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server.R
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library(shiny)
library(shinyjs)
library(GEOquery)
library(pd.mogene.2.0.st)
library(mogene20sttranscriptcluster.db)
library(pd.hg.u133.plus.2)
library(hgu133plus2.db)
library(pd.hugene.2.0.st)
library(hugene20sttranscriptcluster.db)
library(pd.clariom.s.human.ht)
library(clariomshumanhttranscriptcluster.db)
library(pd.clariom.s.human)
library(clariomshumantranscriptcluster.db)
library(pd.clariom.s.mouse.ht)
library(clariomsmousehttranscriptcluster.db)
library(pd.clariom.s.mouse)
library(clariomsmousetranscriptcluster.db)
library(pd.mouse430.2)
library(mouse4302.db)
library(pd.hg.u133a)
library(hgu133a.db)
library(pd.hugene.1.0.st.v1)
library(hugene10sttranscriptcluster.db)
library(pd.mogene.1.0.st.v1)
library(mogene10sttranscriptcluster.db)
library(pd.hg.u133a.2)
library(hgu133a2.db)
library(pd.huex.1.0.st.v2)
library(huex10sttranscriptcluster.db)
library(pd.hg.u219)
library(hgu219.db)
library(pd.mg.u74av2)
library(mgu74av2.db)
library(pd.mouse430a.2)
library(mouse430a2.db)
library(pd.moe430a)
library(moe430a.db)
library(pd.hg.u95av2)
library(hgu95av2.db)
library(pd.hta.2.0)
library(hta20transcriptcluster.db)
library(pd.moex.1.0.st.v1)
library(moex10sttranscriptcluster.db)
library(pd.hg.u133b)
library(hgu133b.db)
library(pd.hugene.1.1.st.v1)
library(hugene11sttranscriptcluster.db)
library(pd.mogene.1.1.st.v1)
library(mogene11sttranscriptcluster.db)
library(pd.clariom.s.rat)
library(clariomsrattranscriptcluster.db)
library(pd.hugene.2.1.st)
library(hugene21sttranscriptcluster.db)
#library(primeviewprobe)
#library(GSEA)
library(limma)
library(oligo)
library(gplots)
library(geneplotter)
library(multtest)
library(rgl)
library(rglwidget)
library(DT)
library(getopt)
library(annotate)
library(knitr)
library(reshape)
library(RColorBrewer)
library(mixOmics)
library(calibrate)
library(rmarkdown)
library(ggplot2)
library(ggfortify)
library(shinyRGL)
library(plotly)
library(htmltools)
library(heatmaply)
library(Biobase)
library(GSVA)
library(GSEABase)
library(pheatmap)
library(viridis)
library(dendsort)
library(htmlwidgets)
#setwd('/Users/valdezkm/Documents/MicroarrayPipeline/CodeInProgress/MicroArrayPipeline')
shinyServer(function(input, output) {
v <- reactiveValues(data = NULL, platform=NULL)
k <- reactiveValues()
observeEvent(
input$GObutton,
isolate({
shinyjs::show("hideEverything")
})
)
observeEvent(
input$button,
isolate({
shinyjs::show("hide1")
})
)
observeEvent(
input$button,
isolate({
shinyjs::show("hide2")
})
)
observeEvent(
input$CELbutton,
isolate({
shinyjs::show("hide1")
})
)
observeEvent(
input$CELbutton,
isolate({
shinyjs::show("hideCEL")
})
)
observeEvent(
input$button2,
isolate({
shinyjs:: show("hide3")
})
)
observeEvent(
input$addrow,
isolate({
shinyjs:: show("hideAnalysis")
})
)
observeEvent(
input$analyze,
isolate({
shinyjs:: show("hideResults")
})
)
observeEvent(
input$test,
isolate({
shinyjs:: show("hideContrast")
})
)
observeEvent(
input$analyze,
isolate({
shinyjs:: show("hideDownloads")
})
)
observeEvent(
input$GObutton,
isolate({
if (input$ProjectID=='') {
info("Please restart and enter a Project ID")
stopApp(-1)
}
})
)
observeEvent(
input$CELbutton,
isolate({
#CEL file input
myfiles=input$Indir
cels = myfiles$name
mytableCEL=matrix("",length(cels),1)
colnames(mytableCEL)=c("title")
for (k in 1:length(cels))
{
mytableCEL[k,]<-c(cels[k])
}
mytableCEL <- data.frame(mytableCEL)
mytableCEL$group <- "..."
v$data <- mytableCEL
output$mytableCEL = DT::renderDataTable({
if (is.null(v$data)) return()
if (is.null(v$platform)) warning()
DT::datatable(v$data, options = list(lengthMenu = c(2,4,6,8), pageLength = 8))
})
})
)
observeEvent(
input$button,
isolate({
#GSE input
withProgress(message = 'Loading files...', value = 0.25, {
if (input$gseid=="8 digit GSE code") return()
id=input$gseid
id = gsub(" ","",id,fixed=TRUE)
incProgress(0.25)
#gds <- getGEO(input$gseid, GSEMatrix = F,getGPL=T,AnnotGPL=T)
gds <- getGEO(id, GSEMatrix = F,getGPL=T,AnnotGPL=T)
#gds
mytable=matrix("",length(GSMList(gds)),3)
colnames(mytable)=c("gsm","title","description")
for (k in 1:length(GSMList(gds)))
{
if (is.null(Meta(GSMList(gds)[[k]])$description)) { #error handling, some records don't have descriptions
mytable[k,] <-c(Meta(GSMList(gds)[[k]])$geo_accession[1], Meta(GSMList(gds)[[k]])$title[1], 'No data available')
} else {
mytable[k,] <-c(Meta(GSMList(gds)[[k]])$geo_accession[1], Meta(GSMList(gds)[[k]])$title[1], Meta(GSMList(gds)[[k]])$description[1])
}
}
# }
mytable <- data.frame(mytable)
mytable$group <- "..."
