Mercurial > repos > vandelj > giant_factor_generator
view src/VolcanoPlotsScript.R @ 2:1f4a30d19264 draft default tip
"planemo upload for repository https://github.com/juliechevalier/GIANT/tree/master commit 89b7d0e8812f53222691cffe29bd48be6519829d"
author | vandelj |
---|---|
date | Fri, 25 Sep 2020 08:53:02 +0000 |
parents | 4764dc6a1019 |
children |
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# R script to plot volcanos through Galaxy based GIANT tool # written by Jimmy Vandel # # initial.options <- commandArgs(trailingOnly = FALSE) file.arg.name <- "--file=" script.name <- sub(file.arg.name, "", initial.options[grep(file.arg.name, initial.options)]) script.basename <- dirname(script.name) source(file.path(script.basename, "utils.R")) source(file.path(script.basename, "getopt.R")) #addComment("Welcome R!") # setup R error handling to go to stderr options( show.error.messages=F, error = function () { cat(geterrmessage(), file=stderr() ); q( "no", 1, F ) } ) # we need that to not crash galaxy with an UTF8 error on German LC settings. loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8") loc <- Sys.setlocale("LC_NUMERIC", "C") #get starting time start.time <- Sys.time() options(stringAsfactors = FALSE, useFancyQuotes = FALSE) args <- commandArgs() # get options, using the spec as defined by the enclosed list. # we read the options from the default: commandArgs(TRUE). spec <- matrix(c( "statisticsFile", "i", 1, "character", "volcanoName" , "n", 1, "character", "pvalColumnName" , "p", 1, "character", "fdrColumnName" , "m", 1, "character", "fcColumnName" , "c", 1, "character", "fcKind","d", 1, "character", "fdrThreshold","s", 1, "double", "fcThreshold","e", 1, "double", "organismID","x",1,"character", "rowNameType","y",1,"character", "log", "l", 1, "character", "outputFile" , "o", 1, "character", "format", "f", 1, "character", "quiet", "q", 0, "logical"), byrow=TRUE, ncol=4) opt <- getopt(spec) # enforce the following required arguments if (is.null(opt$log)) { addComment("[ERROR]'log file' is required\n") q( "no", 1, F ) } addComment("[INFO]Start of R script",T,opt$log,display=FALSE) if (is.null(opt$statisticsFile)) { addComment("[ERROR]'statisticsFile' is required",T,opt$log) q( "no", 1, F ) } if (length(opt$pvalColumnName)==0 || length(opt$fdrColumnName)==0 || length(opt$fcColumnName)==0) { addComment("[ERROR]no selected columns",T,opt$log) q( "no", 1, F ) } if (length(opt$pvalColumnName)!=length(opt$fcColumnName) || length(opt$pvalColumnName)!=length(opt$fdrColumnName)) { addComment("[ERROR]different number of selected columns between p.val, adj-p.val and FC ",T,opt$log) q( "no", 1, F ) } if (is.null(opt$fcKind)) { addComment("[ERROR]'fcKind' is required",T,opt$log) q( "no", 1, F ) } if (is.null(opt$fdrThreshold)) { addComment("[ERROR]'FDR threshold' is required",T,opt$log) q( "no", 1, F ) } if (is.null(opt$fcThreshold)) { addComment("[ERROR]'FC threshold' is required",T,opt$log) q( "no", 1, F ) } if (is.null(opt$outputFile)) { addComment("[ERROR]'output file' is required",T,opt$log) q( "no", 1, F ) } if (is.null(opt$format)) { addComment("[ERROR]'output format' is required",T,opt$log) q( "no", 1, F ) } #demande si le script sera bavard verbose <- if (is.null(opt$quiet)) { TRUE }else{ FALSE } #paramètres internes addComment("[INFO]Parameters checked test mode !",T,opt$log,display=FALSE) addComment(c("[INFO]Working directory: ",getwd()),TRUE,opt$log,display=FALSE) addComment(c("[INFO]Command line: ",args),TRUE,opt$log,display=FALSE) #directory for plots dir.create(file.path(getwd(), "plotDir")) dir.create(file.path(getwd(), "plotLyDir")) #charge des packages silencieusement suppressPackageStartupMessages({ library("methods") library("biomaRt") library("ggplot2") library("plotly") library("stringr") }) #define some usefull variable nbVolcanosToPlot=length(opt$pvalColumnName) #load input file statDataMatrix=read.csv(file=file.path(getwd(), opt$statisticsFile),header=F,sep="\t",colClasses="character") #remove first colum to convert it as rownames rownames(statDataMatrix)=statDataMatrix[,1] statDataMatrix=statDataMatrix[,-1] #identify lines without adjusted p-value info (should contain the same content as rownames) and replace them with NA values FDRinfo=rep(TRUE,nbVolcanosToPlot) for(iVolcano in 1:nbVolcanosToPlot){ #input parameter should be None when adjusted p-val are not available if(opt$fdrColumnName[iVolcano]=="None"){ #content of the corresponding column should also be the same as rownames if(!all(statDataMatrix[,(iVolcano-1)*3+2]==rownames(statDataMatrix))){ addComment(c("[ERROR]It seems that input stat matrix contains adjusted p-values for volcano",iVolcano,"whereas input parameter indicates that not."),T,opt$log) q( "no", 1, F ) } FDRinfo[iVolcano]=FALSE statDataMatrix[,(iVolcano-1)*3+2]=NA } } if(is.data.frame(statDataMatrix)){ statDataMatrix=data.matrix(statDataMatrix) }else{ statDataMatrix=data.matrix(as.numeric(statDataMatrix)) } #check if available column number match with volcano requested number if(ncol(statDataMatrix)!=3*nbVolcanosToPlot){ addComment("[ERROR]Input file column number is different from requested volcano number",T,opt$log) q( "no", 1, F ) } #build global dataFrame with data and fill with p.val and log2(FC) and FDR dataFrame=data.frame(row.names = rownames(statDataMatrix)) #start with p-value dataFrame$p.value=statDataMatrix[,seq(1,nbVolcanosToPlot*3,3),drop=FALSE] #compute FDR if needed or just get available info dataFrame$adj_p.value=dataFrame$p.value for(iVolcano in 1:nbVolcanosToPlot){ #adjusted p-value are already computed if(FDRinfo[iVolcano]){ dataFrame$adj_p.value[,iVolcano]=statDataMatrix[,(iVolcano-1)*3+2,drop=FALSE] }else{ #adjusted p-value should be computed based on p-val using FDR dataFrame$adj_p.value[,iVolcano]=p.adjust(dataFrame$p.value[,iVolcano,drop=FALSE],"fdr") addComment(c("[INFO]Adjusted p-values are not available in input for volcano",iVolcano,", FDR approach will be used on available raw p-values"),T,opt$log) } } if(opt$fcKind=="FC"){ #we should transform as Log2FC dataFrame$coefficients=log2(statDataMatrix[,seq(3,nbVolcanosToPlot*3,3),drop=FALSE]) addComment(c("[INFO]FC are converted in log2(FC) for plotting"),T,opt$log) }else{ dataFrame$coefficients=statDataMatrix[,seq(3,nbVolcanosToPlot*3,3),drop=FALSE] } addComment(c("[INFO]Input data available for",nbVolcanosToPlot,"volcano(s) with",nrow(statDataMatrix),"rows"),T,opt$log) #plot VOLCANOs volcanoPerPage=1 logFCthreshold=log2(opt$fcThreshold) iToPlot=1 plotVector=list() volcanoNameList=c() for (iVolcano in 1:nbVolcanosToPlot){ if(nchar(opt$volcanoName[iVolcano])>0){ curentVolcanoName=opt$volcanoName[iVolcano] }else{ curentVolcanoName=paste(iVolcano,opt$pvalColumnName[iVolcano],sep="_") } #keep only rows without NA for p-val, adjusted p-val and coeff