if(!"JSI.plot" %in% names(caljsi())){
m <- caljsi()[[getpatient.caljsi()]]$JSI.pair
}else{
m <- caljsi()$JSI.pair
}
rownames(m) <- colnames(m)
m <- as.data.frame(m)
colnames(m) <- rownames(m)
write.csv(m,file,row.names = TRUE)
},
contentType = 'text/csv'
)
## classifymut sever
classifymut <- eventReactive(input$submit_classifymut,{
withProgress(min = 0, max = 2, value = 0, {
setProgress(message = 'Mutational lanscape : Calculation in progress',
detail = 'This may take a while...')
maf <- varsMaf$maf
validate(
need(!(is.null(maf)), "")
)
cc <- classifyMut(maf)
incProgress(amount = 1)
setProgress(message = 'Mutational lanscape: Calculation done!')
})
return(cc)
})
output$classifymut_plot <- renderPlot({
if(!is.null(classifymut())){
return(classifymut()$mut.profile.plot)
}
},
width = 560,
height = 560,
res = 100)
output$classifymut_download_button_ui <- renderUI({
if(!is.null(classifymut())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_classifymut_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_classifymut_plot', 'Download')
)
)
}
})
output$classifymut_table <- DT::renderDataTable({
if(!is.null(classifymut())){
t <- classifymut()$mut.class
dt <- datatable(t,
options = list(searching = TRUE,
pageLength = 10,
scrollX = TRUE,
dom = "t",
fixedHeader = TRUE),
rownames = FALSE)
return(dt)
}
})
output$classifymut_table_ui <- renderUI({
if(!is.null(classifymut())){
tagList(
h4(strong('Mutation class')),
br(),
DT::dataTableOutput('classifymut_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_classifymut_table', 'Download')
)
)
)
}
})
output$plotmutprofile.patientlist <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("plotmutprofile_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list,
multiple = TRUE),
bsTooltip(id = "plotmutprofile_patientid",
title = 'Select the specific patients. Default: NULL, all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
plotmutprofile <- eventReactive(input$submit_plotmutprofile,{
maf <- varsMaf$maf
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
withProgress(min = 0, max = 1, value = 0, {
setProgress(message = 'Processing: drawing mutational profile')
if(is.null(input$plotmutprofile_patientid)){
patientid <- NULL
}else{
patientid <- input$plotmutprofile_patientid
}
if(input$plotmutprofile_usegenelist){
if(!is.null(input$plotmutprofile_genelist$datapath)){
genelist <- as.character(read.table(input$plotmutprofile_genelist$datapath)$V1)
}else{
genelist_file <- system.file("extdata", "IntOGen-DriverGenes_COREAD.tsv", package = "MesKit")
genelist <- as.character(read.table(genelist_file)$V1)
}
}else{
genelist <- NULL
}
p <- plotMutProfile(maf,
patient.id = patientid,
geneList = genelist,
classByTumor = input$plotmutprofile_classByTumor,
class = input$plotmutprofile_class,
topGenesCount = input$plotmutprofile_topGenesCount,
removeEmptyCols = input$plotmutprofile_remove_empty_columns,
removeEmptyRows = input$plotmutprofile_remove_empty_rows,
use.tumorSampleLabel = input$plotmutprofile_usetumorsamplelabel)
incProgress(amount = 1)
setProgress(message = 'plotMutProfile done!')
})
return(p)
})
getpatient.plotmutprofile <- eventReactive(input$plotmutprofile.pl,{
return(input$plotmutprofile.pl)
})
plotmutprofile_width <- reactive({
return(input$plotmutprofile_width)
})
plotmutprofile_height <- reactive({
return(input$plotmutprofile_height)
})
output$plotmutprofile_plot <- renderPlot({
if(!is.null(plotmutprofile())){
plotmutprofile()
}
},
width = plotmutprofile_width,
height = plotmutprofile_height,
res = 100)
output$plotmutprofile_download_button_ui <- renderUI({
if(as.numeric(input$submit_plotmutprofile) > 0){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_plotmutprofile_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_plotmutprofile_plot', 'Download')
)
)
}
})
output$Download_plotmutprofile_plot <- downloadHandler(
filename = function() {
paste("mutationprofile.",input$Download_plotmutprofile_plot_check, sep='')
},
content = function(file) {
if (input$Download_plotmutprofile_plot_check == "png"){
png(file,width = input$plotmutprofile_width , height = input$plotmutprofile_height,res = 100)
}
else if (input$Download_plotmutprofile_plot_check == "pdf"){
pdf(file,width = input$plotmutprofile_width/100 , height = input$plotmutprofile_height/100)
}
print(plotmutprofile())
dev.off()
},
contentType = paste('image/',input$Download_plotmutprofile_plot_check,sep="")
)
## plotCNA sever
observeEvent(input$iecontrol_seg,{
buttonValue$seg <- buttonValue$seg + 1
if(buttonValue$seg == 2){
buttonValue$seg <- 0
}
})
output$ie_seg <- renderUI({
if(buttonValue$seg == 1){
tagList(
h3(strong("The segment file")),
p("The segment file store information about copy number of each segment.",
style = "font-size:16px; font-weight:500;line-height:30px;"),
p(strong("Mandatory fields"),": Patient_ID, Tumor_Sample_Barcode, Chromosome, Start_Position, End_Position, CopyNumber, Tumor_Sample_Label(optional)",
style = "font-size:16px; font-weight:500;line-height:30px;"),
h3(strong("Example segment file:")),
DT::dataTableOutput("ied_seg"),
br()
)
}
})
output$ied_seg <- DT::renderDataTable({
if(buttonValue$seg == 1){
segFile <- system.file("extdata", "CRC_HZ.seg.txt", package = "MesKit")
seg <- suppressWarnings(data.table::fread(segFile, header=TRUE, sep="\t", stringsAsFactors = FALSE))
d <- datatable(seg, options = list(searching = TRUE, pageLength = 5, lengthMenu = c(5, 10, 15, 18), scrollX = TRUE, fixedColumns = TRUE, columnDefs=list(list(width="10em",targets="_all"))),rownames = FALSE, width=5)
return(d)
}
})
output$plotcna.patientlist <- renderUI({
if(!is.null(input$plotcna_segfile$datapath)){
seg <- readSegment(segFile = input$plotcna_segfile$datapath) %>% dplyr::bind_rows()
patient.list <- unique(seg$Patient_ID)
tagList(
selectizeInput("plotcna_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list,
multiple = TRUE),
bsTooltip(id = "plotcna_patientid",
title = 'Select the specific patients. Default: NULL, all patients are included',
placement = "top",
trigger = "hover"),
)
}else{
segFile <- system.file("extdata", "CRC_HZ.seg.txt", package = "MesKit")
seg <- readSegment(segFile = segFile) %>% dplyr::bind_rows()
patient.list <- unique(seg$Patient_ID)
tagList(
selectizeInput("plotcna_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list,
multiple = TRUE),
bsTooltip(id = "plotcna_patientid",
title = 'Select the specific patients. Default: NULL, all patients are included',
placement = "top",
trigger = "hover"),
)
}
})
output$plotcna_gistic_parameters_ui <- renderUI({
if(any(input$plotmutprofile_usegisticAmpGenes,
input$plotmutprofile_usegisticDelGenes,
input$plotmutprofile_usegisticAllLesions)){
tagList(
# checkboxInput('plotcna_showGISTICgene', label = div(style = "font-size:1.5em; font-weight:600; padding-left:15px", 'Show GISTIC gene'),value = FALSE,width = 400),
# bsTooltip(id = "plotcna_showGISTICgene",
# title = "Whether GISTIC gene in seg.Default FALSE.",
# placement = "top",
# trigger = "hover"),
tags$table(
tags$tr(id = "inline",
width = "100%",
tags$td(width = "50%", div(style = "font-size:1.5em; font-weight:600; ", "Gistic qvalue: ")),
tags$td(width = "50%", textInput(inputId = "plotcna_gisticqval", value = 0.25, label = NULL)))
),
bsTooltip(id = "plotcna_gisticqval",
title = "The threshold of gistic Q value. Default is 0.25",
placement = "top",
trigger = "hover")
)
}
})
plotcna <- eventReactive(input$submit_plotcna,{
# validate(
# need(!is.null(input$plotcna_segfile$datapath),
# "PlotCNA needs copy number information, upload segmentation file first"
# )
# )
withProgress(min = 0, max = 2, value = 0, {
if(is.null(input$plotcna_segfile$datapath)){
setProgress(message = 'Processing: drawing example CNA profile')
segFile <- system.file("extdata", "CRC_HZ.seg.txt", package = "MesKit")
}else{
setProgress(message = 'Processing: drawing CNA profile')
segFile <- input$plotcna_segfile$datapath
}
if(input$plotmutprofile_usegisticAmpGenes){
if(!is.null(input$plotcna_gisticAmpGenesFile$datapath)){
gisticAmpGenesFile <- input$plotcna_gisticAmpGenesFile$datapath
}else{
gisticAmpGenesFile <- system.file("extdata", "COREAD_amp_genes.conf_99.txt", package = "MesKit")
}
}else{
gisticAmpGenesFile <- NULL
}
if(input$plotmutprofile_usegisticDelGenes){
if(!is.null(input$plotcna_gisticDelGenesFile$datapath)){
gisticDelGenesFile <- input$plotcna_gisticDelGenesFile$datapath
}else{
gisticDelGenesFile <- system.file("extdata", "COREAD_del_genes.conf_99.txt", package = "MesKit")
}
}else{
gisticDelGenesFile <- NULL
}
if(input$plotmutprofile_usegisticAllLesions){
if(!is.null(input$plotcna_gisticAllLesionsFile$datapath)){
gisticAllLesionsFile <- input$plotcna_gisticAllLesionsFile$datapath
}else{
gisticAllLesionsFile <- system.file("extdata", "COREAD_all_lesions.conf_99.txt", package = "MesKit")
}
}else{
gisticAllLesionsFile <- NULL
}
seg <- readSegment(segFile = segFile,
gisticAllLesionsFile = gisticAllLesionsFile,
gisticAmpGenesFile = gisticAmpGenesFile,
gisticDelGenesFile = gisticDelGenesFile,
gistic.qval = as.numeric(input$plotcna_gisticqval) )
incProgress(amount = 1)
setProgress(message = 'Complete reading seg file!')
if(is.null(input$plotcna_patientid)){
patientid <- NULL
}else{
patientid <- input$plotcna_patientid
}
# if(is.null(input$plotcna_showGISTICgene)){
# show.GISTIC.gene <- FALSE
# }else{
# show.GISTIC.gene <- input$plotcna_showGISTICgene
# }
cna.plot <- plotCNA(seg,
patient.id = patientid,
refBuild = input$plotcna_refBuild,
sample.text.size = as.numeric(input$plotcna_sampletextsize) ,
sample.bar.height = as.numeric(input$plotcna_samplebarheight) ,
legend.text.size = as.numeric(input$plotcna_legendtextsize) ,
legend.title.size = as.numeric(input$plotcna_legendtitlesize) ,
chrom.bar.height = as.numeric(input$plotcna_chrombarheight),
showRownames = input$plotcna_showrownames,
removeEmptyChr = input$plotcna_removeempytchr,
use.tumorSampleLabel = input$plotcna_usetumorsamplelabel)
seg <- dplyr::bind_rows(seg)
if(!is.null(patientid)){
seg <- seg[Patient_ID %in% patientid]
}
incProgress(amount = 1)
setProgress(message = 'PlotCNA done!')
})
return(list(seg = seg, cna.plot = cna.plot))
})
# plotcna_value <- reactiveValues(v = plotcna())
plotcna_width <- reactive({
return(input$plotcna_width)
})
plotcna_height <- reactive({
return(input$plotcna_height)
})
output$plotcna_plot <- renderPlot({
if(!is.null(plotcna())){
return(plotcna()$cna.plot)
}
},
width = plotcna_width,
height = plotcna_height,
res = 100)
output$plotcna_download_button_ui <- renderUI({
if(!is.null(plotcna())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_plotcna_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_plotcna_plot', 'Download')
)
)
}
})
output$Download_plotcna_plot <- downloadHandler(
filename = function() {
paste("plotcna.",input$Download_plotcna_plot_check, sep='')
},
content = function(file) {
if (input$Download_plotcna_plot_check == "png"){
png(file,width = input$plotcna_width , height = input$plotcna_height,res = 100)
}
else if (input$Download_plotcna_plot_check == "pdf"){
pdf(file,width = input$plotcna_width/100 , height = input$plotcna_width/100)
}
print(plotcna()$cna.plot)
dev.off()
},
contentType = paste('image/',input$Download_plotcna_plot_check,sep="")
)
output$plotcna_table <- DT::renderDataTable({
if(!is.null(plotcna())){
t <- plotcna()$seg
d <- datatable(t, options = list(searching = TRUE, pageLength = 10, lengthMenu = c(5, 10, 15, 18), scrollX = TRUE, fixedColumns = TRUE, columnDefs=list(list(width="10em",targets="_all"))),rownames = FALSE, width=5)
return(d)
}
})
output$plotcna_table_ui <- renderUI({
if(!is.null(plotcna())){
tagList(
if(is.null(input$plotcna_segfile$datapath)){
div(style = "font-size:1.5em; font-weight:600; ", "Example segment(CRC_HZ)")
}else{
div(style = "font-size:1.5em; font-weight:600; ", "Segment")
},
br(),
DT::dataTableOutput('plotcna_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_plotcna_table', 'Download')
)
)
)
}
})
output$Download_plotcna_table <- downloadHandler(
filename = "plotcna.csv",
content = function(file){
data <- plotcna()$seg
write.csv(data,file,row.names = FALSE)
},
contentType = 'text/csv'
)
## testneutral sever
output$testneutral_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("testneutral_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "testneutral_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
testneutral <- eventReactive(input$submit_testneutral,{
maf <- varsMaf$maf
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
withProgress(min = 0, max = 1, value = 0, {
setProgress(message = 'testNeutral : Calculation in progress',
detail = 'This may take a while...')
t <- testNeutral(maf,
patient.id = input$testneutral_patientid,
min.vaf = as.numeric(input$testneutral_minvaf),
max.vaf = as.numeric(input$testneutral_maxvaf),
min.total.depth = as.numeric(input$testneutral_mintotaldepth),
withinTumor = input$testneutral_withintumor,
R2.threshold = as.numeric(input$testneutral_R2threshold),
min.mut.count = as.numeric(input$testneutral_minmutcount))
incProgress(amount = 1)
setProgress(message = 'testNeutral: Calculation done!')