v$data <- mytable
incProgress(0.25)
output$mytable = DT::renderDataTable({
if (is.null(v$data)) return()
if (is.null(v$platform)) warning()
DT::datatable(v$data, options = list(lengthMenu = c(2,4,6,8), pageLength = 8))
})
})
})
)
observeEvent(
input$button2,
isolate({
if (is.null(v$data)) return()
if (is.null(input$group1)) return()
#print(v$data)
#print( "Error??2")
#error handling names that conflict with DEG script
tempGroup = input$group1
tempGroup = make.names(tempGroup)
v$data[input$mytable_rows_selected, "group" ] <- tempGroup
v$data[input$mytableCEL_rows_selected, "group"] <- tempGroup
#print( "Error??3")
output$mytableCEL = DT::renderDataTable({
if (is.null(v$data)) return()
if (is.null(v$platform)) warning()
DT::datatable(v$data, options = list(lengthMenu = c(2,4,6,8,10), pageLength = 8))
})
output$mytable = DT::renderDataTable({
if (is.null(v$data)) return()
if (is.null(v$platform)) warning()
DT::datatable(v$data, options = list(lengthMenu = c(2,4,6,8,10), pageLength = 8))
})
})
)
observe({
isolate({
output$ui <- renderUI({
# if (is.null(input$number))
# return()
textInput("group1", "Enter a group name (with no spaces)")
})
})
})
observe({
isolate({
output$choice1 <- renderUI({
g = unique(v$data$group)
selectizeInput("selectIn1","Select:",choices = g)
})
})
})
observe({
isolate({
output$choice2 <- renderUI({
g = unique(v$data$group)
selectizeInput("selectIn2","Versus Reference Group:",choices = g)
})
})
})
observeEvent(input$addrow,{
isolate({
newLine1 = c(input$selectIn1)
newLine2 = c(input$selectIn2)
k$k1 <- rbind(k$k1, newLine1)
k$k2 <- rbind(k$k2, newLine2)
})
})
output$contrastTable <- renderTable({
data.frame(paste0(k$k1,' vs ', k$k2))
}, colnames = FALSE)
observe({
isolate({
output$displayContrast <- renderUI({
selectizeInput("NumContrasts", label=h6("Choose contrast to show"),choices=paste0(k$k1, ' vs ', k$k2), width="150px")
})
})
})
observeEvent(
input$analyze, {
isolate({
raw <- reactive(
{
withProgress(message = 'Loading files...', value = 0.25, {
id=input$gseid
if (id=='8 digit GSE code'){
myfiles = input$Indir
cels = myfiles$datapath
Pheno = v$data
rownames(Pheno) = Pheno$title
SampleName = myfiles$name
pd = AnnotatedDataFrame(Pheno)
celfiles = read.celfiles(cels, phenoData = pd)
colnames(pData(celfiles))[1] = 'SampleID'
} else {
id = gsub(" ","",id,fixed=TRUE)
system(paste0('rm *.[cC][eE][lL].gz')) #removes previous CEL files
getGEOSuppFiles(id, makeDirectory = T, baseDir = getwd())
fileID = paste0(id, '_RAW.tar')
#system(paste0('tar -xvf', fileID))
untar(paste0(getwd(),'/',id,'/',fileID))
incProgress(0.25)
#cels = paste0(Pheno$gsm,'_',Pheno$title,'.CEL.gz') #adds filename
Pheno = v$data
SampleName = list.files(pattern = '/*CEL.gz', ignore.case = T) #list contents of new directory with zipped CEL files
if (length(grep('*CEL*',SampleName,ignore.case = T)) == 0) {
info("Raw files must be CEL files")
}
rownames(Pheno) = Pheno$title
cels = SampleName
incProgress(0.25)
pd = AnnotatedDataFrame(Pheno)
celfiles = read.celfiles(cels, phenoData = pd)
colnames(pData(celfiles))[2] = 'SampleID'
}
y<-paste("_",input$ProjectID, sep="")
tAnnot = tempfile(pattern = "annotation_", tmpdir = getwd(), fileext = paste0(y,'.txt'))
cat(celfiles@annotation,file=tAnnot)
if (celfiles@annotation!="pd.hg.u133.plus.2" & celfiles@annotation!="pd.mogene.2.0.st" & celfiles@annotation!="pd.hugene.2.0.st" & celfiles@annotation!="pd.clariom.s.human.ht" & celfiles@annotation!="pd.clariom.s.human" & celfiles@annotation!="pd.clariom.s.mouse.ht" & celfiles@annotation!="pd.clariom.s.mouse" & celfiles@annotation!='pd.mouse430.2' & celfiles@annotation!='pd.hg.u133a' & celfiles@annotation!='pd.hugene.1.0.st.v1' & celfiles@annotation!='pd.mogene.1.0.st.v1' & celfiles@annotation!='pd.hg.u133a.2' & celfiles@annotation!='pd.huex.1.0.st.v2' & celfiles@annotation!='pd.hg.u219' & celfiles@annotation!='pd.mg.u74av2' & celfiles@annotation!='pd.mouse430a.2' & celfiles@annotation!='pd.moe430a' & celfiles@annotation!='pd.hg.u95av2' & celfiles@annotation!='pd.hta.2.0' & celfiles@annotation!='pd.moex.1.0.st.v1' & celfiles@annotation!='pd.hg.u133b' & celfiles@annotation!='pd.hugene.1.1.st.v1' & celfiles@annotation!='pd.mogene.1.1.st.v1' & celfiles@annotation!='pd.clariom.s.rat' & celfiles@annotation!='pd.hugene.2.1.st') {
#cat("Please sort your phenotype on sample name and upload it again. \n")
info(paste0("Affymetrix platform: ",celfiles@annotation," NOT supported. Leaving..."))
