server_output_meta <- function(input, output, server_env) {
output$groupSelector_5 <- renderUI({
if (MEDSET_FLAG) {
results <- server_env$dataset()
gr_lists <- results@parameters$cg_subsets
GROUPS <- 1:length(gr_lists)
if (is.null(names(gr_lists))) {
names(GROUPS) <- sapply(gr_lists, paste, collapse = "_")
} else{
names(GROUPS) <- names(gr_lists)
}
selectInput('cg_group_5', 'Technical CpG subset:', GROUPS,selected=server_env$Selected$CG)
}
})
output$Kselector_5 <- renderUI({
Ks <- server_env$dataset()@parameters$Ks
selectInput('K_5', 'Number of LMCs (k)', Ks,selected=server_env$Selected$K)
})
output$lambdaSelector_5 <- renderUI({
if (MEDSET_FLAG) {
LAMBDAS <- server_env$dataset()@parameters$lambdas
LAMBDA.IDS <- 1:length(server_env$dataset()@parameters$lambdas)
names(LAMBDA.IDS) <- as.character(LAMBDAS)
selectInput('lambda_5', 'Lambda value', LAMBDA.IDS, selected=server_env$Selected$LAMBDA)
}
})
output$compareRunSelector <- renderUI({
runs <- names(server_env$getRuns())
names(runs) <- paste(seq_len(length(runs)), runs, sep = ". ")
selectInput(
'analysisrun_ref',
'',
runs,
selectize = TRUE,
width = "750px",
selected = 1
)
})
output$Kselector_ref <- renderUI({
Ks <- server_env$dataset_ref()@parameters$Ks
selectInput('K_ref', 'Number of LMCs (reference)', Ks, selectize = TRUE)
})
output$lambdaSelector_ref <- renderUI({
LAMBDAS <- server_env$dataset_ref()@parameters$lambdas
LAMBDA.IDS <- 1:length(dataset_ref()@parameters$lambdas)
names(LAMBDA.IDS) <- as.character(LAMBDAS)
selectInput('lambda_ref', 'Lambda value (reference)', LAMBDA.IDS)
})
output$topSDcgsSelectorCompare <- renderUI({
gr <- as.integer(input$cg_group_5)
ind <- server_env$getCGsubset()
ind_ref <- server_env$getCGsubsetRef()
ind_common <- intersect(ind, ind_ref)
sliderInput(
'topSDcpgsCompare',
'Select top SD cgs',
min = 100,
max = length(ind),
value = length(ind),
step = 100,
round = 0
)
})
output$analysisTokensInput <- renderUI({
dn <- "Target"
dn_ref <- "Reference"
list(
textInput("analysisToken", "Analysis token:", dn),
textInput("refAnalysisToken", "Reference analysis token:", dn_ref)
)
})
output$dmCGComponentSelector <- renderUI({
if(!is.null(input$K_5)){
cmp_choices = as.list(as.character(1:as.integer(input$K_5)))
names(cmp_choices) = c(as.character(1:as.integer(input$K_5)))
list(
selectizeInput(
"componentGroup1",
"Select LMCs:",
choices = cmp_choices,
selected = 1,
multiple = TRUE
),
selectizeInput(
"componentGroup2",
"Select LMCs to compare:",
choices = cmp_choices,
selected = 2,
multiple = TRUE
)
)
}
})
output$diffTabT<-renderUI({
direct<-c("hypomethylated","hypermethylated")
if (input$analysisType=="Enrichments"){
direct<-c(direct, "differential")
}
selectInput("diffTableType", "Direction:", direct, selected=2)
})
output$region_selector<- renderUI({
region_t=c("genes", "promoters")
if (input$diffOutputType == "GO Enrichments" && !is.null(input$assembly) && input$assembly=="hg38"){
region_t=c(region_t, "gencode22genes", "gencode22promoters")
}
if(input$diffOutputType == "LOLA Enrichments"){
region_t=c(region_t, "tilling", "tiling200bp", "tiling500bp", "tiling1kb","tiling10kb", "cpgislands")
if((!is.null(input$assembly)) && (input$assembly=="hg38" || input$assembly=="hg19")){
region_t=c(region_t,"ensembleRegBuildBPall")
}
}
selectInput("region_type", "Region Type:", choices=region_t, selected=1)
})
output$assemblySelector <- renderUI({
result<-server_env$dataset()
if(!is.null(result@parameters$ASSEMBLY)){
assembly<-result@parameters$ASSEMBLY
}
assembly<-"hg38"
assemblies<-list()
assemblies[["hg38"]]<-1
assemblies[["hg19"]]<-2
assemblies[["mm10"]]<-3
selectInput("assembly", "Genome Assembly:", choices=names(assemblies), selected=assemblies[[assembly]])
})
output$lmcgoSelector<-renderUI({
server_env$getGOEnrichmenttable()
server_env$lmcgoSelect()
})
output$lmclolaSelector<-renderUI({
server_env$getLOLAEnrichmenttable()
server_env$lmclolaSelect()
})
output$analyType<-renderUI({
atype<-c()
if(!is.null(medecom_ref_object)){
atype<-c(atype, "compare LMCs")
}
atype<-c(atype, "differential methylation", "Enrichments")
if(PHENO_DATA_FLAG){
atype<-c(atype, "Trait Association")
}
selectInput("analysisType", "Analysis:", atype, selected=1)
})
output$targetVariableSelector <- renderUI({
pheno <- server_env$getPhenoData()
selectInput(
"phenoTarget",
"Select target trait:",
choices = colnames(pheno),
selected = 1,
multiple = FALSE
)
})
output$adjustmentVariableSelector <- renderUI({
pheno <- server_env$getPhenoData()
if ("phenoTarget" %in% names(input)) {
list(
selectizeInput(
"phenoAdjust",
"Select trait(s) to adjust for:",
choices = setdiff(colnames(pheno), input$phenoTarget),
selected = 1,
multiple = TRUE
),
if (!is.numeric(pheno[[input$phenoTarget]]))
selectInput(
"zeroLevel",
"Zero level:",
choices = unique(pheno[[input$phenoTarget]]),
selected = 1,
multiple = FALSE
)
else
NULL
)
} else{
list(NULL)
}
})
output$lmcs_selector<-renderUI({
Ks <- 1:server_env$Selected$K
list(
selectInput("lmcs_6_1", "Select LMC to compare", Ks, multiple = F, selected=Ks[[1]]),
selectInput("lmcs_6_2", "Select LMC to compare", Ks, multiple = F, selected=Ks[[2]])
)
})
output$lmcs_selector_go<-renderUI({
Ks <- 1:server_env$Selected$K
list(
selectInput("lmcs_6_1", "Select LMC to compare", Ks, multiple = F, selected=Ks[[1]]),
selectInput("lmcs_6_2", "Select LMC to compare", Ks, multiple = F, selected=Ks[[2]])
)
})
}
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