})
validate(
need(!(is.na(t)), "No result is generated by testneutral.Try adjusting the parameters")
)
return(t)
})
output$testneutral.patientlist <- renderUI({
if(!is.null(testneutral())){
if(!"neutrality.metrics" %in% names(testneutral())){
patient.list <- testneutral()
names <- names(patient.list)
tagList(
selectInput("testneutral.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
)
}
}
})
getpatient.testneutral <- eventReactive(input$testneutral.pl,{
return(input$testneutral.pl)
})
output$testneutral.samplelist <- renderUI({
if(!is.null(testneutral())){
if(!"neutrality.metrics" %in% names(testneutral())){
patient <- input$testneutral.pl
sample.list <- testneutral()[[patient]]$model.fitting.plot
names <- names(sample.list)
tagList(
selectInput("testneutral.sl",
div(style = "font-size:1.5em; font-weight:600; ", 'Tumor sample barcode'),
choices = names, width = 600)
)
}else{
sample.list <- testneutral()$model.fitting.plot
names <- names(sample.list)
tagList(
selectInput("testneutral.sl",
div(style = "font-size:1.5em; font-weight:600; ", 'Tumor sample barcode'),
choices = names, width = 600)
)
}
}
})
getsample.testneutral <- eventReactive(input$testneutral.sl,{
return(input$testneutral.sl)
})
testneutral_width <- reactive({
return(input$testneutral_width)
})
testneutral_height <- reactive({
return(input$testneutral_height)
})
output$testneutral_plot <- renderPlot({
if(!is.null(testneutral())){
patient <- input$testneutral.pl
sample <- input$testneutral.sl
if(!"neutrality.metrics" %in% names(testneutral())){
return(testneutral()[[patient]]$model.fitting.plot[[sample]])
}else{
return(testneutral()$model.fitting.plot[[sample]])
}
}
},
width = testneutral_width,
height = testneutral_height,
res = 100)
output$testneutral_db_ui <- renderUI({
if(!is.null(testneutral())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_testneutral_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_testneutral_plot', 'Download')
)
)
}
})
output$Download_testneutral_plot <- downloadHandler(
filename = function() {
paste("testneutral.",input$Download_testneutral_plot_check, sep='')
},
content = function(file) {
if (input$Download_testneutral_plot_check == "png"){
png(file,width = input$testneutral_width , height = input$testneutral_height,res = 100)
}
else if (input$Download_testneutral_plot_check == "pdf"){
pdf(file,width = input$testneutral_width/100 , height = input$testneutral_height/100)
}
patient <- input$testneutral.pl
sample <- input$testneutral.sl
if(!"neutrality.metrics" %in% names(testneutral())){
print(testneutral()[[patient]]$model.fitting.plot[[sample]])
}else{
print(testneutral()$model.fitting.plot[[sample]])
}
dev.off()
},
contentType = paste('image/',input$Download_testneutral_plot_check,sep="")
)
output$testneutral_table <- DT::renderDataTable({
if(!is.null(testneutral())){
if(!"neutrality.metrics" %in% names(testneutral())){
t <- testneutral()[[getpatient.testneutral()]]$neutrality.metrics
}else{
t <- testneutral()$neutrality.metrics
}
dt <- datatable(t,
options = list(searching = TRUE,
pageLength = 10,
scrollX = TRUE,
dom = "t",
fixedHeader = TRUE),
rownames = FALSE)
return(dt)
}
})
output$testneutral_table_ui <- renderUI({
if(!is.null(testneutral())){
tagList(
div(style = "font-size:1.5em; font-weight:600; ", "Neutrality metrics"),
br(),
DT::dataTableOutput('testneutral_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_testneutral_table', 'Download')
)
)
)
}
})
output$Download_testneutral_table <- downloadHandler(
filename = "testneutral.csv",
content = function(file){
if(!"neutrality.metrics" %in% names(testneutral())){
t <- testneutral()[[getpatient.testneutral()]]$neutrality.metrics
}else{
t <- testneutral()$neutrality.metrics
}
write.csv(t,file,row.names = FALSE)
},
contentType = 'text/csv'
)
## compareccf sever
output$compareccf_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("compareccf_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "compareccf_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
output$compareccf_pairbytumor_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList" & !is.null(input$compareccf_patientid)){
if(length(input$compareccf_patientid) == 1){
x <- maf[[which(names(maf) == input$compareccf_patientid) ]]@data
if(length(unique(x$Tumor_ID)) <= 1){
return(NULL)
}
}
}else if(class(maf) == "Maf"){
x <- maf@data
if(length(unique(x$Tumor_ID)) <= 1){
return(NULL)
}
}
tagList(
checkboxInput('compareccf_pairbytumor',
value = FALSE,
label = div(style = "font-size:1.5em; font-weight:600; padding-left:12px", 'Pair by tumor'),
width = 500),
bsTooltip(id = "compareccf_pairbytumor",
title = "Pair by tumor types in each patients,default is FALSE.",
placement = "top",
trigger = "hover")
)
}
})
compareccf <- eventReactive(input$submit_compareccf, {
maf <- isolate(varsMaf$maf)
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
if(is(maf, "MafList")){
maf_column <- colnames(getMafData(maf[[1]]) )
}else{
maf_column <- colnames(getMafData(maf) )
}
validate(
need("CCF" %in% maf_column, "Please upload ccf data in 'Input Data'!")
)
progress <- Progress$new(session, min=0, max=1)
on.exit(progress$close())
progress$set(message = 'Processing: comparing CCFs in paired samples')
if(is.null(input$compareccf_pairbytumor)){
pairbytumor <- FALSE
}else{
pairbytumor <- input$compareccf_pairbytumor
}
cc <- compareCCF(maf,
patient.id = input$compareccf_patientid,
min.ccf = input$compareccf_minccf,
pairByTumor = pairbytumor,
use.tumorSampleLabel = input$compareccf_usetumorsamplelabel)
progress$set(value = 1)
return(cc)
})
output$compareccf.patientlist <- renderUI({
if(!is.null(compareccf())){
if(class(compareccf()[[1]]) != "data.frame"){
patient.list <- compareccf()
names <- names(patient.list)
tagList(
selectInput("compareccf.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
)
}
}
})
getpatient.compareccf <- eventReactive(input$compareccf.pl,{
return(input$compareccf.pl)
})
output$compareccf.samplelist <- renderUI({
if(!is.null(compareccf())){
if(is.null(input$compareccf_pairbytumor)){
title <- "Sample pair"
}else{
if(input$compareccf_pairbytumor){
title <- "Tumor pair"
}else{
title <- "Sample pair"
}
}
if(class(compareccf()[[1]]) != "data.frame"){
patient <- input$compareccf.pl
sample.list <- compareccf()[[patient]]
names <- names(sample.list)
tagList(
selectInput("compareccf.sl",
div(style = "font-size:1.5em; font-weight:600; ", title),
choices = names, width = 600)
)
}else{
sample.list <- compareccf()
names <- names(sample.list)
tagList(
selectInput("compareccf.sl",
div(style = "font-size:1.5em; font-weight:600; ", title),
choices = names, width = 600)
)
}
}
})
getsample.compareccf <- eventReactive(input$compareccf.sl,{
return(input$compareccf.sl)
})
output$compareccf_table_ui <- renderUI({
if(!is.null(compareccf())){
tagList(
br(),
DT::dataTableOutput('compareccf_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_compareccf_table', 'Download')
)
)
)
}
})
output$compareccf_table <- DT::renderDataTable({
if(!is.null(compareccf())){
if(class(compareccf()[[1]]) != "data.frame"){
t <- compareccf()[[getpatient.compareccf()]][[getsample.compareccf()]]
}else{
t <- compareccf()[[getsample.compareccf()]]
}
dt <- datatable(t,rownames = FALSE)
return(dt)
}
})
output$Download_compareccf_table <- downloadHandler(
filename = "compareccf.csv",
content = function(file){
if(class(compareccf()[[1]]) != "data.frame"){
t <- compareccf()[[getpatient.compareccf()]][[getsample.compareccf()]]
}else{
t <- compareccf()[[getsample.compareccf()]]
}
write.csv(t,file,row.names = FALSE)
},
contentType = 'text/csv'
)
varsphyloTree <- reactiveValues()
observeEvent(input$submit_getphylotree,{
maf <- isolate(varsMaf$maf)
validate(
need(!is.null(maf), "Upload maf file in the section 'Input Data'")
)
withProgress(min = 0, max = 1, value = 0, {
## Rshiny: progress bar
setProgress(message = 'Generating ', detail = paste("phyloTree/phyloTreeList Class", sep=""))
phyloTree <- getPhyloTree(maf,
min.vaf = as.numeric(input$getphylotree_minvaf),
min.ccf = as.numeric(input$getphylotree_minccf),
bootstrap.rep.num = as.numeric(input$getphylotree_bootstraprepnum))
varsphyloTree[["phyloTree"]] <- phyloTree
incProgress(amount=1)
## Rshiny: progress bar
# setProgress(message = 'Input data: Generating ', detail = paste("phyloTree from MAF ",sep=""))
# varsMaf[['phyloTree']] <- phyloTree <- getPhyloTree(isolate(varsMaf$maf),method = input$method)
# incProgress(amount=1)
setProgress(message = paste("Input data: phyloTree/phyloTreeList Generation Done!", sep=""), detail = "")
Sys.sleep(1)
})
})
output$plotphylotree_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("plotphylotree_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "plotphylotree_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
phylotree <- eventReactive(input$submit_plotphylotree, {
maf <- isolate(varsMaf$maf)
validate(
need(!is.null(maf), "Upload maf file in the section 'Input Data'")
)
withProgress(min = 0, max = 2, value = 0,{
setProgress(message = "Generating phyloTree/phyloTreeList Class")
phyloTree <- getPhyloTree(maf,
patient.id = input$plotphylotree_patientid,
min.vaf = as.numeric(input$plotphylotree_getphylotree_minvaf),
min.ccf = as.numeric(input$plotphylotree_getphylotree_minccf),
method = input$plotphylotree_getphylotree_method,
bootstrap.rep.num = as.numeric(input$plotphylotree_getphylotree_bootstraprepnum))
incProgress(amount=1)
setProgress(message = 'Processing: visualize phylogenetic tree')
if(input$plotphylotree_branchcol == "NULL"){
branchCol <- NULL
}else{
branchCol <- input$plotphylotree_branchcol
}
scale_bar_x <- NULL
scale_bar_y <- NULL
if(input$plotphylotree_show_scale_bar){
if(input$plotphylotree_scale_bar_x != ""){
scale_bar_x <- as.numeric(input$plotphylotree_scale_bar_x)
}else{
scale_bar_x <- NULL
}
if(input$plotphylotree_scale_bar_y != ""){
scale_bar_y <- as.numeric(input$plotphylotree_scale_bar_y)
}else{
scale_bar_y <- NULL
}
}
plot.list <- plotPhyloTree(phyloTree,
branchCol = branchCol,
show.bootstrap = input$plotphylotree_showbootstrap,
min.ratio = as.numeric(input$plotphylotree_minratio) ,
signaturesRef = input$plotphylotree_signatureref,
min.mut.count = as.numeric(input$plotphylotree_minmutcount),
use.tumorSampleLabel = input$plotphylotree_usetumorsamplelabel,
show.scale.bar = input$plotphylotree_show_scale_bar,
scale.bar.x = scale_bar_x,
scale.bar.y = scale_bar_y)
incProgress(amount=1)
setProgress(message = paste("Plot phylotree done!", sep=""), detail = "")
Sys.sleep(1)
})
return(plot.list)
})
output$phylotree.patientlist <- renderUI({
if(!is.null(phylotree())){
if(!identical(c("gg","ggplot"),class(phylotree()))){
names <- names(phylotree())
selectInput("phylotree.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
}
}
})
getpatient.phylotree <- eventReactive(input$phylotree.pl,{
return(input$phylotree.pl)
})
plotphylotree_width <- reactive({
return(input$plotphylotree_width)
})
plotphylotree_height <- reactive({
return(input$plotphylotree_height)
})
output$phylotree_plot <- renderPlot({
if(!is.null(phylotree())){
if(!identical(c("gg","ggplot"),class(phylotree()))){
return(phylotree()[[getpatient.phylotree()]])
}else{
return(phylotree())
}
}
},
width = plotphylotree_width,
height = plotphylotree_height,
res = 100
)
output$phylotree_downloadbutton_ui<- renderUI({
if(!is.null(phylotree())){
br()
br()
fluidRow(
column(
width = 2,
radioButtons('Download_phylotree_check', label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"), inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_phylotree', 'Download')
)
)
}
})
output$Download_phylotree <- downloadHandler(
filename = function() {
paste("phylotree.",input$Download_phylotree_check, sep='')
},
content = function(file) {
if (input$Download_phylotree_check == "png"){
png(file,width = input$plotphylotree_width , height = input$plotphylotree_height,res = 100)
}
else if (input$Download_phylotree_check == "pdf"){
pdf(file,width = input$plotphylotree_width/100 , height = input$plotphylotree_height/100)
}
if(!identical(c("gg","ggplot"),class(phylotree()))){
print(phylotree()[[getpatient.phylotree()]])
}else{
print(phylotree())
}
dev.off()
},
contentType = paste('image/',input$Download_phylotree_check,sep="")
)
comparetree <- eventReactive(input$submit_comparetree, {
maf <- isolate(varsMaf$maf)
validate(
need(!is.null(maf), "Upload maf file in the section 'Input Data'")
)
withProgress(min = 0, max = 1, value = 0,{
setProgress(message = 'Processing: compare phylogenetic trees')
phylotree1 <- getPhyloTree(maf, patient.id = input$comparetree_patientid,
method = input$comparetree_getphylotree_method1,
min.ccf = as.numeric(input$comparetree_getphylotree_minccf) ,
min.vaf = as.numeric(input$comparetree_getphylotree_minvaf) ,
bootstrap.rep.num = as.numeric(input$comparetree_getphylotree_bootstraprepnum))
phylotree2 <- getPhyloTree(maf, patient.id = input$comparetree_patientid,
method = input$comparetree_getphylotree_method2,
min.ccf = as.numeric(input$comparetree_getphylotree_minccf) ,
min.vaf = as.numeric(input$comparetree_getphylotree_minvaf) ,
bootstrap.rep.num = as.numeric(input$comparetree_getphylotree_bootstraprepnum) )
ct <- compareTree(phylotree1, phylotree2,
# common.col = input$comparetree_commoncol,
min.ratio = as.numeric(input$comparetree_minratio) ,
show.bootstrap = input$comparetree_showbootstrap,
plot = TRUE,
use.tumorSampleLabel = input$comparetree_usetumorsamplelabel)
incProgress(amount=1)
setProgress(message = paste("Comparetree done!", sep=""), detail = "")
Sys.sleep(1)
})
return(ct)
})
output$comparetree.patientlist <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
}else{
patient.list <- unique(maf@data$Patient_ID)
}
tagList(
selectInput("comparetree_patientid",
label = div(style = "font-size:1.6em; font-weight:600; ", "Select patients"),
choices = patient.list),
bsTooltip(id = "comparetree_patientid",
title = 'Select the specific patient',
placement = "top",
trigger = "hover"),
)
}
})
comparetree_width <- reactive({
return(input$comparetree_width)
})
comparetree_height <- reactive({
return(input$comparetree_height)
})
output$comparetree_plot <- renderPlot({
if(!is.null(comparetree())){
return(comparetree()$compare.plot)
}
},
width = comparetree_width,
height = comparetree_height,
res = 100
)
output$comparetree_dist <- renderPrint({
if(!is.null(comparetree())){
return(comparetree()$compare.dist)
}
})
output$comparetree_db_ui<- renderUI({
if(!is.null(comparetree())){
br()
br()
fluidRow(
column(
width = 2,
radioButtons('Download_comparetree_check', label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"), inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_comparetree', 'Download')
)
)
}
})
output$Download_comparetree <- downloadHandler(
filename = function() {
paste("comparetree.",input$Download_comparetree_check, sep='')
},
content = function(file) {
if (input$Download_comparetree_check == "png"){
png(file,width = input$comparetree_width , height = input$comparetree_height,res = 100)
}
else if (input$Download_comparetree_check == "pdf"){
pdf(file,width = input$comparetree_width/100 , height = input$comparetree_height/100)
}
print(comparetree()$compare.plot)
dev.off()
},
contentType = paste('image/',input$Download_comparetree_check,sep="")
)
output$treemutsig_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("treemutsig_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "treemutsig_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
treemutsig <- eventReactive(input$submit_treemutsig, {
maf <- isolate(varsMaf$maf)
validate(
need(!is.null(maf), "Upload maf file in the section 'Input Data'")
)
withProgress(min = 0, max = 4, value = 0,{
setProgress(message = 'Generating phyloTree/phyloTreeList Class')
phyloTree <- getPhyloTree(maf,
patient.id = input$treemutsig_patientid,
method = input$treemutsig_getphylotree_method,
min.vaf = as.numeric(input$treemutsig_getphylotree_minvaf),
min.ccf = as.numeric(input$treemutsig_getphylotree_minccf),
bootstrap.rep.num = as.numeric(input$treemutsig_getphylotree_bootstraprepnum))
incProgress(amount=1)
setProgress(message = 'Processing: decomposing matrix of somatic SNVs')
tm <- triMatrix(phyloTree,
# withinTumor = input$treemutsig_withintumor,
level = input$treemutsig_level)
incProgress(amount = 1)
setProgress(message = 'Processing: fitSignatrues')
fs <- fitSignatures(tm, signaturesRef = input$treemutsig_signatureref,
min.mut.count = as.numeric(input$treemutsig_minmutcount) ,
signature.cutoff = as.numeric(input$treemutsig_signaturecutoff))
incProgress(amount = 1)
setProgress(message = 'Processing: reconstructing mutational profiles with known signatures')
if(input$treemutsig_mode == 'NULL'){
mode <- NULL
}else{
mode <- input$treemutsig_mode
}
pms <- plotMutSigProfile(fs, mode = mode,
use.tumorSampleLabel = input$treemutsig_usetumorsamplelabel)
incProgress(amount = 1)
setProgress(message = 'plotMutSigProfile done!')