stopApp(-1)
}
incProgress(0.25)
celfiles
})
})
norm=reactive(
{
write.csv(exprs(raw()),'~/Desktop/temp.csv')
withProgress(message = 'Normalization', detail = 'starting ...', value = 0, {
if (raw()@annotation=="pd.hg.u133.plus.2" | raw()@annotation=="pd.clariom.s.human.ht" | raw()@annotation=="pd.clariom.s.human" | raw()@annotation=="pd.clariom.s.mouse.ht" | raw()@annotation=="pd.clariom.s.mouse" | raw()@annotation=='pd.mouse430.2' | raw()@annotation=='pd.hg.u133a' | raw()@annotation=='pd.hg.u133a.2' | raw()@annotation=='pd.hg.u219' | raw()@annotation=='pd.mg.u74av2' | raw()@annotation=='pd.mouse430a.2' | raw()@annotation=='pd.moe430a' | raw()@annotation=='pd.hg.u95av2' | raw()@annotation=='pd.hg.u133b' | raw()@annotation=='pd.clariom.s.rat') {
incProgress(0.5)
celfiles.rma =rma(raw(), background=TRUE, normalize=TRUE, subset=NULL)
} else {
incProgress(0.5)
celfiles.rma =rma(raw(), background=TRUE, normalize=TRUE, subset=NULL, target="core")
}
})
})
qc=reactive(
{
withProgress(message = 'Fitting probe level model', detail = 'starting ...', value = 0.75, {
validate(
need(raw()@annotation!= "pd.mogene.1.0.st.v1" && raw()@annotation!='pd.mogene.1.1.st.v1', 'NUSE and RLE plots unavailable for this platform.')
)
celfiles.qc=fitProbeLevelModel(raw())
})
}
)
# list of DEG
deg=reactive(
{
##-------------
withProgress(message = 'Analysis starting...', value = 0, {
sampleColumns = sort(c(which(v$data$group %in% k$k2[,1]),which(v$data$group %in% k$k1[,1])))
subs = pData(norm())[sampleColumns,]
facs <- factor(subs$group)
labfacs=levels(facs)
# nbfacs=length(labfacs)
contra=data.frame(k$k1,k$k2)
nb=dim(contra)[1]
cons=c()
#validate(
# need((contra[k,1] %in% labfacs) & (contra[k,2] %in% labfacs), "One of the groups in contrast file does not match a group in phenotype file. Make sure names match and upload again.
#Once correct file is entered, 'Computing differentially expressed genes' message will display.")
#)
for (k in 1:nb) {
#if ((contra[k,1] %in% labfacs) & (contra[k,2] %in% labfacs) )
#{
cons=c(cons,paste(contra[k,1],"-",contra[k,2],sep=""))
#} else {
# cat("One of the groups in contrasts file at line :",k+1,"does not match a group in phenotype file..Quitting!!!\n")
# info('One of the groups in contrast file does not match a group in phenotype file. Make sure names match and upload again.')
# print( contra )
# stopApp(-1)
#}
}
myfactor <- factor(subs$group)
design1 <- model.matrix(~0+myfactor)
colnames(design1) <- levels(myfactor)
sub_dat = norm()[,sampleNames(norm())[sampleColumns]]
fit1 <- lmFit(sub_dat,design1)
contrast.matrix <- makeContrasts(contrasts=cons,levels=design1)
fit2 <- contrasts.fit(fit1, contrast.matrix)
ebayes.fit2=eBayes(fit2) # smooths the std error
incProgress(0.25)
# #EXTRACTING ALL GENES FOR EACH CONTRAST
##ANNOTATE PROBESET IDS FROM ANNOTATION PACKAGE FROM BIOCONDUCTOR
## load libraries as sources of annotation
#library(mogene20sttranscriptcluster.db)
#if (input$Platform=="mst2") {
#if (raw()@annotation=="pd.mogene.2.0.st") {
# Annot <- data.frame(ACCNUM=sapply(contents(mogene20sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(mogene20sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(mogene20sttranscriptclusterGENENAME), paste, collapse=", "))
#} else {
# if (input$Platform=="h133p2") {
# if (raw()@annotation=="pd.hg.u133.plus.2") {
# Annot <- data.frame(ACCNUM=sapply(contents(hgu133plus2ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hgu133plus2SYMBOL), paste, collapse=", "), DESC=sapply(contents(hgu133plus2GENENAME), paste, collapse=", "))
# }
#}
if (raw()@annotation=="pd.mogene.2.0.st") {
Annot <- data.frame(ACCNUM=sapply(contents(mogene20sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(mogene20sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(mogene20sttranscriptclusterGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(mogene20sttranscriptclusterENTREZID), paste, collapse=", "))
#Annot <- data.frame(ACCNUM=sapply(contents(mogene20sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(mogene20sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(mogene20sttranscriptclusterGENENAME), paste, collapse=", "))
} else {
# if (input$Platform=="h133p2") {
if (raw()@annotation=="pd.hg.u133.plus.2") {
#Annot <- data.frame(ACCNUM=sapply(contents(hgu133plus2ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hgu133plus2SYMBOL), paste, collapse=", "), DESC=sapply(contents(hgu133plus2GENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(hgu133plus2ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hgu133plus2SYMBOL), paste, collapse=", "), DESC=sapply(contents(hgu133plus2GENENAME), paste, collapse=", "), ENTREZ=sapply(contents(hgu133plus2ENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=="pd.hugene.2.0.st") {
#Annot <- data.frame(ACCNUM=sapply(contents(hugene20sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hugene20sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(hugene20sttranscriptclusterGENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(hugene20sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hugene20sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(hugene20sttranscriptclusterGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(hugene20sttranscriptclusterENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=="pd.clariom.s.human.ht") {
#Annot <- data.frame(ACCNUM=sapply(contents(clariomshumanhttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(clariomshumanhttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(clariomshumanhttranscriptclusterGENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(clariomshumanhttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(clariomshumanhttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(clariomshumanhttranscriptclusterGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(clariomshumanhttranscriptclusterENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=="pd.clariom.s.mouse.ht") {
