--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/topGO_enrichment.R	Tue Dec 18 10:06:00 2018 -0500
@@ -0,0 +1,352 @@
+options(warn=-1)  #TURN OFF WARNINGS !!!!!!
+
+suppressMessages(library(ggplot2))
+suppressMessages(library(topGO))
+
+get_args <- function(){
+  
+  ## Collect arguments
+  args <- commandArgs(TRUE)
+  
+  ## Default setting when no arguments passed
+  if(length(args) < 1) {
+    args <- c("--help")
+  }
+  
+  ## Help section
+  if("--help" %in% args) {
+    cat("Pathview R script
+    Arguments:
+      --help                  Print this test
+      --input_type             
+      --onto
+      --option
+      --correction
+      --threshold
+      --text
+      --plot
+      --column
+      --geneuniverse
+      --header
+
+      Example:
+      Rscript --vanilla enrichment_v3.R --inputtype=tabfile (or copypaste) --input=file.txt --ontology='BP/CC/MF' --option=option
+      (e.g : classic/elim...) --threshold=threshold --correction=correction --textoutput=text --barplotoutput=barplot --dotplotoutput=dotplot 
+      --column=column --geneuniver=human \n\n")
+    
+    q(save="no")
+  }
+  
+  parseArgs <- function(x) strsplit(sub("^--", "", x), "=")
+  argsDF <- as.data.frame(do.call("rbind", parseArgs(args)))
+  args <- as.list(as.character(argsDF$V2))
+  names(args) <- argsDF$V1
+  
+  return(args)
+}
+
+read_file <- function(path,header){
+  file <- try(read.csv(path,header=header, sep="\t",stringsAsFactors = FALSE, quote="\"", check.names = F),silent=TRUE)
+  if (inherits(file,"try-error")){
+    stop("File not found !")
+  }else{
+    return(file)
+  }
+}
+
+get_list_from_cp <-function(list){
+  list = gsub(";"," ",list)
+  list = strsplit(list, "[ \t\n]+")[[1]]
+  list = list[list != ""]    #remove empty entry
+  list = gsub("-.+", "", list)  #Remove isoform accession number (e.g. "-2")
+  return(list)
+}
+
+check_ens_ids <- function(vector) {
+  ens_pattern = "^(ENS[A-Z]+[0-9]{11}|[A-Z]{3}[0-9]{3}[A-Za-z](-[A-Za-z])?|CG[0-9]+|[A-Z0-9]+\\.[0-9]+|YM[A-Z][0-9]{3}[a-z][0-9])$"
+  return(grepl(ens_pattern,vector))
+}
+
+str2bool <- function(x){
+  if (any(is.element(c("t","true"),tolower(x)))){
+    return (TRUE)
+  }else if (any(is.element(c("f","false"),tolower(x)))){
+    return (FALSE)
+  }else{
+    return(NULL)
+  }
+}
+
+# Some libraries such as GOsummaries won't be able to treat the values such as
+# "< 1e-30" produced by topGO. As such it is important to delete the < char
+# with the deleteInfChar function. Nevertheless the user will have access to the original results in the text output.
+deleteInfChar = function(values){
+  
+  lines = grep("<",values)
+  if (length(lines)!=0){
+    for (line in lines){
+      values[line]=gsub("<","",values[line])
+    }
+  }
+  return(values)
+}
+
+corrMultipleTesting = function(result, myGOdata,correction,threshold){
+  
+  # adjust for multiple testing
+  if (correction!="none"){	
+    # GenTable : transforms the result object into a list. Filters can be applied
+    # (e.g : with the topNodes argument, to get for instance only the n first
+    # GO terms with the lowest pvalues), but as we want to  apply a correction we
+    # take all the GO terms, no matter their pvalues 
+    allRes <- GenTable(myGOdata, test = result, orderBy = "result", ranksOf = "result",topNodes=length(attributes(result)$score))
+    # Some pvalues given by topGO are not numeric (e.g : "<1e-30). As such, these
+    # values are converted to 1e-30 to be able to correct the pvalues 
+    pvaluestmp = deleteInfChar(allRes$test)
+    
+    # the correction is done from the modified pvalues  
+    allRes$qvalues = p.adjust(pvaluestmp, method = as.character(correction), n = length(pvaluestmp))
+    allRes = as.data.frame(allRes)
+    
+    # Rename the test column by pvalues, so that is more explicit
+    nb = which(names(allRes) %in% c("test"))
+    
+    names(allRes)[nb] = "pvalues"
+    
+    allRes = allRes[which(as.numeric(allRes$pvalues) <= threshold),]
+    if (length(allRes$pvalues)==0){
+      print("Threshold was too stringent, no GO term found with pvalue equal or lesser than the threshold value")
+      return(NULL)
+    }