pValToPlot=dataFrame$p.value[,iVolcano] fdrToPlot=dataFrame$adj_p.value[,iVolcano] coeffToPlot=dataFrame$coefficients[,iVolcano] rowToRemove=unique(c(which(is.na(pValToPlot)),which(is.na(fdrToPlot)),which(is.na(coeffToPlot)))) if(length(rowToRemove)>0){ pValToPlot=pValToPlot[-rowToRemove] fdrToPlot=fdrToPlot[-rowToRemove] coeffToPlot=coeffToPlot[-rowToRemove] } addComment(c("[INFO]For",curentVolcanoName,"volcano,",length(rowToRemove),"rows are discarded due to NA values,",length(pValToPlot),"remaining rows."),T,opt$log) #save volcano name volcanoNameList=c(volcanoNameList,curentVolcanoName) #remove characters possibly troubling volcanoFileName=iVolcano #define the log10(p-val) threshold corresponding to FDR threshold fixed by user probeWithLowFDR=-log10(pValToPlot[which(fdrToPlot<=opt$fdrThreshold)]) pvalThresholdFDR=NULL if(length(probeWithLowFDR)>0)pvalThresholdFDR=min(probeWithLowFDR) #get significant points over FC and FDR thresholds significativePoints=intersect(which(abs(coeffToPlot)>=logFCthreshold),which(fdrToPlot<=opt$fdrThreshold)) #to reduce size of html plot, we keep 20000 points maximum sampled amongst genes with pval>=33%(pval) and abs(log2(FC))<=66%(abs(log2(FC))) htmlPointsToRemove=intersect(which(abs(coeffToPlot)<=quantile(abs(coeffToPlot),c(0.66))),which(pValToPlot>=quantile(abs(pValToPlot),c(0.33)))) if(length(htmlPointsToRemove)>20000){ htmlPointsToRemove=setdiff(htmlPointsToRemove,sample(htmlPointsToRemove,20000)) }else{ htmlPointsToRemove=c() } xMinLimPlot=min(coeffToPlot)-0.2 xMaxLimPlot=max(coeffToPlot)+0.2 yMaxLimPlot= max(-log10(pValToPlot))+0.2 if(length(significativePoints)>0){ dataSignifToPlot=data.frame(pval=-log10(pValToPlot[significativePoints]),FC=coeffToPlot[significativePoints],description=paste(names(coeffToPlot[significativePoints]),"\n","FC: " , round(2^coeffToPlot[significativePoints],2) , " | Adjusted p-val: ",prettyNum(fdrToPlot[significativePoints],digits=4), sep="")) #to test if remains any normal points to draw if(length(significativePoints)<length(pValToPlot)){ dataToPlot=data.frame(pval=-log10(pValToPlot[-significativePoints]),FC=coeffToPlot[-significativePoints],description=paste("FC: " , round(2^coeffToPlot[-significativePoints],2) , " | Adjusted p-val: ",prettyNum(fdrToPlot[-significativePoints],digits=4), sep="")) }else{ dataToPlot=data.frame(pval=0,FC=0,description="null") } }else{ dataToPlot=data.frame(pval=-log10(pValToPlot),FC=coeffToPlot,description=paste("FC: " , round(2^coeffToPlot,2) , " | Adjusted p-val: ",prettyNum(fdrToPlot,digits=4), sep="")) } ##traditional plot p <- ggplot(data=dataToPlot, aes(x=FC, y=pval)) + geom_point() + theme_bw() + ggtitle(curentVolcanoName) + ylab(label="-Log10(p-val)") + xlab(label="Log2 Fold Change") + theme(panel.border=element_blank(),plot.title = element_text(hjust = 0.5),legend.position="none") if(logFCthreshold!=0) p <- p + geom_vline(xintercept=-logFCthreshold, color="salmon",linetype="dotted", size=1) + geom_vline(xintercept=logFCthreshold, color="salmon",linetype="dotted", size=1) + geom_text(data.frame(text=c(paste(c("log2(1/FC=",opt$fcThreshold,")"),collapse=""),paste(c("log2(FC=",opt$fcThreshold,")"),collapse="")),x=c(-logFCthreshold,logFCthreshold),y=c(0,0)),mapping=aes(x=x, y=y, label=text), size=4, angle=90, vjust=-0.4, hjust=0, color="salmon") if(!is.null(pvalThresholdFDR)) p <- p + geom_hline(yintercept=pvalThresholdFDR, color="skyblue1",linetype="dotted", size=0.5) + geom_text(data.frame(text=c(paste(c("Adjusted