#Annot <- data.frame(ACCNUM=sapply(contents(clariomsmousehttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(clariomsmousehttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(clariomsmousehttranscriptclusterGENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(clariomsmousehttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(clariomsmousehttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(clariomsmousehttranscriptclusterGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(clariomsmousehttranscriptclusterENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=="pd.clariom.s.mouse") {
#Annot <- data.frame(ACCNUM=sapply(contents(clariomsmousetranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(clariomsmousetranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(clariomsmousetranscriptclusterGENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(clariomsmousetranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(clariomsmousetranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(clariomsmousetranscriptclusterGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(clariomsmousetranscriptclusterENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=="pd.clariom.s.human") {
#Annot <- data.frame(ACCNUM=sapply(contents(clariomshumantranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(clariomshumantranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(clariomshumantranscriptclusterGENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(clariomshumantranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(clariomshumantranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(clariomshumantranscriptclusterGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(clariomshumantranscriptclusterENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=="pd.mouse430.2") {
#Annot <- data.frame(ACCNUM=sapply(contents(mouse4302ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(mouse4302SYMBOL), paste, collapse=", "), DESC=sapply(contents(mouse4302GENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(mouse4302ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(mouse4302SYMBOL), paste, collapse=", "), DESC=sapply(contents(mouse4302GENENAME), paste, collapse=", "), ENTREZ=sapply(contents(mouse4302ENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.hg.u133a') {
#Annot <- data.frame(ACCNUM=sapply(contents(hgu133aACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hgu133aSYMBOL), paste, collapse=", "), DESC=sapply(contents(hgu133aGENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(hgu133aACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hgu133aSYMBOL), paste, collapse=", "), DESC=sapply(contents(hgu133aGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(hgu133aENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.hugene.1.0.st.v1') {
#Annot <- data.frame(ACCNUM=sapply(contents(hugene10sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hugene10sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(hugene10sttranscriptclusterGENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(hugene10sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hugene10sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(hugene10sttranscriptclusterGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(hugene10sttranscriptclusterENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.mogene.1.0.st.v1') {
#Annot <- data.frame(ACCNUM=sapply(contents(mogene10sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(mogene10sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(mogene10sttranscriptclusterGENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(mogene10sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(mogene10sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(mogene10sttranscriptclusterGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(mogene10sttranscriptclusterENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.hg.u133a.2') {
#Annot <- data.frame(ACCNUM=sapply(contents(hgu133a2ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hgu133a2SYMBOL), paste, collapse=", "), DESC=sapply(contents(hgu133a2GENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(hgu133a2ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hgu133a2SYMBOL), paste, collapse=", "), DESC=sapply(contents(hgu133a2GENENAME), paste, collapse=", "), ENTREZ=sapply(contents(hgu133a2ENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.huex.1.0.st.v2') {
#Annot <- data.frame(ACCNUM=sapply(contents(huex10sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(huex10sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(huex10sttranscriptclusterGENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(huex10sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(huex10sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(huex10sttranscriptclusterGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(huex10sttranscriptclusterENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.hg.u219') {
#Annot <- data.frame(ACCNUM=sapply(contents(hgu219ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hgu219SYMBOL), paste, collapse=", "), DESC=sapply(contents(hgu219GENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(hgu219ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hgu219SYMBOL), paste, collapse=", "), DESC=sapply(contents(hgu219GENENAME), paste, collapse=", "), ENTREZ=sapply(contents(hgu219ENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.ht.hg.u133.plus.pm') {
#Annot <- data.frame(ACCNUM=sapply(contents(hgu133plus2ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hgu133plus2SYMBOL), paste, collapse=", "), DESC=sapply(contents(hgu133plus2GENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(hgu133plus2ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hgu133plus2SYMBOL), paste, collapse=", "), DESC=sapply(contents(hgu133plus2GENENAME), paste, collapse=", "), ENTREZ=sapply(contents(hgu133plus2ENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.mg.u74av2') {
#Annot <- data.frame(ACCNUM=sapply(contents(mgu74av2ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(mgu74av2SYMBOL), paste, collapse=", "), DESC=sapply(contents(mgu74av2GENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(mgu74av2ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(mgu74av2SYMBOL), paste, collapse=", "), DESC=sapply(contents(mgu74av2GENENAME), paste, collapse=", "), ENTREZ=sapply(contents(mgu74av2ENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.mouse430a.2') {