+    allRes = allRes[order(allRes$qvalues),]
+  }
+  
+  if (correction=="none"){
+    # get all the go terms under user threshold 
+    mysummary <- summary(attributes(result)$score <= threshold)
+    numsignif <- as.integer(mysummary[[3]])
+    # get all significant nodes 
+    allRes <- GenTable(myGOdata, test = result, orderBy = "result", ranksOf = "result",topNodes=numsignif)
+    
+    
+    allRes = as.data.frame(allRes)
+    # Rename the test column by pvalues, so that is more explicit
+    nb = which(names(allRes) %in% c("test"))
+    names(allRes)[nb] = "pvalues"
+    if (numsignif==0){
+      
+      print("Threshold was too stringent, no GO term found with pvalue equal or lesser than the threshold value")
+      return(NULL)
+    }
+    
+    allRes = allRes[order(allRes$pvalues),] 
+  } 
+  
+  return(allRes)  
+}
+
+# roundValues will simplify the results by rounding down the values. For instance 1.1e-17 becomes 1e-17
+roundValues = function(values){
+  for (line in 1:length(values)){
+    values[line]=as.numeric(gsub(".*e","1e",as.character(values[line])))
+  }
+  return(values)
+}
+
+createDotPlot = function(data, onto){
+  
+  values  = deleteInfChar(data$pvalues)
+  values = roundValues(values)
+  values = as.numeric(values)
+  
+  geneRatio = data$Significant/data$Annotated
+  goTerms = data$Term
+  count = data$Significant
+  
+  labely = paste("GO terms",onto,sep=" ")
+  ggplot(data,aes(x=geneRatio,y=goTerms, color=values,size=count)) +geom_point( ) + scale_colour_gradientn(colours=c("red","violet","blue")) + xlab("Gene Ratio") + ylab(labely) + labs(color="p-values\n" ) 
+  ggsave("dotplot.png", device = "png", dpi = 320, limitsize = TRUE, width = 15, height = 15, units="cm")
+}
+
+createBarPlot = function(data, onto){
+  
+  
+  values  = deleteInfChar(data$pvalues)
+  values = roundValues(values)
+  values = as.numeric(values)
+  
+  goTerms = data$Term
+  count = data$Significant
+  
+  labely = paste("GO terms",onto,sep=" ")
+  ggplot(data, aes(x=goTerms, y=count,fill=values,scale(scale = 0.5))) + ylab("Gene count") + xlab(labely) +geom_bar(stat="identity") + scale_fill_gradientn(colours=c("red","violet","blue")) + coord_flip() + labs(fill="p-values\n") 
+  ggsave("barplot.png", device = "png", dpi = 320, limitsize = TRUE, width = 15, height = 15, units="cm")
+}
+
+# Produce the different outputs
+createOutputs = function(result, cut_result,text, barplot, dotplot, onto){
+  
+  if (is.null(result)){
+    if (text){
+      err_msg = "None of the input ids can be found in the org package data, enrichment analysis cannot be realized. \n The inputs ids probably either have no associated GO terms or are not ENSG identifiers (e.g : ENSG00000012048)."
+      write.table(err_msg, file='result', quote=FALSE, sep='\t', col.names = T, row.names = F)
+    }
+    if (barplot){
+      png(filename="barplot.png")
+      plot.new()
+      #text(0,0,err_msg)
+      dev.off()
+    }
+    if (dotplot){
+      png(filename="dotplot.png")
+      plot.new()
+      #text(0,0,err_msg)
+      dev.off()
+    }
+    opt <- options(show.error.messages=FALSE)
+    on.exit(options(opt))
+    stop("null result")
+  }
+  
+  if (is.null(cut_result)){
+    if (text){
+      err_msg = "Threshold was too stringent, no GO term found with pvalue equal or lesser than the threshold value."
+      write.table(err_msg, file='result', quote=FALSE, sep='\t', col.names = T, row.names = F)
+    }
+    if (barplot){
+      png(filename="barplot.png")
+      plot.new()
+      text(0,0,err_msg)
+      dev.off()
+    }
+    if (dotplot){
+      png(filename="dotplot.png")
+      plot.new()
+      text(0,0,err_msg)
+      dev.off()
+    }
+    opt <- options(show.error.messages=FALSE)
+    on.exit(options(opt))
+    stop("null cut_result")
+  }
+  
+  if (text){
+    write.table(cut_result, file='result', quote=FALSE, sep='\t', col.names = T, row.names = F)
+  }
+  
+  if (barplot){
+    createBarPlot(cut_result, onto)
+  }
+  
+  if (dotplot){
+    createDotPlot(cut_result, onto)
+  }
+}
+
+# Launch enrichment analysis and return result data from the analysis or the null
+# object if the enrichment could not be done.
