/
server.R
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server.R
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library(shiny)
library(shinyFiles)
#library(gdata)
library(SCPattern)
library(EBSeq)
# Define server logic for slider examples
shinyServer(function(input, output, session) {
volumes <- c('home'="~")
shinyDirChoose(input, 'Outdir', roots=volumes, session=session, restrictions=system.file(package='base'))
output$Dir <- renderPrint({parseDirPath(volumes, input$Outdir)})
In <- reactive({
print(input$Outdir)
outdir <- paste0("~/",input$Outdir[[1]][[2]],"/")
print(outdir)
the.file <- input$filename$name
if(is.null(the.file))stop("Please upload data")
Sep=strsplit(the.file,split="\\.")[[1]]
#if(Sep[length(Sep)]%in%c("xls"))a1=read.xls(input$filename$datapath,stringsAsFactors=F,header=TRUE, row.names=1)
if(Sep[length(Sep)]=="csv")a1=read.csv(input$filename$datapath,stringsAsFactors=F,header=TRUE, row.names=1)
#if(Sep[length(Sep)]%in%c("txt","tab"))a1=read.table(input$filename$datapath,stringsAsFactors=F,header=TRUE, row.names=1)
if(Sep[length(Sep)]!="csv")a1=read.table(input$filename$datapath,stringsAsFactors=F,header=TRUE, row.names=1)
Data=data.matrix(a1)
Group.file <- input$ConditionVector$name
if(is.null(Group.file))stop("Please upload condition file")
#GroupB=FALSE
Group.Sep=strsplit(Group.file,split="\\.")[[1]]
if(Group.Sep[length(Group.Sep)]%in%c("xls"))
GroupVIn=read.xls(input$ConditionVector$datapath,stringsAsFactors=F,header=F)
if(Group.Sep[length(Group.Sep)]=="csv")
GroupVIn=read.csv(input$ConditionVector$datapath,stringsAsFactors=F,header=F)
if(Group.Sep[length(Group.Sep)]%in%c("txt","tab"))
GroupVIn=read.table(input$ConditionVector$datapath,stringsAsFactors=F,header=F, sep="\t")
GroupV=GroupVIn[[1]]
if(length(GroupV)!=ncol(Data)) stop("length of the condition vector is not the same as number of cells!")
# Compose data frame
#input$filename$name
List <- list(
Input=the.file,
GroupFile=Group.file,
iters=input$iters, Circular=ifelse(input$Circular=="1", TRUE, FALSE),
Cond=factor(GroupV, levels=unique(GroupV)),# follow the order they appeared
test=input$test_buttons,
test_details=switch(input$test_buttons,"1"="DE vs. EE (undirectional)",
"2"="Up vs. Down vs. EE", "3"="Up vs. Down vs. EE vs. Both direction",
"4"="Up vs. Down"),
RMTF=ifelse(input$RM_buttons=="1",TRUE,FALSE),
Dropupper=input$Dropupper,
#PPcut=input$PPcut,
LODNum=input$LOD,
Dir=outdir,
exExpF = paste0(outdir,input$exNormFileName,".csv"),
exOEF = paste0(outdir,input$exListFileName,".csv"),
exPVF = paste0(outdir,input$exPVFileName,".csv"),
exPVFraw = paste0(outdir,input$exPVFileName),
PlotTF = ifelse(input$Plot_buttons=="1",TRUE,FALSE),
whetherLog = ifelse(input$log_whether=="1",FALSE,TRUE),
PlotType = input$Plot_type,
PlotF = paste0(outdir,input$exPlotFileName,".pdf"),
PlotN = input$PlotNum
)
# normalization and LOD
if(List$test=="1"){
Directional <- FALSE
NumPat <- 2
}
else{
Directional <- TRUE
NumPat <- switch(List$test, "2"=3, "3"=4, "4"=2)
}
Sizes <- MedianNorm(Data)
if(is.na(Sizes[1])){
Sizes <- MedianNorm(Data, alternative=TRUE)
message("alternative normalization method is applied")
}
DataUse0 <- GetNormalizedMat(Data,Sizes)
DataUse=DataUse0[which(apply(DataUse0,1,max)>List$LODNum),]
# main function
Res <- SCPTest(DataUse, List$Cond, Sizes, Circular=List$Circular, maxround=List$iters,
Dropout.remove=List$RMTF, Dropout.upper=List$Dropupper, LOD=List$LOD,
NumPat=NumPat, Directional=Directional)
print("writting output...")