Sys.sleep(1)
return(pms)
})
})
output$treemutsig.patientlist <- renderUI({
if(!is.null(treemutsig())){
if(is(treemutsig()[[1]],"list")){
plot.list <- treemutsig()
names <- names(plot.list)
selectInput("treemutsig.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
}
}
})
getpatient.treemutsig <- eventReactive(input$treemutsig.pl,{
return(input$treemutsig.pl)
})
output$treemutsig.samplelist <- renderUI({
if(!is.null(treemutsig())){
if(is(treemutsig()[[1]],"list")){
patient <- input$treemutsig.pl
sample.list <- treemutsig()[[patient]]
names <- names(sample.list)
tagList(
selectInput("treemutsig.sl",
div(style = "font-size:1.5em; font-weight:600; ", 'Select branch'),
choices = names, width = 600)
)
}else{
sample.list <- treemutsig()
names <- names(sample.list)
tagList(
selectInput("treemutsig.sl",
div(style = "font-size:1.5em; font-weight:600; ", 'Select branch'),
choices = names, width = 600)
)
}
}
})
getsample.treemutsig <- eventReactive(input$treemutsig.sl,{
return(input$treemutsig.sl)
})
treemutsig_width <- reactive({
return(input$treemutsig_width)
})
treemutsig_height <- reactive({
return(input$treemutsig_height)
})
output$treemutsig_plot <- renderPlot({
if(!is.null(treemutsig())){
if(is(treemutsig()[[1]],"list")){
return(treemutsig()[[getpatient.treemutsig()]][[getsample.treemutsig()]])
}else{
return(treemutsig()[[getsample.treemutsig()]])
}
}
},
width = treemutsig_width,
height = treemutsig_height,
res = 100
)
output$treemutsig_download_button_ui <- renderUI({
if(!is.null(treemutsig())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_treemutsig_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_treemutsig_plot', 'Download')
)
)
}
})
output$Download_treemutsig_plot <- downloadHandler(
filename = function() {
paste("treemutsig.",input$Download_treemutsig_plot_check, sep='')
},
content = function(file) {
if (input$Download_treemutsig_plot_check == "png"){
png(file,width = input$treemutsig_width , height = input$treemutsig_height,res = 100)
}
else if (input$Download_treemutsig_plot_check == "pdf"){
pdf(file,width = input$treemutsig_width/100 , height = input$treemutsig_height/100)
}
if(is(treemutsig()[[1]],"list")){
print(treemutsig()[[getpatient.treemutsig()]][[getsample.treemutsig()]])
}else{
print(treemutsig()[[getsample.treemutsig()]])
}
dev.off()
},
contentType = paste('image/',input$Download_treemutsig_plot_check,sep="")
)
output$treemutsig_table_ui <- renderUI({
if(!is.null(treemutsig())){
tagList(
div(style = "font-size:1.5em; font-weight:600; ", "Signature summary"),
br(),
DT::dataTableOutput('treemutsig_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_treemutsig_table', 'Download')
)
),
br()
)
}
})
output$muttrunkbranch_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("muttrunkbranch_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "muttrunkbranch_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
muttrunkbranch <- eventReactive(input$submit_muttrunkbranch, {
maf <- isolate(varsMaf$maf)
validate(
need(!is.null(maf), "Upload maf file in the section 'Input Data'")
)
withProgress(min = 0, max = 2, value = 0,{
setProgress(message = 'Generating phyloTree/phyloTreeList Class')
phyloTree <- getPhyloTree(maf,
patient.id = input$muttrunkbranch_patientid,
method = input$muttrunkbranch_getphylotree_method,
min.vaf = as.numeric(input$muttrunkbranch_getphylotree_minvaf),
min.ccf = as.numeric(input$muttrunkbranch_getphylotree_minccf),
bootstrap.rep.num = as.numeric(input$muttrunkbranch_getphylotree_bootstraprepnum))
incProgress(amount = 1)
setProgress(message = 'mutTrunkBranch : Calculation in progress')
mtb <- mutTrunkBranch(phyloTree, CT = input$muttrunkbranch_ct,
pvalue = as.numeric(input$muttrunkbranch_pvalue))
incProgress(amount = 1)
setProgress(message = 'mutTrunkBranch done!')
return(mtb)
})
})
getpatient.muttrunkbranch <- eventReactive(input$muttrunkbranch.pl,{
return(input$muttrunkbranch.pl)
})
output$muttrunkbranch.patientlist <- renderUI({
if(!is.null(muttrunkbranch())){
if(!"mutTrunkBranch.plot" %in% names(muttrunkbranch()) ){
x <- muttrunkbranch()
patient.list <- names(x)
selectInput("muttrunkbranch.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = patient.list, width = 600)
}
}
})
muttrunkbranch_width <- reactive({
return(input$muttrunkbranch_width)
})
muttrunkbranch_height <- reactive({
return(input$muttrunkbranch_height)
})
output$muttrunkbranch_plot <- renderPlot({
if(!is.null(muttrunkbranch())){
if(!"mutTrunkBranch.plot" %in% names(muttrunkbranch())){
p <- muttrunkbranch()[[getpatient.muttrunkbranch()]]$mutTrunkBranch.plot
}else{
p <- muttrunkbranch()$mutTrunkBranch.plot
}
return(p)
}
},
width = muttrunkbranch_width,
height = muttrunkbranch_height,
res = 100
)
output$muttrunkbranch_download_button_ui <- renderUI({
if(!is.null(muttrunkbranch())){
fluidRow(
column(
width = 2,
radioButtons('Download_muttrunkbranch_plot_check', label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),choiceValues = c("png", "pdf"), inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_muttrunkbranch_plot', 'Download')
)
)
}
})
output$Download_muttrunkbranch_plot <- downloadHandler(
filename = function() {
paste("muttrunkbranch.",input$Download_muttrunkbranch_plot_check, sep='')
},
content = function(file) {
if (input$Download_muttrunkbranch_plot_check == "png"){
png(file,width = input$muttrunkbranch_width , height = input$muttrunkbranch_height,res = 100)
}
else if (input$Download_muttrunkbranch_plot_check == "pdf"){
pdf(file,width = input$muttrunkbranch_width/100 , height = input$muttrunkbranch_height/100)
}
if(!"mutTrunkBranch.plot" %in% names(muttrunkbranch())){
p <- muttrunkbranch()[[getpatient.muttrunkbranch()]]$mutTrunkBranch.plot
}else{
p <- muttrunkbranch()$mutTrunkBranch.plot
}
print(p)
dev.off()
},
contentType = paste('image/',input$Download_muttrunkbranch_plot_check,sep="")
)
output$muttrunkbranch_table_ui <- renderUI({
if(!is.null(muttrunkbranch())){
tagList(
div(style = "font-size:1.5em; font-weight:600; ", "Summary"),
br(),
DT::dataTableOutput('muttrunkbranch_table'),
fluidRow(
column(
width = 3,
downloadBttn('Download_muttrunkbranch_table', 'Download')
)
)
)
}
})
output$muttrunkbranch_table <- DT::renderDataTable({
if(!is.null(muttrunkbranch())){
if(!"mutTrunkBranch.plot" %in% names(muttrunkbranch())){
t <- muttrunkbranch()[[getpatient.muttrunkbranch()]]$mutTrunkBranch.res
}else{
t <- muttrunkbranch()$mutTrunkBranch.res
}
dt <- datatable(t, options = list(searching = TRUE, pageLength = 10, lengthMenu = c(5, 10, 15, 18), scrollX = TRUE, fixedColumns = TRUE, columnDefs=list(list(width="10em",targets="_all"))),rownames = FALSE, width=5)
return(dt)
}
})
output$Download_muttrunkbranch_table <- downloadHandler(
filename = "muttrunkbranch.csv",
content = function(file){
if(!"mutTrunkBranch.plot" %in% names(muttrunkbranch())){
t <- muttrunkbranch()[[getpatient.muttrunkbranch()]]$mutTrunkBranch.res
}else{
t <- muttrunkbranch()$mutTrunkBranch.res
}
write.csv(t, file, row.names = FALSE)
},
contentType = 'text/csv'
)
})
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MesKit documentation built on March 28, 2021, 6 p.m.
R Package Documentation
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# Define server logic required to plot various variables against mpg
shinyServer(function(input, output, session){
observeEvent(input$help, {
updateTabItems(session, "sidername", "home")
})
observeEvent(input$contact, {
updateTabItems(session, "sidername", "home")
})
inputData <- eventReactive(input$submit1, {
if(input$submit1){
if(is.null(input$mafFile$datapath)){
mafFile <- system.file("extdata", "CRC_HZ.maf", package = "MesKit")
clinFile <- system.file("extdata/", "CRC_HZ.clin.txt", package = "MesKit")
if(input$useccffile){
ccfFile <- system.file("extdata", "CRC_HZ.ccf.tsv", package = "MesKit")
}else{
ccfFile <- NULL
}
maf <- readMaf(mafFile = mafFile, clinicalFile = clinFile, ccfFile = ccfFile)
} else {
if(!is.null(input$mafFile)){
if(is.null(input$ccfFile)){
ccfFile <- NULL
}else{
ccfFile <- input$ccfFile$datapath
}
maf <- readMaf(mafFile = input$mafFile$datapath,
clinicalFile = input$clinFile$datapath,
ccfFile = ccfFile,
refBuild = input$ref,
use.indel.ccf = input$ccfFile_use_indel_ccf)
}
else{
maf <- readMaf(mafFile = input$mafFile$datapath,
clinicalFile = input$clinFile$datapath,
refBuild = input$ref)
}
}
return(maf)
}
})
varsMaf <- reactiveValues()
observeEvent(input$submit1,{
withProgress(min = 0, max = 1, value = 0, {
## Rshiny: progress bar
setProgress(message = 'Processing: generating Maf/MafList Class')
varsMaf[['maf']] <- inputData()
incProgress(amount=1)
setProgress(message = "Maf/MafList Generation Done!")