#Annot <- data.frame(ACCNUM=sapply(contents(mouse430a2ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(mouse430a2SYMBOL), paste, collapse=", "), DESC=sapply(contents(mouse430a2GENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(mouse430a2ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(mouse430a2SYMBOL), paste, collapse=", "), DESC=sapply(contents(mouse430a2GENENAME), paste, collapse=", "), ENTREZ=sapply(contents(mouse430a2ENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.moe430a') {
#Annot <- data.frame(ACCNUM=sapply(contents(moe430aACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(moe430aSYMBOL), paste, collapse=", "), DESC=sapply(contents(moe430aGENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(moe430aACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(moe430aSYMBOL), paste, collapse=", "), DESC=sapply(contents(moe430aGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(moe430aENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.hg.u95av2') {
#Annot <- data.frame(ACCNUM=sapply(contents(hgu95av2ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hgu95av2SYMBOL), paste, collapse=", "), DESC=sapply(contents(hgu95av2GENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(hgu95av2ACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hgu95av2SYMBOL), paste, collapse=", "), DESC=sapply(contents(hgu95av2GENENAME), paste, collapse=", "), ENTREZ=sapply(contents(hgu95av2ENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.hta.2.0') {
#Annot <- data.frame(ACCNUM=sapply(contents(hta20transcriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hta20transcriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(hta20transcriptclusterGENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(hta20transcriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hta20transcriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(hta20transcriptclusterGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(hta20transcriptclusterENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.moex.1.0.st.v1') {
#Annot <- data.frame(ACCNUM=sapply(contents(moex10sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(moex10sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(moex10sttranscriptclusterGENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(moex10sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(moex10sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(moex10sttranscriptclusterGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(moex10sttranscriptclusterENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.hg.u133b') {
#Annot <- data.frame(ACCNUM=sapply(contents(hgu133bACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hgu133bSYMBOL), paste, collapse=", "), DESC=sapply(contents(hgu133bGENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(hgu133bACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hgu133bSYMBOL), paste, collapse=", "), DESC=sapply(contents(hgu133bGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(hgu133bENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.hugene.1.1.st.v1') {
#Annot <- data.frame(ACCNUM=sapply(contents(hugene11sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hugene11sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(hugene11sttranscriptclusterGENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(hugene11sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hugene11sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(hugene11sttranscriptclusterGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(hugene11sttranscriptclusterENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.mogene.1.1.st.v1') {
#Annot <- data.frame(ACCNUM=sapply(contents(mogene11sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(mogene11sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(mogene11sttranscriptclusterGENENAME), paste, collapse=", "))
Annot <- data.frame(ACCNUM=sapply(contents(mogene11sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(mogene11sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(mogene11sttranscriptclusterGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(mogene11sttranscriptclusterENTREZID), paste, collapse=", "))
} else{
if (raw()@annotation=='pd.clariom.s.rat'){
Annot <- data.frame(ACCNUM=sapply(contents(clariomsrattranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(clariomsrattranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(clariomsrattranscriptclusterGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(clariomsrattranscriptclusterENTREZID), paste, collapse=", "))
} else {
if (raw()@annotation=='pd.hugene.2.1.st') {
Annot <- data.frame(ACCNUM=sapply(contents(hugene21sttranscriptclusterACCNUM), paste, collapse=", "), SYMBOL=sapply(contents(hugene21sttranscriptclusterSYMBOL), paste, collapse=", "), DESC=sapply(contents(hugene21sttranscriptclusterGENENAME), paste, collapse=", "), ENTREZ=sapply(contents(hugene21sttranscriptclusterENTREZID), paste, collapse=", "))
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}
incProgress(0.25)
mylist=vector("list",nb)
myCollapsedList=vector("list",nb)
for (i in 1:nb)
{
all.genes.con = topTable(ebayes.fit2, coef = i, number=nrow(ebayes.fit2))
# Merge data frames together (like a database table join)
all <- merge(all.genes.con, Annot,by.x=0, by.y=0, all.x=T)
all=all[order(all$P.Value),]
colnames(all)[1]="probsetID"
#add fold change and rearrange columns
all$FC = ifelse(all$logFC<0, -1/(2^all$logFC), 2^all$logFC)
all = all[,c(9,12,2,5,6,3,8,10,11,1,4,7)]
# Write uncollapsed deg out to a file
write.table(all,file=paste(input$ProjectID,"_",cons[i],"_all_genes.txt",sep=""),sep="\t",row.names=F)
# Collapse deg for gui and output, write out to file
collapsed = all[,-c(7,10)]
collapsed = aggregate(.~SYMBOL+DESC+ENTREZ,data=collapsed,mean)
collapsed = collapsed[,c(1,4:8,2:3,9:10)]
write.table(collapsed,file=paste(input$ProjectID,"_",cons[i],"_all_genes_collapsed.txt",sep=""),sep="\t",row.names=F)