#browser()
levs <- levels(List$Cond)
nlevs <- nlevels(List$Cond)
if(nlevs==2){
PPmat <- Res$PP
#if("NC"%in%colnames(PPmat))
AllEE <- "NC"
#if("EE"%in%colnames(PPmat))AllEE <- "EE"
names(Res$MAP)=names(Res$maxPP)=rownames(Res$PP)
NotEE <- names(Res$MAP)[which(Res$MAP!=AllEE)]
NotEE.s <- names(sort(Res$maxPP[NotEE], decreasing=T))
PPmat.sig <- cbind(NotEE.s, Res$maxPP[NotEE.s], Res$MAP[NotEE.s])
colnames(PPmat.sig) <- c("gene", "PP most likely pattern", "most likely pattern")
rownames(PPmat.sig) <- rep("", nrow(PPmat.sig))
}
if(nlevs > 2){
PPmat <- Res$PP.all
PPmat.sig0 <- Res$sortedlist
NotEE.s <- rownames(Res$sortedlist)
PPmat.sig <- cbind(NotEE.s, PPmat.sig0)
colnames(PPmat.sig) <- c("gene", "PP most likely pattern", "most likely pattern")
}
write.csv(PPmat.sig,file=List$exOEF)
write.csv(PPmat,file=List$exPVF)
write.csv(DataUse0, file=List$exExpF)
#for(i in 1:length(Res$Res))write.csv(Res$Res[[i]]$PP, file=paste0(List$exPVFraw,
# "_",levs[i],"_",levs[i+1],".csv"))
if(List$PlotTF){
PN <- NULL
if(List$PlotN!="")PN <- as.numeric(List$PlotN)
else PN <- min(100,length(NotEE.s))
if(length(PN)>0){
pdf(List$PlotF, height=15,width=15)
par(mfrow=c(5,4))
for(i in 1:PN){
if(List$PlotType%in%c("1","3")){
if(List$whetherLog==TRUE)VioFun(NotEE.s[i],log2(DataUse0+1),
List$Cond, Dropout.remove=FALSE, ylab="log2(expression+1)",
main_pre="Dropouts are shown")
if(List$whetherLog==FALSE)VioFun(NotEE.s[i],DataUse0,
List$Cond, Dropout.remove=FALSE, ylab="expression",
main_pre="Dropouts are shown")
}
if(List$PlotType%in%c("2","3")){
if(List$whetherLog==TRUE)VioFun(NotEE.s[i],log2(DataUse0+1),
List$Cond, Dropout.remove=TRUE, ylab="log2(expression+1)",
Dropout.upper=List$Dropupper, main_pre="Dropouts are not shown")
if(List$whetherLog==FALSE)VioFun(NotEE.s[i],DataUse0,
List$Cond, Dropout.remove=TRUE, ylab="expression",
Dropout.upper=List$Dropupper, main_pre="Dropouts are not shown")
}
}
dev.off()
}}
List=c(List, list(Sig=PPmat.sig))
})
Act <- eventReactive(input$Submit,{
In()})
# Show the values using an HTML table
output$print0 <- renderText({
tmp <- Act()
str(tmp)
paste("output directory:", tmp$Dir)
})
output$tab <- renderDataTable({
tmp <- Act()$Sig
t1 <- tmp
print("done")
t1
},options = list(lengthManu = c(4,4), pageLength = 20))
# output$done <- renderText({"Done"})
})