Sys.sleep(1)
})
})
buttonValue <- reactiveValues(maf = 0, ccf = 0, clin = 0, seg = 0)
observeEvent(input$iecontrol01,{
buttonValue$ccf <- 0
buttonValue$clin <- 0
buttonValue$maf <- buttonValue$maf + 1
if(buttonValue$maf == 2){
buttonValue$maf <- 0
}
})
observeEvent(input$iecontrol02,{
buttonValue$maf <- 0
buttonValue$clin <- 0
buttonValue$ccf <- buttonValue$ccf + 1
if(buttonValue$ccf == 2){
buttonValue$ccf <- 0
}
})
observeEvent(input$iecontrol_clin,{
buttonValue$maf <- 0
buttonValue$ccf <- 0
buttonValue$clin <- buttonValue$clin + 1
if(buttonValue$clin == 2){
buttonValue$clin <- 0
}
})
## output Introduction of maf datatable
output$ie1 <- renderUI({
if(buttonValue$maf == 1){
tagList(
div(
h3(strong("The MAF files")),
p("MAF files contain many fields of information about chromosome and gene mutations and
their annotations. The following fields are highly recommended to be contained in
the MAF files.",
style = "font-size:16px; font-weight:500;line-height:30px;"),
p(strong("Mandatory fields"),": Hugo_Symbol, Chromosome, Start_Position, End_Position,
Variant_Classification, Variant_Type, Reference_Allele,
Tumor_Seq_Allele2, Ref_allele_depth, Alt_allele_depth,
VAF, Tumor_Sample_Barcode, Patient_ID, Tumor_ID",
style = "font-size:16px; font-weight:500;line-height:30px;"),
h3(strong("Example MAF file"))
),
DT::dataTableOutput("ied1",width = "100%"),
br()
)
}
})
output$ied1 <- DT::renderDataTable({
if(buttonValue$maf == 1){
mafFile <- system.file("extdata/", "CRC_HZ.maf", package = "MesKit")
maf_data <- data.table::fread(
file = mafFile,
quote = "",
header = TRUE,
data.table = TRUE,
fill = TRUE,
sep = '\t',
skip = "Hugo_Symbol",
stringsAsFactors = FALSE
)
d <- datatable(maf_data,
options = list(searching = TRUE,
pageLength = 5,
lengthMenu = c(5, 10, 15, 18),
scrollX = TRUE, fixedColumns = TRUE,
columnDefs=list(list(width="10em",targets="_all"))),
rownames = FALSE, width=5)
return(d)
}
})
## output Introduction of CCF
output$ie2 <- renderUI({
if(buttonValue$ccf == 1){
tagList(
h3(strong("The CCF file")),
p("CCF files contain cancer cell fraction of each mutation.",
style = "font-size:16px; font-weight:500;line-height:30px;"),
p(strong("Mandatory fields"),": Patient_ID, Tumor_Sample_Barcode, Chromosome, Start_Position, CCF, CCF_std/CCF_CI_High (required when identify clonal/subclonal mutations)",
style = "font-size:16px; font-weight:500;line-height:30px;"),
h3(strong("Example CCF file:")),
DT::dataTableOutput("ied2"),
br()
)
}
})
output$ied2 <- DT::renderDataTable({
if(buttonValue$ccf == 1){
ccfFile <- system.file("extdata/", "CRC_HZ.ccf.tsv", package = "MesKit")
ccf_data <- suppressWarnings(data.table::fread(
ccfFile,
quote = "",
header = TRUE,
fill = TRUE,
sep = '\t',
stringsAsFactors = FALSE
))
d <- datatable(ccf_data, options = list(searching = TRUE, pageLength = 5, lengthMenu = c(5, 10, 15, 18), scrollX = TRUE, fixedColumns = TRUE, columnDefs=list(list(width="10em",targets="_all"))),rownames = FALSE, width=5)
return(d)
}
})
## output Introduction of clinical file
output$ie_clin <- renderUI({
if(buttonValue$clin == 1){
tagList(
h3(strong("The clinical file")),
p("Clinical file store clinical information.",
style = "font-size:16px; font-weight:500;line-height:30px;"),
p(strong("Mandatory fields"),": Tumor_Sample_Barcode, Tumor_ID, Patient_ID, Tumor_Sample_Label(optional)",
style = "font-size:16px; font-weight:500;line-height:30px;"),
h3(strong("Example clinical file:")),
DT::dataTableOutput("ied_clin"),
br()
)
}
})
output$ied_clin <- DT::renderDataTable({
if(buttonValue$clin == 1){
clin.File <- system.file("extdata/", "CRC_HZ.clin.txt", package = "MesKit")
clin_data <- data.table::fread(
file = clin.File,
quote = "",
header = TRUE,
data.table = TRUE,
fill = TRUE,
sep = '\t',
stringsAsFactors = FALSE
)
d <- datatable(clin_data, options = list(searching = TRUE, pageLength = 5, lengthMenu = c(5, 10, 15, 18), scrollX = TRUE, fixedColumns = TRUE, columnDefs=list(list(width="10em",targets="_all"))),rownames = FALSE, width=5)
return(d)
}
})
output$datapreview <- renderUI({
if(input$submit1){
DT::dataTableOutput('maftable', width = '100%')
}
})
output$maftable <- DT::renderDataTable({
if(input$submit1){
maf <- inputData()
if(class(maf) == "Maf"){
t <- datatable(inputData()@data, options = list(searching = TRUE, pageLength = 10, lengthMenu = c(5, 10, 15, 18), scrollX = TRUE, fixedColumns = TRUE, columnDefs=list(list(width="10em",targets="_all"))),rownames = FALSE, width=5)
}else{
t <- datatable(inputData()[[1]]@data, options = list(searching = TRUE, pageLength = 10, lengthMenu = c(5, 10, 15, 18), scrollX = TRUE, fixedColumns = TRUE, columnDefs=list(list(width="10em",targets="_all"))),rownames = FALSE, width=5)
}
return(t)
}
})
output$mathscore_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("mathscore_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "mathscore_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
ms <- eventReactive(input$submit_mathscore, {
maf <- isolate(varsMaf$maf)
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
patientid <- input$mathscore_patientid
progress <- Progress$new(session, min=1, max=15)
on.exit(progress$close())
progress$set(message = 'Processing: calculating MATH score...')
mathScore(maf,
patient.id = patientid,
min.vaf = as.numeric(input$mathscore_minvaf),
withinTumor = input$mathscore_withintumor,
use.adjVAF = input$mathscore_useadjvaf,
use.tumorSampleLabel = input$mathscore_usetumorsamplelabel)
})
getpatient.mathscore <- eventReactive(input$mathscore.patientlist, {
return(input$mathscore.patientlist)
})
output$mathscore.patientlist <- renderUI({
if(!is.null(ms())){
if(length(ms()) > 0){
names <- names(ms())
selectInput("mathscore.patientlist",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
}
}
})
output$mathScore <- DT::renderDataTable({
return(ms()[[getpatient.mathscore()]])
})
# ms_value <- ms()
output$msdb <- renderUI({
if(!is.null(ms())){
fluidRow(
column(
width = 9,
downloadBttn('DownloadMathScore', 'Download')
),
column(
width = 3
)
)
}
})
output$DownloadMathScore <- downloadHandler(
filename = "mathscore.csv",
content = function(file){
data <- ms()
write.csv(data,file,row.names = FALSE)
},
contentType = 'text/csv'
)
output$vafcluster_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("vafcluster_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "vafcluster_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
vafcluster <- eventReactive(input$submit3, {
maf <- isolate(varsMaf$maf)
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
patientid <- input$vafcluster_patientid
withProgress(min = 0, max = 1, value = 0,{
setProgress(message = 'Processing: perform mutation clustering')
vc <- mutCluster(maf,
patient.id = patientid,
withinTumor = input$vafcluster_withintumor,
segFile = input$vafcluster_segfile,
# min.vaf = as.numeric(input$vafcluster_minvaf) ,
# max.vaf = as.numeric(input$vafcluster_maxvaf),
use.adjVAF = input$vafcluster_useadjvaf,
use.ccf = input$vafcluster_useccf,
use.tumorSampleLabel = input$vafcluster_usetumorsamplelabel)
incProgress(amount = 1)
setProgress(message = 'vafCluster done!')
})
return(vc)
})
getpatient.vafcluster <- eventReactive(input$vafcluster.patientlist, {
return(input$vafcluster.patientlist)
})
output$vafcluster.patientlist <- renderUI({
if(!is.null(vafcluster())){
if(!"cluster.plot" %in% names(vafcluster())){
names <- names(vafcluster())
selectInput("vafcluster.patientlist",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
}
}
})
output$vafcluster.samplelist <- renderUI({
if(!is.null(vafcluster())){
if("cluster.plot" %in% names(vafcluster())){
sample.list <- vafcluster()$cluster.plot
names <- names(sample.list)
}else{
sample.list <- vafcluster()[[getpatient.vafcluster()]]$cluster.plot
names <- names(sample.list)
print(names)
}
if(input$vafcluster_withintumor){
tagList(
selectInput("vafcluster.sl",
div(style = "font-size:1.5em; font-weight:600; ", 'Tumor ID'),
choices = names, width = 600)
)
}else{
tagList(
selectInput("vafcluster.sl",
div(style = "font-size:1.5em; font-weight:600; ", 'Tumor Sample Barcode'),
choices = names, width = 600)
)
}
}
})
getsample.vafcluster <- eventReactive(input$vafcluster.sl,{
return(input$vafcluster.sl)
})
vafcluster_width <- reactive({
return(input$vafcluster_width)
})
vafcluster_height <- reactive({
return(input$vafcluster_height)
})
output$vaf <- renderPlot({
if(!is.null(vafcluster())){
if("cluster.plot" %in% names(vafcluster())){
return(vafcluster()$cluster.plot[[getsample.vafcluster()]])
}else{
return(vafcluster()[[getpatient.vafcluster()]]$cluster.plot[[getsample.vafcluster()]])
}
}
},width = vafcluster_width,
height = vafcluster_height,
res = 100)
output$vcdb <- renderUI({
if(!is.null(vafcluster())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'DownloadVafPlotCheck',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('DownloadVafPlot', 'Download')
)
)
}
})
output$DownloadVafPlot <- downloadHandler(
filename = function() {
paste("vafcluster.",input$DownloadVafPlotCheck, sep='')
},
content = function(file) {
if (input$DownloadVafPlotCheck == "png"){
png(file,width = input$vafcluster_width , height = input$vafcluster_height,res = 100)
}
else if (input$DownloadVafPlotCheck == "pdf"){
pdf(file,width = input$vafcluster_width/100 , height = input$vafcluster_height/100)
}
if("cluster.plot" %in% names(vafcluster())){
print(vafcluster()$cluster.plot[[getsample.vafcluster()]])
}else{
print(vafcluster()[[getpatient.vafcluster()]]$cluster.plot[[getsample.vafcluster()]])
}
dev.off()
},
contentType = paste('image/',input$DownloadVafPlotCheck,sep="")
)
output$vafcluster_table <- DT::renderDataTable({
if(!is.null(vafcluster())){
if("cluster.data" %in% names(vafcluster())){
t <- vafcluster()$cluster.data
}else{
t <- vafcluster()[[getpatient.vafcluster()]]$cluster.data
}
dt <- datatable(t, options = list(searching = TRUE, pageLength = 5, lengthMenu = c(5, 10, 15, 18), scrollX = TRUE, fixedColumns = TRUE, columnDefs=list(list(width="10em",targets="_all"))),rownames = FALSE, width=5)
return(dt)
}
})
output$vafcluster_table_ui <- renderUI({
if(!is.null(vafcluster())){
tagList(
div(style = "font-size:1.5em; font-weight:600; ", 'Cluster result'),
br(),
DT::dataTableOutput('vafcluster_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_vafcluster_table', 'Download')
)
),
br()
)
}
})
output$Download_vafcluster_table <- downloadHandler(
filename = "vafcluster.csv",
content = function(file){
if("cluster.data" %in% names(vafcluster())){
t <- vafcluster()$cluster.data
}else{
t <- vafcluster()[[getpatient.vafcluster()]]$cluster.data
}
write.csv(t,file,row.names = FALSE)
},
contentType = 'text/csv'
)
output$ccfauc_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("ccfauc_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "ccfauc_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
ccfauc <- eventReactive(input$submit_ccfauc,{
maf <- varsMaf$maf
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
if(is(maf, "MafList")){
maf_column <- colnames(getMafData(maf[[1]]) )
}else{
maf_column <- colnames(getMafData(maf) )
}
validate(
need("CCF" %in% maf_column, "Please upload ccf data in 'Input Data'!")
)
patientid <- input$ccfauc_patientid
withProgress(min = 0, max = 1, value = 0, {
setProgress(message = 'Processing: calculating AUC...')
validate(
need(!(is.null(maf)), "")
)
cc <- ccfAUC(maf,
patient.id = patientid,
min.ccf = as.numeric(input$ccfauc_minccf) ,
withinTumor = input$ccfauc_withintumor,
# use.adjVAF = input$ccfauc_useadjvaf,
use.tumorSampleLabel = input$ccfauc_usetumorsamplelabel)
incProgress(amount = 1)
setProgress(message = 'ccfAUC done!')
})
return(cc)
})
output$ccfauc.patientlist <- renderUI({
if(!is.null(ccfauc())){
if(!"CCF.density.plot" %in% names(ccfauc())){
cc <- ccfauc()
names <- names(cc)
tagList(
selectInput("auc.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
)
}
}
})
getpatient.ccfauc <- eventReactive(input$auc.pl,{
return(input$auc.pl)
})
ccfauc_width <- reactive({
return(input$ccfauc_width)
})
ccfauc_height <- reactive({
return(input$ccfauc_height)
})
output$ccfauc_plot <- renderPlot({
if(!is.null(ccfauc())){
if("CCF.density.plot" %in% names(ccfauc())){
return(ccfauc()$CCF.density.plot)
}else{
return(ccfauc()[[getpatient.ccfauc()]]$CCF.density.plot)
}
}
},
width = ccfauc_width,
height = ccfauc_height,
res = 100)
output$ccfauc_db_ui <- renderUI({
if(!is.null(ccfauc())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_ccfauc_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_ccfauc_plot', 'Download')
)
)
}
})
output$Download_ccfauc_plot <- downloadHandler(
filename = function() {
paste("ccfauc.",input$Download_ccfauc_plot_check, sep='')
},
content = function(file) {
if (input$Download_ccfauc_plot_check == "png"){
png(file,width = input$ccfauc_width , height = input$ccfauc_height,res = 100)
}
else if (input$Download_ccfauc_plot_check == "pdf"){
pdf(file,width = input$ccfauc_width/100 , height = input$ccfauc_height/100)
}
if("CCF.density.plot" %in% names(ccfauc())){
print(ccfauc()$CCF.density.plot)
}else{
print(ccfauc()[[getpatient.ccfauc()]]$CCF.density.plot)
}
dev.off()
},
contentType = paste('image/',input$Download_ccfauc_plot_check,sep="")
)
output$ccfauc_table <- DT::renderDataTable({
if(!is.null(ccfauc())){
if("CCF.density.plot" %in% names(ccfauc())){
t <- ccfauc()$AUC.value
}else{
t <- ccfauc()[[getpatient.ccfauc()]]$AUC.value
}
dt <- datatable(t,
options = list(searching = TRUE,
pageLength = 10,
scrollX = TRUE,
dom = "t",
fixedHeader = TRUE),
rownames = FALSE)
return(dt)
}
})
output$ccfauc_table_ui <- renderUI({
if(!is.null(ccfauc())){
tagList(
div(style = "font-size:1.5em; font-weight:600; ", 'AUC value'),
br(),
DT::dataTableOutput('ccfauc_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_ccfauc_table', 'Download')
)
),
br()
)
}
})
output$Download_ccfauc_table <- downloadHandler(
filename = "ccfauc.csv",
content = function(file){
if("CCF.density.plot" %in% names(ccfauc())){
t <- ccfauc()$AUC.value
}else{
t <- ccfauc()[[getpatient.ccfauc()]]$AUC.value
}
write.csv(t,file,row.names = FALSE)
},
contentType = 'text/csv'
)
## calfst sever
output$calfst_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("calfst_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "calfst_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
calfst <- eventReactive(input$submit_calfst,{
maf <- varsMaf$maf
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
withProgress(min = 0, max = 1, value = 0, {
setProgress(message = 'Processing: calculating Fst..')
# if(input$calfst_title == ""){
# title <- NULL
# }else{
# title <- input$calfst_title
# }
fst <- calFst(maf,
patient.id = input$calfst_patientid,
min.vaf = as.numeric(input$calfst_minvaf) ,
min.total.depth = as.numeric(input$calfst_mintotaldepth),
withinTumor =input$calfst_withinTumor,
use.adjVAF = input$calfst_useadjvaf,
# title = title,
use.circle = input$calfst_usecircle,
number.cex = as.numeric(input$calfst_numbercex),
number.col = input$calfst_numbercol,
use.tumorSampleLabel = input$calfst_usetumorsamplelabel)
incProgress(amount = 1)
setProgress(message = 'calFst done!')