# create deg lists (both uncollapsed and collapsed) to return
mylist[[i]]=all
myCollapsedList[[i]] = collapsed
## end for
}
# output annotated normalized expression for all samples
all_output = merge(exprs(norm()), Annot,by.x=0, by.y=0, all.x=T)
y<-paste("_",input$ProjectID, sep="")
tNorm = tempfile(pattern = "normalized_data_", tmpdir = getwd(), fileext = paste0(y,'.txt'))
write.table(all_output,file=tNorm,sep="\t",row.names=F)
# return annotated normalized expression for chosen samples
all <- merge(exprs(sub_dat), Annot,by.x=0, by.y=0, all.x=T)
names(mylist)=cons
incProgress(0.5, detail = 'DEG done')
#mylist
list(mylist=mylist, all=all, cons=cons, design1=design1, nb=nb, myCollapsedList=myCollapsedList)
})
##-------------
}
) #end DEG
pathways=reactive(
{
#L2P pathway starts here KV
k$all = cbind(paste0(k$k1, ' vs ', k$k2))
num = which(input$NumContrasts==k$all[,1])
all = deg()$mylist[[num]]
#up=vector("list",nb)
#dw=vector("list",nb)
iup=which(all$P.Value<0.05 & all$logFC>=0)
idw=which(all$P.Value<0.05 & all$logFC<0)
fin.up=all[iup,]
if (length(iup) > 500)
{
fin.up=fin.up[order(fin.up$P.Value),]
fin.up=fin.up[1:500,]
}
#x2=rownames(fin.up)
#gup=apply(array(as.character(x2)),1,function(z) unlist(strsplit(z, "\\|"))[2])
fin.dw=all[idw,]
if (length(idw) > 500)
{
fin.dw=fin.dw[order(fin.dw$P.Value),]
fin.dw=fin.dw[1:500,]
}
#running volcano plot prior to pathways inexplicably turns SYMBOL into a factor so:
fin.up$SYMBOL = as.character(fin.up$SYMBOL)
fin.dw$SYMBOL = as.character(fin.dw$SYMBOL)
#x2=rownames(fin.dw)
#gdw=apply(array(as.character(x2)),1,function(z) unlist(strsplit(z, "\\|"))[2])
if (raw()@annotation=="pd.hg.u133.plus.2" | raw()@annotation=="pd.hugene.2.0.st" | raw()@annotation=="pd.clariom.s.human.ht" | raw()@annotation=="pd.clariom.s.human" | raw()@annotation=='pd.hg.u133a' | raw()@annotation=='pd.hugene.1.0.st.v1' | raw()@annotation=='pd.hg.u133a.2' | raw()@annotation=='pd.huex.1.0.st.v2' | raw()@annotation=='pd.hg.u219' | raw()@annotation=='pd.ht.hg.u133.plus.pm' | raw()@annotation=='pd.hg.u95av2' | raw()@annotation=='pd.hta.2.0' | raw()@annotation=='pd.hg.u133b' | raw()@annotation=='pd.hugene.1.1.st.v1' | raw()@annotation=='pd.hugene.2.1.st')
{
cat(fin.up$SYMBOL,file=(paste0(input$ProjectID,'_',names(deg()$mylist[num]),'_Top500_Up.txt')), sep='\n')
cat(fin.dw$SYMBOL,file=(paste0(input$ProjectID,'_',names(deg()$mylist[num]),'_Top500_Down.txt')),sep='\n')
}
else
{
cat(fin.up$SYMBOL,file=paste0(names(deg()$mylist[num]),"_Top500temp_Up.txt"),sep='\n')
cat(fin.dw$SYMBOL,file=paste0(names(deg()$mylist[num]),"_Top500temp_Dw.txt"),sep='\n')
system(paste0("cat ",names(deg()$mylist[num]),"_Top500temp_Up.txt | grep -v \"^NA\" | ./m2h | grep -v XXXX | cut -f2 -d\" \" >",input$ProjectID,'_',names(deg()$mylist[num]),"_Top500_Up.txt"))
system(paste0("cat ",names(deg()$mylist[num]),"_Top500temp_Dw.txt | grep -v \"^NA\" | ./m2h | grep -v XXXX | cut -f2 -d\" \" >",input$ProjectID,'_',names(deg()$mylist[num]),"_Top500_Down.txt"))
}
system(paste0("cat ",input$ProjectID,'_',names(deg()$mylist[num]),"_Top500_Up.txt |sort | uniq | ./l2p >",input$ProjectID,'_',names(deg()$mylist[num]),"_Pathways_Up.txt"))
system(paste0("cat ",input$ProjectID,'_',names(deg()$mylist[num]),"_Top500_Down.txt |sort | uniq | ./l2p >",input$ProjectID,'_',names(deg()$mylist[num]),"_Pathways_Down.txt"))
addUpCol = read.delim(paste0(input$ProjectID,'_',names(deg()$mylist[num]),"_Pathways_Up.txt"), sep = '\t')
addDwCol = read.delim(paste0(input$ProjectID,'_',names(deg()$mylist[num]),"_Pathways_Down.txt"), sep = '\t')
colnames(addUpCol)=c("pval","fdr","ratio","nb.hits","nb.genes.path","nb.user.genes","tot.back.genes","path_id","source","description","type","gene.list")
colnames(addDwCol)=c("pval","fdr","ratio","nb.hits","nb.genes.path","nb.user.genes","tot.back.genes","path_id","source","description","type","gene.list")
addUpCol = addUpCol[order(addUpCol$pval),]
addDwCol = addDwCol[order(addDwCol$pval),]
addUpCol = addUpCol[,c(8,9,10,11,1,2,3,12,4,5,6,7)]
addDwCol = addDwCol[,c(8,9,10,11,1,2,3,12,4,5,6,7)]
write.table(addUpCol, file = paste0(input$ProjectID,'_',names(deg()$mylist[num]),"_Pathways_Up.txt"), sep = '\t', row.names = F)
write.table(addDwCol, file = paste0(input$ProjectID,'_',names(deg()$mylist[num]),"_Pathways_Down.txt"), sep = '\t', row.names = F)
list(up=addUpCol,dw=addDwCol)
}
) #end pathways
ssGSEA=reactive(
{
withProgress(message = 'Performing ssGSEA', detail = 'may take a couple of minutes ...', value = 0, {
ssgs = deg()$all
ssgs = ssgs[ssgs$SYMBOL!='NA',]
if (raw()@annotation=="pd.hg.u133.plus.2" | raw()@annotation=="pd.hugene.2.0.st" | raw()@annotation=="pd.clariom.s.human.ht" | raw()@annotation=="pd.clariom.s.human" | raw()@annotation=='pd.hg.u133a' | raw()@annotation=='pd.hugene.1.0.st.v1' | raw()@annotation=='pd.hg.u133a.2' | raw()@annotation=='pd.huex.1.0.st.v2' | raw()@annotation=='pd.hg.u219' | raw()@annotation=='pd.ht.hg.u133.plus.pm' | raw()@annotation=='pd.hg.u95av2' | raw()@annotation=='pd.hta.2.0' | raw()@annotation=='pd.hg.u133b' | raw()@annotation=='pd.hugene.1.1.st.v1' | raw()@annotation=='pd.hugene.2.1.st') {
ssgs = subset(ssgs, select=-c(ACCNUM,DESC,Row.names,ENTREZ))
ssgs = aggregate(.~SYMBOL,data=ssgs,mean) #aggregate duplicate probes by mean
rownames(ssgs) = ssgs$SYMBOL
ssgs = subset(ssgs, select=-c(SYMBOL))
ssgs = as.matrix(ssgs)
}
else
{
ssgs = subset(ssgs, select=-c(ACCNUM,DESC,Row.names,SYMBOL))
ssgs = aggregate(.~ENTREZ,data=ssgs,mean) #aggregate duplicate probes by mean
rownames(ssgs) = ssgs$ENTREZ
ssgs = subset(ssgs, select=-c(ENTREZ))
ssgs = as.matrix(ssgs)
}
#user input gene set
if (input$geneSet=="") {
info("Please select human or mouse gene set from list")
} else {
gset = getGmt(input$geneSet)
ssgsResults = gsva(ssgs, gset, method='ssgsea') #run GSVA
}
y<-paste("_",input$ProjectID, sep="")
tSS = tempfile(pattern = "ssGSEA_enrichmentScores_", tmpdir = getwd(), fileext = paste0(y,'.txt'))
write.table(ssgsResults,file=tSS,sep="\t",col.names=NA)
incProgress(amount = 0.50, detail = 'Performing differential expression analysis of pathways...')