+goEnrichment = function(geneuniverse,sample,background_sample,onto){
+  
+  if (is.null(background_sample)){
+    xx = annFUN.org(onto,mapping=geneuniverse,ID="ensembl")   # get all the GO terms of the corresponding ontology (BP/CC/MF) and all their associated ensembl ids according to the org package
+    allGenes = unique(unlist(xx))                             # check if the genes given by the user can be found in the org package (gene universe), that is in allGenes 
+  } else {
+    allGenes = background_sample
+  }
+  
+  if (length(intersect(sample,allGenes))==0){
+    print("None of the input ids can be found in the org package data, enrichment analysis cannot be realized. \n The inputs ids probably have no associated GO terms.")
+    return(c(NULL,NULL))
+  }
+  
+  geneList = factor(as.integer(allGenes %in% sample)) 
+  if (length(levels(geneList)) == 1 ){
+    stop("All or none of the background genes are found in tested genes dataset, enrichment analysis can't be done")
+  }
+  names(geneList) <- allGenes
+  
+  #topGO enrichment 
+  
+  # Creation of a topGOdata object
+  # It will contain : the list of genes of interest, the GO annotations and the GO hierarchy
+  # Parameters : 
+  # ontology : character string specifying the ontology of interest (BP, CC, MF)
+  # allGenes : named vector of type numeric or factor 
+  # annot : tells topGO how to map genes to GO annotations.
+  # argument not used here : nodeSize : at which minimal number of GO annotations
+  # do we consider a gene  
+  
+  myGOdata = new("topGOdata", description="SEA with TopGO", ontology=onto, allGenes=geneList,  annot = annFUN.org, mapping=geneuniverse,ID="ensembl")
+  
+  # Performing enrichment tests
+  result <- runTest(myGOdata, algorithm=option, statistic="fisher")
+  return(c(result,myGOdata))	
+}
+
+args <- get_args()
+
+#save(args,file="/home/dchristiany/proteore_project/ProteoRE/tools/topGO/args.rda")
+#load("/home/dchristiany/proteore_project/ProteoRE/tools/topGO/args.rda")
+
+input_type = args$inputtype
+input = args$input
+onto = args$ontology
+option = args$option
+correction = args$correction
+threshold = as.numeric(args$threshold)
+text = str2bool(args$textoutput)
+barplot = "barplot" %in% unlist(strsplit(args$plot,","))
+dotplot = "dotplot" %in% unlist(strsplit(args$plot,","))
+column = as.numeric(gsub("c","",args$column))
+geneuniverse = args$geneuniverse
+header = str2bool(args$header)
+background = str2bool(args$background)
+if (background){
+  background_genes = args$background_genes
+  background_input_type = args$background_input_type
+  background_header = str2bool(args$background_header)
+  background_column = as.numeric(gsub("c","",args$background_column))
+}
+
+#get input
+if (input_type=="copy_paste"){
+  sample <- get_list_from_cp(input)
+} else if (input_type=="file"){
+  tab=read_file(input,header)
+  sample = trimws(unlist(strsplit(tab[,column],";")))
+}
+
+#check of ENS ids
+if (! any(check_ens_ids(sample))){
+  print("no ensembl gene ids found in your ids list, please check your IDs in input or the selected column of your input file")
+  stop()
+}
+
+#get input if background genes
+if (background){
+  if (background_input_type=="copy_paste"){
+    background_sample <- get_list_from_cp(background_genes)
+  } else if (background_input_type=="file"){
+    background_tab=read_file(background_genes,background_header)
+    background_sample = unique(trimws(unlist(strsplit(background_tab[,background_column],";"))))
+  }
+  #check of ENS ids
+  if (! any(check_ens_ids(background_sample))){
+    print("no ensembl gene ids found in your background ids list, please check your IDs in input or the selected column of your input file")
+    stop()
+  }
+} else {
+  background_sample=NULL
+}
+
+# Launch enrichment analysis
+allresult = suppressMessages(goEnrichment(geneuniverse,sample,background_sample,onto))
+result = allresult[1][[1]]
+myGOdata = allresult[2][[1]]
+if (!is.null(result)){
+  cut_result = corrMultipleTesting(result,myGOdata, correction,threshold) # Adjust the result with a multiple testing correction or not and with the user, p-value cutoff
+}else{
+  cut_result=NULL
+}
+
+createOutputs(result, cut_result,text, barplot, dotplot, onto)