})
return(fst)
})
output$calfst.patientlist <- renderUI({
if(!is.null(calfst())){
if(!"Fst.plot" %in% names(calfst())){
names <- names(calfst())
tagList(
selectInput("calfst.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
)
}
}
})
getpatient.calfst <- eventReactive(input$calfst.pl,{
return(input$calfst.pl)
})
calfst_width <- reactive({
return(input$calfst_width)
})
calfst_height <- reactive({
return(input$calfst_height)
})
output$calfst_plot <- renderPlot({
if(!is.null(calfst())){
if(!"Fst.plot" %in% names(calfst())){
return(calfst()[[getpatient.calfst()]]$Fst.plot)
}else{
return(calfst()$Fst.plot)
}
}
},
width = calfst_width,
height = calfst_height,
res = 100)
output$calfst_db_ui <- renderUI({
if(!is.null(calfst())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_calfst_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_calfst_plot', 'Download')
)
)
}
})
output$Download_calfst_plot <- downloadHandler(
filename = function() {
paste("calfst.",input$Download_calfst_plot_check, sep='')
},
content = function(file) {
if (input$Download_calfst_plot_check == "png"){
png(file,width = input$calfst_width , height = input$calfst_height,res = 100)
}
else if (input$Download_calfst_plot_check == "pdf"){
pdf(file,width = input$calfst_width/100 , height = input$calfst_height/100)
}
if(!"Fst.plot" %in% names(calfst())){
print(calfst()[[getpatient.calfst()]]$Fst.plot)
}else{
print(calfst()$Fst.plot)
}
dev.off()
},
contentType = paste('image/',input$Download_calfst_plot_check,sep="")
)
output$calfst_pair_table <- DT::renderDataTable({
if(!is.null(calfst())){
if(!"Fst.plot" %in% names(calfst())){
m <- calfst()[[getpatient.calfst()]]$Fst.pair
}else{
m <- calfst()$Fst.pair
}
rownames(m) <- colnames(m)
m <- as.data.frame(m)
colnames(m) <- rownames(m)
dt <- datatable(m,options = list(searching = TRUE,
pageLength = 10,
scrollX = TRUE,
dom = "t",
fixedHeader = TRUE),
rownames = TRUE)
return(dt)
}
})
output$calfst_pair_table_ui <- renderUI({
if(!is.null(calfst())){
tagList(
div(style = "font-size:1.5em; font-weight:600; ", 'Fst pair'),
br(),
DT::dataTableOutput('calfst_pair_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_calfst_pair_table', 'Download')
)
)
)
}
})
output$Download_calfst_pair_table <- downloadHandler(
filename = "calfst.csv",
content = function(file){
if(!"Fst.plot" %in% names(calfst())){
m <- calfst()[[getpatient.calfst()]]$Fst.pair
}else{
m <- calfst()$Fst.pair
}
rownames(m) <- colnames(m)
m <- as.data.frame(m)
colnames(m) <- rownames(m)
write.csv(m,file,row.names = TRUE)
},
contentType = 'text/csv'
)
## neidist sever
output$calneidist_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("calneidist_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "calneidist_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
calneidist <- eventReactive(input$submit_calneidist,{
maf <- varsMaf$maf
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
if(is(maf, "MafList")){
maf_column <- colnames(getMafData(maf[[1]]) )
}else{
maf_column <- colnames(getMafData(maf) )
}
validate(
need("CCF" %in% maf_column, "Please upload ccf data in 'Input Data'!")
)
withProgress(min = 0, max = 1, value = 0, {
setProgress(message = "Processing: calculating Nei's distance")
# if(input$calneidist_title==""){
# title <- NULL
# }else{
# title <- input$calneidist_title
# }
cc <- calNeiDist(maf,
patient.id = input$calneidist_patientid,
min.ccf = as.numeric(input$calneidist_minccf) ,
withinTumor = input$calneidist_withintumor,
use.adjVAF = input$calneidist_useadjvaf,
use.circle = input$calneidist_usecircle,
number.cex = as.numeric(input$calneidist_numbercex),
number.col = input$calneidist_numbercol,
use.tumorSampleLabel = input$calneidist_usetumorsamplelabel)
incProgress(amount = 1)
setProgress(message = 'calNeiDist done!')
})
return(cc)
})
output$calneidist.patientlist <- renderUI({
if(!is.null(calneidist())){
if(!"Nei.plot" %in% names(calneidist())){
names <- names(calneidist())
tagList(
selectInput("calneidist.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
)
}
}
})
getpatient.calneidist <- eventReactive(input$calneidist.pl,{
return(input$calneidist.pl)
})
calneidist_width <- reactive({
return(input$calneidist_width)
})
calneidist_height <- reactive({
return(input$calneidist_height)
})
output$calneidist_plot <- renderPlot({
if(!is.null(calneidist())){
if(!"Nei.plot" %in% names(calneidist())){
return(calneidist()[[getpatient.calneidist()]]$Nei.plot)
}else{
return(calneidist()$Nei.plot)
}
}
},
width = calneidist_width,
height = calneidist_height,
res = 100)
output$calneidist_db_ui <- renderUI({
if(!is.null(calneidist())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_calneidist_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_calneidist_plot', 'Download')
)
)
}
})
output$Download_calneidist_plot <- downloadHandler(
filename = function() {
paste("calneidist.",input$Download_calneidist_plot_check, sep='')
},
content = function(file) {
if (input$Download_calneidist_plot_check == "png"){
png(file,width = input$calneidist_width , height = input$calneidist_height,res = 100)
}
else if (input$Download_calneidist_plot_check == "pdf"){
pdf(file,width = input$calneidist_width/100 , height = input$calneidist_height/100)
}
if(!"Nei.plot" %in% names(calneidist())){
print(calneidist()[[getpatient.calneidist()]]$Nei.plot)
}else{
print(calneidist()$Nei.plot)
}
dev.off()
},
contentType = paste('image/',input$Download_calneidist_plot_check,sep="")
)
output$calneidist_pair_table <- DT::renderDataTable({
if(!is.null(calneidist())){
if(!"Nei.plot" %in% names(calneidist())){
m <- calneidist()[[getpatient.calneidist()]]$Nei.dist
}else{
m <- calneidist()$Nei.dist
}
rownames(m) <- colnames(m)
m <- as.data.frame(m)
colnames(m) <- rownames(m)
dt <- datatable(m,options = list(searching = TRUE,
pageLength = 10,
scrollX = TRUE,
dom = "t",
fixedHeader = TRUE),
rownames = TRUE)
return(dt)
}
})
output$calneidist_pair_table_ui <- renderUI({
if(!is.null(calneidist())){
tagList(
div(style = "font-size:1.5em; font-weight:600; ", "Nei's distance"),
br(),
DT::dataTableOutput('calneidist_pair_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_calneidist_pair_table', 'Download')
)
)
)
}
})
output$Download_calneidist_pair_table <- downloadHandler(
filename = "calneidist.csv",
content = function(file){
if(!"Nei.plot" %in% names(calneidist())){
m <- calneidist()[[getpatient.calneidist()]]$Nei.dist
}else{
m <- calneidist()$Nei.dist
}
rownames(m) <- colnames(m)
m <- as.data.frame(m)
colnames(m) <- rownames(m)
write.csv(m,file,row.names = TRUE)
},
contentType = 'text/csv'
)
## mutheatmap
output$mutheatmap_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("mutheatmap_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "mutheatmap_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
output$mutheatmap_parameters_ui <- renderUI({
if(!is.null(input$mutheatmap_genelist$datapath)){
tagList(
checkboxInput('mutheatmap_plotgenelist',
value = FALSE,
label = div(style = "font-size:1.5em; font-weight:600; padding-left:12px", 'Plot gene list'),
width = 500),
bsTooltip(id = "mutheatmap_plotgenelist",
title = "If TRUE, plot heatmap with genes on geneList when geneList is not NULL.Default FALSE.",
placement = "top",
trigger = "hover"),
# checkboxInput('mutheatmap_showgene',
# value = FALSE,
# label = div(style = "font-size:1.5em; font-weight:600; padding-left:12px", 'Show gene'),
# width = 500),
# bsTooltip(id = "mutheatmap_showgene",
# title = "Show the name of genes next to the heatmap.Default FALSE.",
# placement = "top",
# trigger = "hover"),
checkboxInput('mutheatmap_showgenelist',
value = TRUE,
label = div(style = "font-size:1.5em; font-weight:600; padding-left:12px", 'Show gene list'),
width = 500),
bsTooltip(id = "mutheatmap_showgenelist",
title = "Show the names of gene on the geneList.Default TRUE.",
placement = "top",
trigger = "hover"),
tags$table(
tags$tr(id = "inline",
width = "100%",
tags$td(width = "50%", div(style = "font-size:1.5em; font-weight:600; ", "Gene text size: ")),
tags$td(width = "50%", textInput(inputId = "mutheatmap_genetextsize", value = 9, label = NULL)))
),
bsTooltip(id = "mutheatmap_genetextsize",
title = "Size of gene name.Default 9.",
placement = "top",
trigger = "hover"),
br()
)
}
})
mutheatmap <- eventReactive(input$submit_mutheatmap,{
maf <- varsMaf$maf
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
if(!is.null(input$mutheatmap_genelist$datapath)){
genelist <- as.character(read.table(input$mutheatmap_genelist$datapath)$V1)
}else{
genelist <- NULL
}
withProgress(min = 0, max = 1, value = 0, {
setProgress(message = 'Processing: ploting heatmap of somatic mutations.')
if(is.null(input$mutheatmap_plotgenelist)){
plot.geneList <- FALSE
# show.gene <- FALSE
show.geneList <- FALSE
gene.text.size <- 9
}else{
plot.geneList <- input$mutheatmap_plotgenelist
# show.gene <- input$mutheatmap_showgene
show.geneList <- input$mutheatmap_showgenelist
gene.text.size <- as.numeric(input$mutheatmap_genetextsize)
}
hm <- mutHeatmap(maf,
patient.id = input$mutheatmap_patientid,
geneList = genelist,
min.vaf = as.numeric(input$mutheatmap_minvaf),
min.ccf = as.numeric(input$mutheatmap_minccf),
use.ccf = input$mutheatmap_useccf,
plot.geneList = plot.geneList,
# show.gene = show.gene,
show.geneList = show.geneList,
mut.threshold = as.numeric(input$mutheatmap_mutthreshold),
sample.text.size = as.numeric(input$mutheatmap_sampletextsize),
legend.title.size = as.numeric(input$mutheatmap_legendtitlesize),
gene.text.size = gene.text.size,
use.adjVAF = input$mutheatmap_useadjvaf,
classByTumor = input$mutheatmap_classByTumor,
use.tumorSampleLabel = input$mutheatmap_usetumorsamplelabel)
incProgress(amount = 1)
setProgress(message = 'mutHeatmap done!')
})
return(hm)
})
output$mutheatmap.patientlist <- renderUI({
if(!is.null(mutheatmap())){
if(!identical(c("gg","ggplot"),class(mutheatmap()))){
names <- names(mutheatmap())
tagList(
selectInput("mutheatmap.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
)
}
}
})
getpatient.mutheatmap <- eventReactive(input$mutheatmap.pl,{
return(input$mutheatmap.pl)
})
mutheatmap_width <- reactive({
return(input$mutheatmap_width)
})
mutheatmap_height <- reactive({
return(input$mutheatmap_height)
})
output$mutheatmap_plot <- renderPlot({
if(!is.null(mutheatmap())){
if(!identical(c("gg","ggplot"),class(mutheatmap()))){
return(mutheatmap()[[getpatient.mutheatmap()]])
}else{
return(mutheatmap())
}
}
},
width = mutheatmap_width,
height = mutheatmap_height,
res = 100)
output$mutheatmap_db_ui <- renderUI({
if(!is.null(mutheatmap())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_mutheatmap_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_mutheatmap_plot', 'Download')
)
)
}
})
output$Download_mutheatmap_plot <- downloadHandler(
filename = function() {
paste("mutheatmap.",input$Download_mutheatmap_plot_check, sep='')
},
content = function(file) {
if (input$Download_mutheatmap_plot_check == "png"){
png(file,width = input$mutheatmap_width , height = input$mutheatmap_height,res = 100)
}
else if (input$Download_mutheatmap_plot_check == "pdf"){
pdf(file,width = input$mutheatmap_width/100 , height = input$mutheatmap_height/100)
}
if(!identical(c("gg","ggplot"),class(mutheatmap()))){
print(mutheatmap()[[getpatient.mutheatmap()]])
}else{
print(mutheatmap())
}
dev.off()
},
contentType = paste('image/',input$Download_mutheatmap_plot_check,sep="")
)
## caljsi sever
output$caljsi_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("caljsi_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "caljsi_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
output$caljsi_pairbytumor_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList" & !is.null(input$caljsi_patientid)){
if(length(input$caljsi_patientid) == 1){
x <- maf[[which(names(maf) == input$caljsi_patientid) ]]@data
if(length(unique(x$Tumor_ID)) <= 1){
return(NULL)
}
}
}else if(class(maf) == "Maf"){
x <- maf@data
if(length(unique(x$Tumor_ID)) <= 1){
return(NULL)
}
}
tagList(
checkboxInput('caljsi_pairbytumor',
value = FALSE,
label = div(style = "font-size:1.5em; font-weight:600; padding-left:12px", 'Pair by tumor'),
width = 500),
bsTooltip(id = "caljsi_pairbytumor",
title = "calculate JSI by tumor",
placement = "top",
trigger = "hover")
)
}
})
caljsi <- eventReactive(input$submit_caljsi,{
maf <- varsMaf$maf
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
if(is(maf, "MafList")){
maf_column <- colnames(getMafData(maf[[1]]) )
}else{
maf_column <- colnames(getMafData(maf) )
}
validate(
need("CCF" %in% maf_column, "Please upload ccf data in 'Input Data'!")
)
withProgress(min = 0, max = 1, value = 0, {
setProgress(message = 'Processing: calculating Jaccard similarity index')
# if(input$caljsi_title==""){
# title <- NULL
# }else{
# title <- input$caljsi_title
# }
if(is.null(input$caljsi_pairbytumor)){
pairbytumor <- FALSE
}else{
pairbytumor <- input$caljsi_pairbytumor
}
cc <- calJSI(maf,
patient.id = input$caljsi_patientid,
min.vaf = as.numeric(input$caljsi_minccf) ,
pairByTumor = pairbytumor,
# title = title,
use.circle = input$caljsi_usecircle,
number.cex = as.numeric(input$caljsi_numbercex),
number.col = input$caljsi_numbercol,
plot = TRUE,
use.tumorSampleLabel = input$caljsi_usetumorsamplelabel)
incProgress(amount = 1)
setProgress(message = 'caljsi done!')