fit1 = lmFit(ssgsResults,deg()$design1)
contrast.matrix = makeContrasts(contrasts=deg()$cons,levels=deg()$design1)
fit2 = contrasts.fit(fit1,contrast.matrix)
ebayes.fit2 = eBayes(fit2)
myPathways=vector("list",deg()$nb)
for (i in 1:deg()$nb)
{
all.pathways = topTable(ebayes.fit2, coef=i, number=nrow(ebayes.fit2))
all.pathways = all.pathways[order(abs(all.pathways$P.Value)),]
colnames(all.pathways)[2] = 'Avg.Enrichment.Score'
write.table(all.pathways,file=paste0(input$ProjectID,"_",deg()$cons[i],"_ssGSEA_pathways.txt"),sep="\t",row.names=T,col.names=NA)
myPathways[[i]] = all.pathways
}
names(myPathways)=deg()$cons
list(myPathways=myPathways,ssgsResults=ssgsResults)
})
}
)
#Processing all outputs
####creates a list of colors specific to each group
fs = factor(pData(raw())$group)
#fs = factor(pData(raw())$SampleGroup)
lFs=levels(fs)
numFs=length(lFs)
colors = list()
for (i in 1:numFs){
colors[which(fs==lFs[i])] = i*5
}
colors = unlist(colors)
####end
output$projectid=renderText({paste("Project ID: ",input$ProjectID)})
output$rawhist=renderPlot(
{
hist(raw(),which="all", main =" Raw Samples distribution")
}
)
###Beginning raw maplot###
output$rawmaplot=renderUI({
#facs <- pData(raw())$SampleID
facs <- pData(raw())$SampleID
nbfacs=length(facs)
plot_output_list <- lapply(1:nbfacs, function(i) {
plotname <- paste("plot", i, sep="")
plotOutput(plotname, height = 400, width = 600)
})
# Convert the list to a tagList - this is necessary for the list of items
# to display properly.
do.call(tagList, plot_output_list)
})
facs <- pData(raw())$SampleID
nbfacs=length(facs)
for (i in 1:nbfacs) {
local({
my_i <- i
plotname <- paste("plot", my_i, sep="")
output[[plotname]] <- renderPlot({
withProgress(message = 'Generating Raw Maplot', detail = paste0('Plot ', my_i, ' ...'), value = (my_i/nbfacs), {
MAplot(raw(),which=my_i,plotFun=smoothScatter,refSamples=c(1:nbfacs), main='', cex=2)
})
})
})
}
###end raw maplot###
output$rawbox=renderPlot(
{
par(mar=c(8,4,4,2))
# tempNames = gsub('_(HG-U133A_2).CEL','',pData(raw())$SampleID,fixed = T)
# boxplot(raw(), col=colors, which="all", main="Boxplots before normalization",las=2,names=tempNames)
boxplot(raw(), col=colors, which="all", main="Boxplots before normalization",las=2,names=pData(raw())$SampleID)
}
)
output$rle=renderPlot(
{
par(mar=c(8,4,4,2))
RLE(qc(), main="RLE plot",names=pData(raw())$SampleID, col=colors, las=2)
}
)
output$nuse=renderPlot(
{
par(mar=c(8,4,4,2))
NUSE(qc(), main="NUSE plot",names=pData(raw())$SampleID, col=colors, las=2)
}
)
output$rmahist=renderPlot(
{
hist(norm(), main ="Distribution after Normalization")
}
)
## MVAplot after normalization
output$normaplot=renderUI({
facs2 <- pData(norm())$SampleID
nbfacs2=length(facs2)
plot_output_list2 <- lapply(1:nbfacs2, function(i) {
plotname2 <- paste("plota", i, sep="")
plotOutput(plotname2, height = 400, width = 600)
})