})
return(cc)
})
output$caljsi.patientlist <- renderUI({
if(!is.null(caljsi())){
if(!"JSI.plot" %in% (names(caljsi()))){
names <- names(caljsi())
tagList(
selectInput("caljsi.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
)
}
}
})
getpatient.caljsi <- eventReactive(input$caljsi.pl,{
return(input$caljsi.pl)
})
caljsi_width <- reactive({
return(input$caljsi_width)
})
caljsi_height <- reactive({
return(input$caljsi_height)
})
output$caljsi_plot <- renderPlot({
if(!is.null(caljsi())){
if(!"JSI.plot" %in% names(caljsi())){
return(caljsi()[[getpatient.caljsi()]]$JSI.plot)
}else{
return(caljsi()$JSI.plot)
}
}
},
width = caljsi_width,
height = caljsi_height,
res = 100)
output$caljsi_db_ui <- renderUI({
if(!is.null(caljsi())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_caljsi_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_caljsi_plot', 'Download')
)
)
}
})
output$Download_caljsi_plot <- downloadHandler(
filename = function() {
paste("caljsi.",input$Download_caljsi_plot_check, sep='')
},
content = function(file) {
if (input$Download_caljsi_plot_check == "png"){
png(file,width = input$caljsi_width , height = input$caljsi_height,res = 100)
}
else if (input$Download_caljsi_plot_check == "pdf"){
pdf(file,width = input$caljsi_width/100 , height = input$caljsi_height/100)
}
if(!"JSI.plot" %in% names(caljsi())){
print(caljsi()[[getpatient.caljsi()]]$JSI.plot)
}else{
print(caljsi()$JSI.plot)
}
dev.off()
},
contentType = paste('image/',input$Download_caljsi_plot_check,sep="")
)
output$caljsi_pair_table <- DT::renderDataTable({
if(!is.null(caljsi())){
if(!"JSI.plot" %in% names(caljsi())){
m <- caljsi()[[getpatient.caljsi()]]$JSI.pair
}else{
m <- caljsi()$JSI.pair
}
rownames(m) <- colnames(m)
m <- as.data.frame(m)
colnames(m) <- rownames(m)
dt <- datatable(m,options = list(searching = TRUE,
pageLength = 10,
scrollX = TRUE,
dom = "t",
fixedHeader = TRUE),
rownames = TRUE)
return(dt)
}
})
output$caljsi_pair_table_ui <- renderUI({
if(!is.null(caljsi())){
tagList(
div(style = "font-size:1.5em; font-weight:600; ", "JSI pair"),
br(),
DT::dataTableOutput('caljsi_pair_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_caljsi_pair_table', 'Download')
)
)
)
}
})
output$Download_caljsi_pair_table <- downloadHandler(
filename = "caljsi.csv",
content = function(file){
if(!"JSI.plot" %in% names(caljsi())){
m <- caljsi()[[getpatient.caljsi()]]$JSI.pair
}else{
m <- caljsi()$JSI.pair
}
rownames(m) <- colnames(m)
m <- as.data.frame(m)
colnames(m) <- rownames(m)
write.csv(m,file,row.names = TRUE)
},
contentType = 'text/csv'
)
## classifymut sever
classifymut <- eventReactive(input$submit_classifymut,{
withProgress(min = 0, max = 2, value = 0, {
setProgress(message = 'Mutational lanscape : Calculation in progress',
detail = 'This may take a while...')
maf <- varsMaf$maf
validate(
need(!(is.null(maf)), "")
)
cc <- classifyMut(maf)
incProgress(amount = 1)
setProgress(message = 'Mutational lanscape: Calculation done!')
})
return(cc)
})
output$classifymut_plot <- renderPlot({
if(!is.null(classifymut())){
return(classifymut()$mut.profile.plot)
}
},
width = 560,
height = 560,
res = 100)
output$classifymut_download_button_ui <- renderUI({
if(!is.null(classifymut())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_classifymut_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_classifymut_plot', 'Download')
)
)
}
})
output$classifymut_table <- DT::renderDataTable({
if(!is.null(classifymut())){
t <- classifymut()$mut.class
dt <- datatable(t,
options = list(searching = TRUE,
pageLength = 10,
scrollX = TRUE,
dom = "t",
fixedHeader = TRUE),
rownames = FALSE)
return(dt)
}
})
output$classifymut_table_ui <- renderUI({
if(!is.null(classifymut())){
tagList(
h4(strong('Mutation class')),
br(),
DT::dataTableOutput('classifymut_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_classifymut_table', 'Download')
)
)
)
}
})
output$plotmutprofile.patientlist <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("plotmutprofile_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list,
multiple = TRUE),
bsTooltip(id = "plotmutprofile_patientid",
title = 'Select the specific patients. Default: NULL, all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
plotmutprofile <- eventReactive(input$submit_plotmutprofile,{
maf <- varsMaf$maf
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
withProgress(min = 0, max = 1, value = 0, {
setProgress(message = 'Processing: drawing mutational profile')
if(is.null(input$plotmutprofile_patientid)){
patientid <- NULL
}else{
patientid <- input$plotmutprofile_patientid
}
if(input$plotmutprofile_usegenelist){
if(!is.null(input$plotmutprofile_genelist$datapath)){
genelist <- as.character(read.table(input$plotmutprofile_genelist$datapath)$V1)
}else{
genelist_file <- system.file("extdata", "IntOGen-DriverGenes_COREAD.tsv", package = "MesKit")
genelist <- as.character(read.table(genelist_file)$V1)
}
}else{
genelist <- NULL
}
p <- plotMutProfile(maf,
patient.id = patientid,
geneList = genelist,
classByTumor = input$plotmutprofile_classByTumor,
class = input$plotmutprofile_class,
topGenesCount = input$plotmutprofile_topGenesCount,
removeEmptyCols = input$plotmutprofile_remove_empty_columns,
removeEmptyRows = input$plotmutprofile_remove_empty_rows,
use.tumorSampleLabel = input$plotmutprofile_usetumorsamplelabel)
incProgress(amount = 1)
setProgress(message = 'plotMutProfile done!')
})
return(p)
})
getpatient.plotmutprofile <- eventReactive(input$plotmutprofile.pl,{
return(input$plotmutprofile.pl)
})
plotmutprofile_width <- reactive({
return(input$plotmutprofile_width)
})
plotmutprofile_height <- reactive({
return(input$plotmutprofile_height)
})
output$plotmutprofile_plot <- renderPlot({
if(!is.null(plotmutprofile())){
plotmutprofile()
}
},
width = plotmutprofile_width,
height = plotmutprofile_height,
res = 100)
output$plotmutprofile_download_button_ui <- renderUI({
if(as.numeric(input$submit_plotmutprofile) > 0){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_plotmutprofile_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_plotmutprofile_plot', 'Download')
)
)
}
})
output$Download_plotmutprofile_plot <- downloadHandler(
filename = function() {
paste("mutationprofile.",input$Download_plotmutprofile_plot_check, sep='')
},
content = function(file) {
if (input$Download_plotmutprofile_plot_check == "png"){
png(file,width = input$plotmutprofile_width , height = input$plotmutprofile_height,res = 100)
}
else if (input$Download_plotmutprofile_plot_check == "pdf"){
pdf(file,width = input$plotmutprofile_width/100 , height = input$plotmutprofile_height/100)
}
print(plotmutprofile())
dev.off()
},
contentType = paste('image/',input$Download_plotmutprofile_plot_check,sep="")
)
## plotCNA sever
observeEvent(input$iecontrol_seg,{
buttonValue$seg <- buttonValue$seg + 1
if(buttonValue$seg == 2){
buttonValue$seg <- 0
}
})
output$ie_seg <- renderUI({
if(buttonValue$seg == 1){
tagList(
h3(strong("The segment file")),
p("The segment file store information about copy number of each segment.",
style = "font-size:16px; font-weight:500;line-height:30px;"),
p(strong("Mandatory fields"),": Patient_ID, Tumor_Sample_Barcode, Chromosome, Start_Position, End_Position, CopyNumber, Tumor_Sample_Label(optional)",
style = "font-size:16px; font-weight:500;line-height:30px;"),
h3(strong("Example segment file:")),
DT::dataTableOutput("ied_seg"),
br()
)
}
})
output$ied_seg <- DT::renderDataTable({
if(buttonValue$seg == 1){
segFile <- system.file("extdata", "CRC_HZ.seg.txt", package = "MesKit")
seg <- suppressWarnings(data.table::fread(segFile, header=TRUE, sep="\t", stringsAsFactors = FALSE))
d <- datatable(seg, options = list(searching = TRUE, pageLength = 5, lengthMenu = c(5, 10, 15, 18), scrollX = TRUE, fixedColumns = TRUE, columnDefs=list(list(width="10em",targets="_all"))),rownames = FALSE, width=5)
return(d)
}
})
output$plotcna.patientlist <- renderUI({
if(!is.null(input$plotcna_segfile$datapath)){
seg <- readSegment(segFile = input$plotcna_segfile$datapath) %>% dplyr::bind_rows()
patient.list <- unique(seg$Patient_ID)
tagList(
selectizeInput("plotcna_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list,
multiple = TRUE),
bsTooltip(id = "plotcna_patientid",
title = 'Select the specific patients. Default: NULL, all patients are included',
placement = "top",
trigger = "hover"),
)
}else{
segFile <- system.file("extdata", "CRC_HZ.seg.txt", package = "MesKit")
seg <- readSegment(segFile = segFile) %>% dplyr::bind_rows()
patient.list <- unique(seg$Patient_ID)
tagList(
selectizeInput("plotcna_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list,
multiple = TRUE),
bsTooltip(id = "plotcna_patientid",
title = 'Select the specific patients. Default: NULL, all patients are included',
placement = "top",
trigger = "hover"),
)
}
})
output$plotcna_gistic_parameters_ui <- renderUI({
if(any(input$plotmutprofile_usegisticAmpGenes,
input$plotmutprofile_usegisticDelGenes,
input$plotmutprofile_usegisticAllLesions)){
tagList(
# checkboxInput('plotcna_showGISTICgene', label = div(style = "font-size:1.5em; font-weight:600; padding-left:15px", 'Show GISTIC gene'),value = FALSE,width = 400),
# bsTooltip(id = "plotcna_showGISTICgene",
# title = "Whether GISTIC gene in seg.Default FALSE.",
# placement = "top",
# trigger = "hover"),
tags$table(
tags$tr(id = "inline",
width = "100%",
tags$td(width = "50%", div(style = "font-size:1.5em; font-weight:600; ", "Gistic qvalue: ")),
tags$td(width = "50%", textInput(inputId = "plotcna_gisticqval", value = 0.25, label = NULL)))
),
bsTooltip(id = "plotcna_gisticqval",
title = "The threshold of gistic Q value. Default is 0.25",
placement = "top",
trigger = "hover")
)
}
})
plotcna <- eventReactive(input$submit_plotcna,{
# validate(
# need(!is.null(input$plotcna_segfile$datapath),
# "PlotCNA needs copy number information, upload segmentation file first"
# )
# )
withProgress(min = 0, max = 2, value = 0, {
if(is.null(input$plotcna_segfile$datapath)){
setProgress(message = 'Processing: drawing example CNA profile')
segFile <- system.file("extdata", "CRC_HZ.seg.txt", package = "MesKit")
}else{
setProgress(message = 'Processing: drawing CNA profile')
segFile <- input$plotcna_segfile$datapath
}
if(input$plotmutprofile_usegisticAmpGenes){
if(!is.null(input$plotcna_gisticAmpGenesFile$datapath)){
gisticAmpGenesFile <- input$plotcna_gisticAmpGenesFile$datapath
}else{
gisticAmpGenesFile <- system.file("extdata", "COREAD_amp_genes.conf_99.txt", package = "MesKit")
}
}else{
gisticAmpGenesFile <- NULL
}
if(input$plotmutprofile_usegisticDelGenes){
if(!is.null(input$plotcna_gisticDelGenesFile$datapath)){
gisticDelGenesFile <- input$plotcna_gisticDelGenesFile$datapath
}else{
gisticDelGenesFile <- system.file("extdata", "COREAD_del_genes.conf_99.txt", package = "MesKit")
}
}else{
gisticDelGenesFile <- NULL
}
if(input$plotmutprofile_usegisticAllLesions){
if(!is.null(input$plotcna_gisticAllLesionsFile$datapath)){
gisticAllLesionsFile <- input$plotcna_gisticAllLesionsFile$datapath
}else{
gisticAllLesionsFile <- system.file("extdata", "COREAD_all_lesions.conf_99.txt", package = "MesKit")
}
}else{
gisticAllLesionsFile <- NULL
}
seg <- readSegment(segFile = segFile,
gisticAllLesionsFile = gisticAllLesionsFile,
gisticAmpGenesFile = gisticAmpGenesFile,
gisticDelGenesFile = gisticDelGenesFile,
gistic.qval = as.numeric(input$plotcna_gisticqval) )
incProgress(amount = 1)
setProgress(message = 'Complete reading seg file!')
if(is.null(input$plotcna_patientid)){
patientid <- NULL
}else{
patientid <- input$plotcna_patientid
}
# if(is.null(input$plotcna_showGISTICgene)){
# show.GISTIC.gene <- FALSE
# }else{
# show.GISTIC.gene <- input$plotcna_showGISTICgene
# }
cna.plot <- plotCNA(seg,
patient.id = patientid,
refBuild = input$plotcna_refBuild,
sample.text.size = as.numeric(input$plotcna_sampletextsize) ,
sample.bar.height = as.numeric(input$plotcna_samplebarheight) ,
legend.text.size = as.numeric(input$plotcna_legendtextsize) ,
legend.title.size = as.numeric(input$plotcna_legendtitlesize) ,
chrom.bar.height = as.numeric(input$plotcna_chrombarheight),
showRownames = input$plotcna_showrownames,
removeEmptyChr = input$plotcna_removeempytchr,
use.tumorSampleLabel = input$plotcna_usetumorsamplelabel)
seg <- dplyr::bind_rows(seg)
if(!is.null(patientid)){
seg <- seg[Patient_ID %in% patientid]
}
incProgress(amount = 1)
setProgress(message = 'PlotCNA done!')
})
return(list(seg = seg, cna.plot = cna.plot))
})
# plotcna_value <- reactiveValues(v = plotcna())
plotcna_width <- reactive({
return(input$plotcna_width)
})
plotcna_height <- reactive({
return(input$plotcna_height)
})
output$plotcna_plot <- renderPlot({
if(!is.null(plotcna())){
return(plotcna()$cna.plot)
}
},
width = plotcna_width,
height = plotcna_height,
res = 100)
output$plotcna_download_button_ui <- renderUI({
if(!is.null(plotcna())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_plotcna_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_plotcna_plot', 'Download')
)
)
}
})
output$Download_plotcna_plot <- downloadHandler(
filename = function() {
paste("plotcna.",input$Download_plotcna_plot_check, sep='')
},
content = function(file) {
if (input$Download_plotcna_plot_check == "png"){
png(file,width = input$plotcna_width , height = input$plotcna_height,res = 100)
}
else if (input$Download_plotcna_plot_check == "pdf"){
pdf(file,width = input$plotcna_width/100 , height = input$plotcna_width/100)
}
print(plotcna()$cna.plot)
dev.off()
},
contentType = paste('image/',input$Download_plotcna_plot_check,sep="")
)
output$plotcna_table <- DT::renderDataTable({
if(!is.null(plotcna())){
t <- plotcna()$seg
d <- datatable(t, options = list(searching = TRUE, pageLength = 10, lengthMenu = c(5, 10, 15, 18), scrollX = TRUE, fixedColumns = TRUE, columnDefs=list(list(width="10em",targets="_all"))),rownames = FALSE, width=5)
return(d)
}
})
output$plotcna_table_ui <- renderUI({
if(!is.null(plotcna())){
tagList(
if(is.null(input$plotcna_segfile$datapath)){
div(style = "font-size:1.5em; font-weight:600; ", "Example segment(CRC_HZ)")
}else{
div(style = "font-size:1.5em; font-weight:600; ", "Segment")
},
br(),
DT::dataTableOutput('plotcna_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_plotcna_table', 'Download')
)
)
)
}
})
output$Download_plotcna_table <- downloadHandler(
filename = "plotcna.csv",
content = function(file){
data <- plotcna()$seg
write.csv(data,file,row.names = FALSE)
},
contentType = 'text/csv'
)
## testneutral sever
output$testneutral_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("testneutral_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "testneutral_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
testneutral <- eventReactive(input$submit_testneutral,{
maf <- varsMaf$maf
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
withProgress(min = 0, max = 1, value = 0, {
setProgress(message = 'testNeutral : Calculation in progress',
detail = 'This may take a while...')
t <- testNeutral(maf,
patient.id = input$testneutral_patientid,
min.vaf = as.numeric(input$testneutral_minvaf),
max.vaf = as.numeric(input$testneutral_maxvaf),
min.total.depth = as.numeric(input$testneutral_mintotaldepth),
withinTumor = input$testneutral_withintumor,
R2.threshold = as.numeric(input$testneutral_R2threshold),
min.mut.count = as.numeric(input$testneutral_minmutcount))
incProgress(amount = 1)
setProgress(message = 'testNeutral: Calculation done!')
})
validate(
need(!(is.na(t)), "No result is generated by testneutral.Try adjusting the parameters")
)
return(t)
})
output$testneutral.patientlist <- renderUI({
if(!is.null(testneutral())){
if(!"neutrality.metrics" %in% names(testneutral())){
patient.list <- testneutral()
names <- names(patient.list)
tagList(
selectInput("testneutral.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
)
}
}
})
getpatient.testneutral <- eventReactive(input$testneutral.pl,{
return(input$testneutral.pl)
})
output$testneutral.samplelist <- renderUI({
if(!is.null(testneutral())){
if(!"neutrality.metrics" %in% names(testneutral())){
patient <- input$testneutral.pl
sample.list <- testneutral()[[patient]]$model.fitting.plot
names <- names(sample.list)
tagList(
selectInput("testneutral.sl",
div(style = "font-size:1.5em; font-weight:600; ", 'Tumor sample barcode'),
choices = names, width = 600)
)
}else{
sample.list <- testneutral()$model.fitting.plot
names <- names(sample.list)
tagList(
selectInput("testneutral.sl",
div(style = "font-size:1.5em; font-weight:600; ", 'Tumor sample barcode'),
choices = names, width = 600)
)
}
}
})
getsample.testneutral <- eventReactive(input$testneutral.sl,{
return(input$testneutral.sl)
})
testneutral_width <- reactive({
return(input$testneutral_width)
})
testneutral_height <- reactive({
return(input$testneutral_height)
})
output$testneutral_plot <- renderPlot({
if(!is.null(testneutral())){
patient <- input$testneutral.pl
sample <- input$testneutral.sl
if(!"neutrality.metrics" %in% names(testneutral())){
return(testneutral()[[patient]]$model.fitting.plot[[sample]])
}else{
return(testneutral()$model.fitting.plot[[sample]])
}
}
},
width = testneutral_width,
height = testneutral_height,
res = 100)
output$testneutral_db_ui <- renderUI({
if(!is.null(testneutral())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_testneutral_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_testneutral_plot', 'Download')
)
)
}
})
output$Download_testneutral_plot <- downloadHandler(
filename = function() {
paste("testneutral.",input$Download_testneutral_plot_check, sep='')
},
content = function(file) {
if (input$Download_testneutral_plot_check == "png"){
png(file,width = input$testneutral_width , height = input$testneutral_height,res = 100)
}
else if (input$Download_testneutral_plot_check == "pdf"){
pdf(file,width = input$testneutral_width/100 , height = input$testneutral_height/100)
}
patient <- input$testneutral.pl
sample <- input$testneutral.sl
if(!"neutrality.metrics" %in% names(testneutral())){
print(testneutral()[[patient]]$model.fitting.plot[[sample]])
}else{
print(testneutral()$model.fitting.plot[[sample]])
}
dev.off()
},
contentType = paste('image/',input$Download_testneutral_plot_check,sep="")
)
output$testneutral_table <- DT::renderDataTable({
if(!is.null(testneutral())){
if(!"neutrality.metrics" %in% names(testneutral())){
t <- testneutral()[[getpatient.testneutral()]]$neutrality.metrics
}else{
t <- testneutral()$neutrality.metrics
}
dt <- datatable(t,
options = list(searching = TRUE,
pageLength = 10,
scrollX = TRUE,
dom = "t",
fixedHeader = TRUE),
rownames = FALSE)
return(dt)
}
})
output$testneutral_table_ui <- renderUI({
if(!is.null(testneutral())){
tagList(
div(style = "font-size:1.5em; font-weight:600; ", "Neutrality metrics"),
br(),
DT::dataTableOutput('testneutral_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_testneutral_table', 'Download')
)
)
)
}
})
output$Download_testneutral_table <- downloadHandler(
filename = "testneutral.csv",
content = function(file){
if(!"neutrality.metrics" %in% names(testneutral())){
t <- testneutral()[[getpatient.testneutral()]]$neutrality.metrics
}else{
t <- testneutral()$neutrality.metrics
}
write.csv(t,file,row.names = FALSE)
},
contentType = 'text/csv'
)
## compareccf sever
output$compareccf_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("compareccf_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "compareccf_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
output$compareccf_pairbytumor_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList" & !is.null(input$compareccf_patientid)){
if(length(input$compareccf_patientid) == 1){
x <- maf[[which(names(maf) == input$compareccf_patientid) ]]@data
if(length(unique(x$Tumor_ID)) <= 1){
return(NULL)
}
}
}else if(class(maf) == "Maf"){
x <- maf@data
if(length(unique(x$Tumor_ID)) <= 1){
return(NULL)
}
}
tagList(
checkboxInput('compareccf_pairbytumor',
value = FALSE,
label = div(style = "font-size:1.5em; font-weight:600; padding-left:12px", 'Pair by tumor'),
width = 500),
bsTooltip(id = "compareccf_pairbytumor",
title = "Pair by tumor types in each patients,default is FALSE.",
placement = "top",
trigger = "hover")
)
}
})
compareccf <- eventReactive(input$submit_compareccf, {
maf <- isolate(varsMaf$maf)
validate(
need(!(is.null(maf)), "Please upload data in 'Input Data'!")
)
if(is(maf, "MafList")){
maf_column <- colnames(getMafData(maf[[1]]) )
}else{
maf_column <- colnames(getMafData(maf) )
}
validate(
need("CCF" %in% maf_column, "Please upload ccf data in 'Input Data'!")
)
progress <- Progress$new(session, min=0, max=1)
on.exit(progress$close())
progress$set(message = 'Processing: comparing CCFs in paired samples')
if(is.null(input$compareccf_pairbytumor)){
pairbytumor <- FALSE
}else{
pairbytumor <- input$compareccf_pairbytumor
}
cc <- compareCCF(maf,
patient.id = input$compareccf_patientid,
min.ccf = input$compareccf_minccf,
pairByTumor = pairbytumor,
use.tumorSampleLabel = input$compareccf_usetumorsamplelabel)
progress$set(value = 1)
return(cc)
})
output$compareccf.patientlist <- renderUI({
if(!is.null(compareccf())){
if(class(compareccf()[[1]]) != "data.frame"){
patient.list <- compareccf()
names <- names(patient.list)
tagList(
selectInput("compareccf.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
)
}
}
})
getpatient.compareccf <- eventReactive(input$compareccf.pl,{
return(input$compareccf.pl)
})
output$compareccf.samplelist <- renderUI({
if(!is.null(compareccf())){
if(is.null(input$compareccf_pairbytumor)){
title <- "Sample pair"
}else{
if(input$compareccf_pairbytumor){
title <- "Tumor pair"
}else{
title <- "Sample pair"
}
}
if(class(compareccf()[[1]]) != "data.frame"){
patient <- input$compareccf.pl
sample.list <- compareccf()[[patient]]
names <- names(sample.list)
tagList(
selectInput("compareccf.sl",
div(style = "font-size:1.5em; font-weight:600; ", title),
choices = names, width = 600)
)
}else{
sample.list <- compareccf()
names <- names(sample.list)
tagList(
selectInput("compareccf.sl",
div(style = "font-size:1.5em; font-weight:600; ", title),
choices = names, width = 600)
)
}
}
})
getsample.compareccf <- eventReactive(input$compareccf.sl,{
return(input$compareccf.sl)
})
output$compareccf_table_ui <- renderUI({
if(!is.null(compareccf())){
tagList(
br(),
DT::dataTableOutput('compareccf_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_compareccf_table', 'Download')
)
)
)
}
})
output$compareccf_table <- DT::renderDataTable({
if(!is.null(compareccf())){
if(class(compareccf()[[1]]) != "data.frame"){
t <- compareccf()[[getpatient.compareccf()]][[getsample.compareccf()]]
}else{
t <- compareccf()[[getsample.compareccf()]]
}
dt <- datatable(t,rownames = FALSE)
return(dt)
}
})
output$Download_compareccf_table <- downloadHandler(
filename = "compareccf.csv",
content = function(file){
if(class(compareccf()[[1]]) != "data.frame"){
t <- compareccf()[[getpatient.compareccf()]][[getsample.compareccf()]]
}else{
t <- compareccf()[[getsample.compareccf()]]
}
write.csv(t,file,row.names = FALSE)
},
contentType = 'text/csv'
)
varsphyloTree <- reactiveValues()
observeEvent(input$submit_getphylotree,{
maf <- isolate(varsMaf$maf)
validate(
need(!is.null(maf), "Upload maf file in the section 'Input Data'")
)
withProgress(min = 0, max = 1, value = 0, {
## Rshiny: progress bar
setProgress(message = 'Generating ', detail = paste("phyloTree/phyloTreeList Class", sep=""))
phyloTree <- getPhyloTree(maf,
min.vaf = as.numeric(input$getphylotree_minvaf),
min.ccf = as.numeric(input$getphylotree_minccf),
bootstrap.rep.num = as.numeric(input$getphylotree_bootstraprepnum))
varsphyloTree[["phyloTree"]] <- phyloTree
incProgress(amount=1)
## Rshiny: progress bar
# setProgress(message = 'Input data: Generating ', detail = paste("phyloTree from MAF ",sep=""))
# varsMaf[['phyloTree']] <- phyloTree <- getPhyloTree(isolate(varsMaf$maf),method = input$method)
# incProgress(amount=1)
setProgress(message = paste("Input data: phyloTree/phyloTreeList Generation Done!", sep=""), detail = "")
Sys.sleep(1)
})
})
output$plotphylotree_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("plotphylotree_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "plotphylotree_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
phylotree <- eventReactive(input$submit_plotphylotree, {
maf <- isolate(varsMaf$maf)
validate(
need(!is.null(maf), "Upload maf file in the section 'Input Data'")
)
withProgress(min = 0, max = 2, value = 0,{
setProgress(message = "Generating phyloTree/phyloTreeList Class")
phyloTree <- getPhyloTree(maf,
patient.id = input$plotphylotree_patientid,
min.vaf = as.numeric(input$plotphylotree_getphylotree_minvaf),
min.ccf = as.numeric(input$plotphylotree_getphylotree_minccf),
method = input$plotphylotree_getphylotree_method,
bootstrap.rep.num = as.numeric(input$plotphylotree_getphylotree_bootstraprepnum))
incProgress(amount=1)
setProgress(message = 'Processing: visualize phylogenetic tree')
if(input$plotphylotree_branchcol == "NULL"){
branchCol <- NULL
}else{
branchCol <- input$plotphylotree_branchcol
}
scale_bar_x <- NULL
scale_bar_y <- NULL
if(input$plotphylotree_show_scale_bar){
if(input$plotphylotree_scale_bar_x != ""){
scale_bar_x <- as.numeric(input$plotphylotree_scale_bar_x)
}else{
scale_bar_x <- NULL
}
if(input$plotphylotree_scale_bar_y != ""){
scale_bar_y <- as.numeric(input$plotphylotree_scale_bar_y)
}else{
scale_bar_y <- NULL
}
}
plot.list <- plotPhyloTree(phyloTree,
branchCol = branchCol,
show.bootstrap = input$plotphylotree_showbootstrap,
min.ratio = as.numeric(input$plotphylotree_minratio) ,
signaturesRef = input$plotphylotree_signatureref,
min.mut.count = as.numeric(input$plotphylotree_minmutcount),
use.tumorSampleLabel = input$plotphylotree_usetumorsamplelabel,
show.scale.bar = input$plotphylotree_show_scale_bar,
scale.bar.x = scale_bar_x,
scale.bar.y = scale_bar_y)
incProgress(amount=1)
setProgress(message = paste("Plot phylotree done!", sep=""), detail = "")
Sys.sleep(1)
})
return(plot.list)
})
output$phylotree.patientlist <- renderUI({
if(!is.null(phylotree())){
if(!identical(c("gg","ggplot"),class(phylotree()))){
names <- names(phylotree())
selectInput("phylotree.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
}
}
})
getpatient.phylotree <- eventReactive(input$phylotree.pl,{