# Convert the list to a tagList - this is necessary for the list of items
# to display properly.
do.call(tagList, plot_output_list2)
})
facs2 <- pData(norm())$SampleID
nbfacs2=length(facs2)
for (i in 1:nbfacs2) {
local({
my_i <- i
plotname2 <- paste("plota", my_i, sep="")
# MA plots are then used to visualize intensity-dependent ratio for each group
output[[plotname2]] <- renderPlot({
withProgress(message = 'Generating Normalized Maplot', detail = paste0('Plot ', my_i, ' ...'), value = my_i/nbfacs2, {
MAplot(norm(),which=my_i,plotFun=smoothScatter,refSamples=c(1:nbfacs2),main='', cex=2)
})
})
})
}
output$rmabox=renderPlot(
{
par(mar=c(8,4,4,2))
tempNames = gsub('_(HG-U133A_2).CEL','',pData(raw())$SampleID,fixed = T)
boxplot(norm(),col=colors, main="Boxplots after RMA normalization",las=2,names=tempNames)
}
)
## end mvaplat after normalization
## pca 3D
output$pca3d=renderPlotly(
{
withProgress(message = 'Generating PCA', detail = 'starting ...', value = 0.5, {
tedf= t(exprs(norm()))
#removes zero variances (issue with small sample sizes)
if (length(which(apply(tedf, 2, var)==0)) >= 0){
tedf = tedf[ , apply(tedf, 2, var) != 0]
}
pca=prcomp(tedf, scale. = T)
incProgress(amount = 0.25, detail = 'determining variance ...')
pc1.var=round(pca$sdev[1]^2/sum(pca$sdev^2)*100,2)
pc2.var=round(pca$sdev[2]^2/sum(pca$sdev^2)*100,2)
pc3.var=round(pca$sdev[3]^2/sum(pca$sdev^2)*100,2)
group.v=as.vector(pData(norm())$SampleID)
p = plot_ly(as.data.frame(pca$x[,1:3]), x = ~PC1, y = ~PC2, z = ~PC3,color = v$data$group, hoverinfo="text",
hovertext = ~group.v) %>%
add_markers() %>%
layout(scene = list(xaxis = list(title = paste0("PC1 (",pc1.var,"%)")),
yaxis = list(title = paste0("PC2 (",pc2.var,"%)")),
zaxis = list(title = paste0("PC3 (",pc3.var,"%)"))))
htmlwidgets::saveWidget(as_widget(p), "pca.html")
# save(p,file='/Users/valdezkm/Documents/GBM_cellLines_MicroArray/QC/p.RData')
p
})
}
)
output$heatmap=renderPlotly(
{
mat=as.matrix(dist(t(exprs(norm()))))
rownames(mat)=pData(norm())$SampleID
colnames(mat)=rownames(mat)
heatmaply(mat,margins = c(80,120,60,40),colorRampPalette(colors = c("red", "yellow")))
}
)
output$deg=DT::renderDataTable(DT::datatable(
{
#turn NumContrasts back into a number
k$all = cbind(paste0(k$k1, ' vs ', k$k2))
num = which(input$NumContrasts==k$all[,1])
dat = deg()$myCollapsedList[[num]]
dat = dat[,-3]
dat[,3:4] = format(dat[,3:4], scientific = TRUE)
if (is.na(input$pval) & is.na(input$fc)) {
dat
} else if (is.na(input$pval)) {
dat = dat[(abs(as.numeric(dat[,2])) >= input$fc),]
} else if (is.na(input$fc)) {
dat = dat[(as.numeric(dat[,3]) <= input$pval),]
} else {
dat = dat[(as.numeric(dat[,3]) <= input$pval & abs(as.numeric(dat[,2])) >= input$fc),]
dat
}
#ENTREZ link (slows down DEG output)
withProgress(message = 'Processing...', value = 0.75, {
dat$ENTREZ <- sapply(dat$ENTREZ, function(x)
toString(tags$a(href=paste0("https://www.ncbi.nlm.nih.gov/gene/", x), x)))
dat
})
# deg()[[1]]
}, caption =paste0("contrast: ",names(deg()$mylist)[num]), escape = FALSE
)
)
output$topUp=DT::renderDataTable(DT::datatable(
{
k$all = cbind(paste0(k$k1, ' vs ', k$k2))
num = which(input$NumContrasts==k$all[,1])
#deg()[[input$NumContrasts]]
#topUp = read.delim(paste0(input$ProjectID,'_',names(deg())[input$NumContrasts],"_Pathways_Up.txt"), sep = '\t', header = T)
#dev.off(which = plotly)
topUp = pathways()$up
if(is.na(input$pathPval)) {
topUp
} else {
topUp = topUp[(as.numeric(topUp[,5]) <= input$pathPval),]
}
topUp
} , caption=paste0("Pathways for the top 500 Upregulated Genes: ", names(deg()$mylist)[num]),
options = list(columnDefs = list(list(targets = 8,
render = JS("function(data, type, row, meta) {",
"return type === 'display' && data.length > 30 ?",
"'<span title=\"' + data + '\">' + data.substr(0, 30) + '...</span>' : data;",
"}")))), callback = JS('table.page(3).draw(false);')
,selection='single')
)
output$topDown=DT::renderDataTable(DT::datatable(
{
#callDEG = deg()[[input$NumContrasts]]
#topDw = read.delim(paste0(input$ProjectID,'_',names(deg())[input$NumContrasts],"_Pathways_Down.txt"), sep = '\t', header = T)
k$all = cbind(paste0(k$k1, ' vs ', k$k2))
num = which(input$NumContrasts==k$all[,1])
topDw = pathways()$dw
if (is.na(input$pathPval)) {
topDw
} else {
topDw = topDw[(as.numeric(topDw[,5]) <= input$pathPval),]
}
topDw
} , caption=paste0("Pathways for the top 500 Downregulated Genes: ", names(deg()$mylist)[num]),
options = list(columnDefs = list(list(targets = 8,
render = JS("function(data, type, row, meta) {",
"return type === 'display' && data.length > 30 ?",