return(input$phylotree.pl)
})
plotphylotree_width <- reactive({
return(input$plotphylotree_width)
})
plotphylotree_height <- reactive({
return(input$plotphylotree_height)
})
output$phylotree_plot <- renderPlot({
if(!is.null(phylotree())){
if(!identical(c("gg","ggplot"),class(phylotree()))){
return(phylotree()[[getpatient.phylotree()]])
}else{
return(phylotree())
}
}
},
width = plotphylotree_width,
height = plotphylotree_height,
res = 100
)
output$phylotree_downloadbutton_ui<- renderUI({
if(!is.null(phylotree())){
br()
br()
fluidRow(
column(
width = 2,
radioButtons('Download_phylotree_check', label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"), inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_phylotree', 'Download')
)
)
}
})
output$Download_phylotree <- downloadHandler(
filename = function() {
paste("phylotree.",input$Download_phylotree_check, sep='')
},
content = function(file) {
if (input$Download_phylotree_check == "png"){
png(file,width = input$plotphylotree_width , height = input$plotphylotree_height,res = 100)
}
else if (input$Download_phylotree_check == "pdf"){
pdf(file,width = input$plotphylotree_width/100 , height = input$plotphylotree_height/100)
}
if(!identical(c("gg","ggplot"),class(phylotree()))){
print(phylotree()[[getpatient.phylotree()]])
}else{
print(phylotree())
}
dev.off()
},
contentType = paste('image/',input$Download_phylotree_check,sep="")
)
comparetree <- eventReactive(input$submit_comparetree, {
maf <- isolate(varsMaf$maf)
validate(
need(!is.null(maf), "Upload maf file in the section 'Input Data'")
)
withProgress(min = 0, max = 1, value = 0,{
setProgress(message = 'Processing: compare phylogenetic trees')
phylotree1 <- getPhyloTree(maf, patient.id = input$comparetree_patientid,
method = input$comparetree_getphylotree_method1,
min.ccf = as.numeric(input$comparetree_getphylotree_minccf) ,
min.vaf = as.numeric(input$comparetree_getphylotree_minvaf) ,
bootstrap.rep.num = as.numeric(input$comparetree_getphylotree_bootstraprepnum))
phylotree2 <- getPhyloTree(maf, patient.id = input$comparetree_patientid,
method = input$comparetree_getphylotree_method2,
min.ccf = as.numeric(input$comparetree_getphylotree_minccf) ,
min.vaf = as.numeric(input$comparetree_getphylotree_minvaf) ,
bootstrap.rep.num = as.numeric(input$comparetree_getphylotree_bootstraprepnum) )
ct <- compareTree(phylotree1, phylotree2,
# common.col = input$comparetree_commoncol,
min.ratio = as.numeric(input$comparetree_minratio) ,
show.bootstrap = input$comparetree_showbootstrap,
plot = TRUE,
use.tumorSampleLabel = input$comparetree_usetumorsamplelabel)
incProgress(amount=1)
setProgress(message = paste("Comparetree done!", sep=""), detail = "")
Sys.sleep(1)
})
return(ct)
})
output$comparetree.patientlist <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
}else{
patient.list <- unique(maf@data$Patient_ID)
}
tagList(
selectInput("comparetree_patientid",
label = div(style = "font-size:1.6em; font-weight:600; ", "Select patients"),
choices = patient.list),
bsTooltip(id = "comparetree_patientid",
title = 'Select the specific patient',
placement = "top",
trigger = "hover"),
)
}
})
comparetree_width <- reactive({
return(input$comparetree_width)
})
comparetree_height <- reactive({
return(input$comparetree_height)
})
output$comparetree_plot <- renderPlot({
if(!is.null(comparetree())){
return(comparetree()$compare.plot)
}
},
width = comparetree_width,
height = comparetree_height,
res = 100
)
output$comparetree_dist <- renderPrint({
if(!is.null(comparetree())){
return(comparetree()$compare.dist)
}
})
output$comparetree_db_ui<- renderUI({
if(!is.null(comparetree())){
br()
br()
fluidRow(
column(
width = 2,
radioButtons('Download_comparetree_check', label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"), inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_comparetree', 'Download')
)
)
}
})
output$Download_comparetree <- downloadHandler(
filename = function() {
paste("comparetree.",input$Download_comparetree_check, sep='')
},
content = function(file) {
if (input$Download_comparetree_check == "png"){
png(file,width = input$comparetree_width , height = input$comparetree_height,res = 100)
}
else if (input$Download_comparetree_check == "pdf"){
pdf(file,width = input$comparetree_width/100 , height = input$comparetree_height/100)
}
print(comparetree()$compare.plot)
dev.off()
},
contentType = paste('image/',input$Download_comparetree_check,sep="")
)
output$treemutsig_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("treemutsig_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "treemutsig_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
treemutsig <- eventReactive(input$submit_treemutsig, {
maf <- isolate(varsMaf$maf)
validate(
need(!is.null(maf), "Upload maf file in the section 'Input Data'")
)
withProgress(min = 0, max = 4, value = 0,{
setProgress(message = 'Generating phyloTree/phyloTreeList Class')
phyloTree <- getPhyloTree(maf,
patient.id = input$treemutsig_patientid,
method = input$treemutsig_getphylotree_method,
min.vaf = as.numeric(input$treemutsig_getphylotree_minvaf),
min.ccf = as.numeric(input$treemutsig_getphylotree_minccf),
bootstrap.rep.num = as.numeric(input$treemutsig_getphylotree_bootstraprepnum))
incProgress(amount=1)
setProgress(message = 'Processing: decomposing matrix of somatic SNVs')
tm <- triMatrix(phyloTree,
# withinTumor = input$treemutsig_withintumor,
level = input$treemutsig_level)
incProgress(amount = 1)
setProgress(message = 'Processing: fitSignatrues')
fs <- fitSignatures(tm, signaturesRef = input$treemutsig_signatureref,
min.mut.count = as.numeric(input$treemutsig_minmutcount) ,
signature.cutoff = as.numeric(input$treemutsig_signaturecutoff))
incProgress(amount = 1)
setProgress(message = 'Processing: reconstructing mutational profiles with known signatures')
if(input$treemutsig_mode == 'NULL'){
mode <- NULL
}else{
mode <- input$treemutsig_mode
}
pms <- plotMutSigProfile(fs, mode = mode,
use.tumorSampleLabel = input$treemutsig_usetumorsamplelabel)
incProgress(amount = 1)
setProgress(message = 'plotMutSigProfile done!')
Sys.sleep(1)
return(pms)
})
})
output$treemutsig.patientlist <- renderUI({
if(!is.null(treemutsig())){
if(is(treemutsig()[[1]],"list")){
plot.list <- treemutsig()
names <- names(plot.list)
selectInput("treemutsig.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = names, width = 600)
}
}
})
getpatient.treemutsig <- eventReactive(input$treemutsig.pl,{
return(input$treemutsig.pl)
})
output$treemutsig.samplelist <- renderUI({
if(!is.null(treemutsig())){
if(is(treemutsig()[[1]],"list")){
patient <- input$treemutsig.pl
sample.list <- treemutsig()[[patient]]
names <- names(sample.list)
tagList(
selectInput("treemutsig.sl",
div(style = "font-size:1.5em; font-weight:600; ", 'Select branch'),
choices = names, width = 600)
)
}else{
sample.list <- treemutsig()
names <- names(sample.list)
tagList(
selectInput("treemutsig.sl",
div(style = "font-size:1.5em; font-weight:600; ", 'Select branch'),
choices = names, width = 600)
)
}
}
})
getsample.treemutsig <- eventReactive(input$treemutsig.sl,{
return(input$treemutsig.sl)
})
treemutsig_width <- reactive({
return(input$treemutsig_width)
})
treemutsig_height <- reactive({
return(input$treemutsig_height)
})
output$treemutsig_plot <- renderPlot({
if(!is.null(treemutsig())){
if(is(treemutsig()[[1]],"list")){
return(treemutsig()[[getpatient.treemutsig()]][[getsample.treemutsig()]])
}else{
return(treemutsig()[[getsample.treemutsig()]])
}
}
},
width = treemutsig_width,
height = treemutsig_height,
res = 100
)
output$treemutsig_download_button_ui <- renderUI({
if(!is.null(treemutsig())){
fluidRow(
column(
width = 2,
radioButtons(inputId = 'Download_treemutsig_plot_check',
label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),
choiceValues = c("png", "pdf"),
inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_treemutsig_plot', 'Download')
)
)
}
})
output$Download_treemutsig_plot <- downloadHandler(
filename = function() {
paste("treemutsig.",input$Download_treemutsig_plot_check, sep='')
},
content = function(file) {
if (input$Download_treemutsig_plot_check == "png"){
png(file,width = input$treemutsig_width , height = input$treemutsig_height,res = 100)
}
else if (input$Download_treemutsig_plot_check == "pdf"){
pdf(file,width = input$treemutsig_width/100 , height = input$treemutsig_height/100)
}
if(is(treemutsig()[[1]],"list")){
print(treemutsig()[[getpatient.treemutsig()]][[getsample.treemutsig()]])
}else{
print(treemutsig()[[getsample.treemutsig()]])
}
dev.off()
},
contentType = paste('image/',input$Download_treemutsig_plot_check,sep="")
)
output$treemutsig_table_ui <- renderUI({
if(!is.null(treemutsig())){
tagList(
div(style = "font-size:1.5em; font-weight:600; ", "Signature summary"),
br(),
DT::dataTableOutput('treemutsig_table'),
br(),
fluidRow(
column(
width = 3,
downloadBttn('Download_treemutsig_table', 'Download')
)
),
br()
)
}
})
output$muttrunkbranch_patientid_ui <- renderUI({
maf <- varsMaf$maf
if(!is.null(maf)){
if(class(maf) == "MafList"){
patient.list <- names(maf)
tagList(
selectizeInput("muttrunkbranch_patientid",
label = div(style = "font-size:1.5em; font-weight:600; ", "Select patients"),
choices = patient.list,
select = patient.list[1],
multiple = TRUE),
bsTooltip(id = "muttrunkbranch_patientid",
title = 'Select the specific patients. Default: all patients are included',
placement = "top",
trigger = "hover"),
)
}
}
})
muttrunkbranch <- eventReactive(input$submit_muttrunkbranch, {
maf <- isolate(varsMaf$maf)
validate(
need(!is.null(maf), "Upload maf file in the section 'Input Data'")
)
withProgress(min = 0, max = 2, value = 0,{
setProgress(message = 'Generating phyloTree/phyloTreeList Class')
phyloTree <- getPhyloTree(maf,
patient.id = input$muttrunkbranch_patientid,
method = input$muttrunkbranch_getphylotree_method,
min.vaf = as.numeric(input$muttrunkbranch_getphylotree_minvaf),
min.ccf = as.numeric(input$muttrunkbranch_getphylotree_minccf),
bootstrap.rep.num = as.numeric(input$muttrunkbranch_getphylotree_bootstraprepnum))
incProgress(amount = 1)
setProgress(message = 'mutTrunkBranch : Calculation in progress')
mtb <- mutTrunkBranch(phyloTree, CT = input$muttrunkbranch_ct,
pvalue = as.numeric(input$muttrunkbranch_pvalue))
incProgress(amount = 1)
setProgress(message = 'mutTrunkBranch done!')
return(mtb)
})
})
getpatient.muttrunkbranch <- eventReactive(input$muttrunkbranch.pl,{
return(input$muttrunkbranch.pl)
})
output$muttrunkbranch.patientlist <- renderUI({
if(!is.null(muttrunkbranch())){
if(!"mutTrunkBranch.plot" %in% names(muttrunkbranch()) ){
x <- muttrunkbranch()
patient.list <- names(x)
selectInput("muttrunkbranch.pl",
div(style = "font-size:1.5em; font-weight:600; ", 'Patient'),
choices = patient.list, width = 600)
}
}
})
muttrunkbranch_width <- reactive({
return(input$muttrunkbranch_width)
})
muttrunkbranch_height <- reactive({
return(input$muttrunkbranch_height)
})
output$muttrunkbranch_plot <- renderPlot({
if(!is.null(muttrunkbranch())){
if(!"mutTrunkBranch.plot" %in% names(muttrunkbranch())){
p <- muttrunkbranch()[[getpatient.muttrunkbranch()]]$mutTrunkBranch.plot
}else{
p <- muttrunkbranch()$mutTrunkBranch.plot
}
return(p)
}
},
width = muttrunkbranch_width,
height = muttrunkbranch_height,
res = 100
)
output$muttrunkbranch_download_button_ui <- renderUI({
if(!is.null(muttrunkbranch())){
fluidRow(
column(
width = 2,
radioButtons('Download_muttrunkbranch_plot_check', label = div(style = "font-size:18px; font-weight: bold; ", 'Save type as:'),
choiceNames = list(
tags$span(style = "font-size:14.5px; font-weight:400; ", "png"),
tags$span(style = "font-size:14.5px; font-weight:400; ", "pdf")
),choiceValues = c("png", "pdf"), inline = TRUE)
),
column(
width = 3,
downloadBttn('Download_muttrunkbranch_plot', 'Download')
)
)
}
})
output$Download_muttrunkbranch_plot <- downloadHandler(
filename = function() {
paste("muttrunkbranch.",input$Download_muttrunkbranch_plot_check, sep='')
},
content = function(file) {
if (input$Download_muttrunkbranch_plot_check == "png"){
png(file,width = input$muttrunkbranch_width , height = input$muttrunkbranch_height,res = 100)
}
else if (input$Download_muttrunkbranch_plot_check == "pdf"){
pdf(file,width = input$muttrunkbranch_width/100 , height = input$muttrunkbranch_height/100)
}
if(!"mutTrunkBranch.plot" %in% names(muttrunkbranch())){
p <- muttrunkbranch()[[getpatient.muttrunkbranch()]]$mutTrunkBranch.plot
}else{
p <- muttrunkbranch()$mutTrunkBranch.plot
}
print(p)
dev.off()
},
contentType = paste('image/',input$Download_muttrunkbranch_plot_check,sep="")
)
output$muttrunkbranch_table_ui <- renderUI({
if(!is.null(muttrunkbranch())){
tagList(
div(style = "font-size:1.5em; font-weight:600; ", "Summary"),
br(),
DT::dataTableOutput('muttrunkbranch_table'),
fluidRow(
column(
width = 3,
downloadBttn('Download_muttrunkbranch_table', 'Download')
)
)
)
}
})
output$muttrunkbranch_table <- DT::renderDataTable({
if(!is.null(muttrunkbranch())){
if(!"mutTrunkBranch.plot" %in% names(muttrunkbranch())){
t <- muttrunkbranch()[[getpatient.muttrunkbranch()]]$mutTrunkBranch.res
}else{
t <- muttrunkbranch()$mutTrunkBranch.res
}
dt <- datatable(t, options = list(searching = TRUE, pageLength = 10, lengthMenu = c(5, 10, 15, 18), scrollX = TRUE, fixedColumns = TRUE, columnDefs=list(list(width="10em",targets="_all"))),rownames = FALSE, width=5)
return(dt)
}
})
output$Download_muttrunkbranch_table <- downloadHandler(
filename = "muttrunkbranch.csv",
content = function(file){
if(!"mutTrunkBranch.plot" %in% names(muttrunkbranch())){
t <- muttrunkbranch()[[getpatient.muttrunkbranch()]]$mutTrunkBranch.res
}else{
t <- muttrunkbranch()$mutTrunkBranch.res
}
write.csv(t, file, row.names = FALSE)
},
contentType = 'text/csv'
)
})
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