pval limit(",opt$fdrThreshold,")"),collapse="")),x=c(xMinLimPlot),y=c(pvalThresholdFDR)),mapping=aes(x=x, y=y, label=text), size=4, vjust=0, hjust=0, color="skyblue3") if(length(significativePoints)>0)p <- p + geom_point(data=dataSignifToPlot,aes(colour=description)) ##interactive plot if(length(htmlPointsToRemove)>0){ pointToRemove=union(htmlPointsToRemove,significativePoints) #to test if it remains any normal points to draw if(length(pointToRemove)<length(pValToPlot)){ dataToPlot=data.frame(pval=-log10(pValToPlot[-pointToRemove]),FC=coeffToPlot[-pointToRemove],description=paste("FC: " , round(2^coeffToPlot[-pointToRemove],2) , " | Adjusted p-val: ", prettyNum(fdrToPlot[-pointToRemove],digits=4), sep="")) }else{ dataToPlot=data.frame(pval=0,FC=0,description="null") } } if((nrow(dataToPlot)+length(significativePoints))>40000)addComment(c("[WARNING]For",curentVolcanoName,"volcano, numerous points to plot(",nrow(dataToPlot)+nrow(dataSignifToPlot),"), resulting volcano could be heavy, using more stringent thresholds could be helpful."),T,opt$log) phtml <- plot_ly(data=dataToPlot, x=~FC, y=~pval,type="scatter", mode="markers",showlegend = FALSE, marker = list(color="gray",opacity=0.5), text=~description, hoverinfo="text") %>% layout(title = curentVolcanoName[iVolcano],xaxis=list(title="Log2 Fold Change",showgrid=TRUE, zeroline=FALSE),yaxis=list(title="-Log10(p-val)", showgrid=TRUE, zeroline=FALSE)) if(length(significativePoints)>0) phtml=add_markers(phtml,data=dataSignifToPlot, x=~FC, y=~pval, mode="markers" , marker=list( color=log10(abs(dataSignifToPlot$FC)*dataSignifToPlot$pval),colorscale='Rainbow'), text=~description, hoverinfo="text", inherit = FALSE) %>% hide_colorbar() if(logFCthreshold!=0){ phtml=add_trace(phtml,x=c(-logFCthreshold,-logFCthreshold), y=c(0,yMaxLimPlot), type="scatter", mode = "lines", line=list(color="coral",dash="dash"), hoverinfo='none', showlegend = FALSE,inherit = FALSE) phtml=add_annotations(phtml,x=-logFCthreshold,y=0,xref = "x",yref = "y",text = paste(c("log2(1/FC=",opt$fcThreshold,")"),collapse=""),xanchor = 'right',showarrow = F,textangle=270,font=list(color="coral")) phtml=add_trace(phtml,x=c(logFCthreshold,logFCthreshold), y=c(0, yMaxLimPlot), type="scatter", mode = "lines", line=list(color="coral",dash="dash"), hoverinfo='none', showlegend = FALSE,inherit = FALSE) phtml=add_annotations(phtml,x=logFCthreshold,y=0,xref = "x",yref = "y",text = paste(c("log2(FC=",opt$fcThreshold,")"),collapse=""),xanchor = 'right',showarrow = F,textangle=270,font=list(color="coral")) } if(!is.null(pvalThresholdFDR)){ phtml=add_trace(phtml,x=c(xMinLimPlot,xMaxLimPlot), y=c(pvalThresholdFDR,pvalThresholdFDR), type="scatter", mode = "lines", line=list(color="cornflowerblue",dash="dash"), hoverinfo='none', showlegend = FALSE,inherit = FALSE) phtml=add_annotations(phtml,x=xMinLimPlot,y=pvalThresholdFDR+0.1,xref = "x",yref = "y",text = paste(c("Adjusted pval limit(",opt$fdrThreshold,")"),collapse=""),xanchor = 'left',showarrow = F,font=list(color="cornflowerblue")) } plotVector[[length(plotVector)+1]]=p #save plotly files pp <- ggplotly(phtml) htmlwidgets::saveWidget(as_widget(pp), paste(c(file.path(getwd(), "plotLyDir"),"/Volcanos_",volcanoFileName,".html"),collapse=""),selfcontained = F) if(iVolcano==nbVolcanosToPlot || length(plotVector)==volcanoPerPage){ #plot and close the actual plot if(opt$format=="pdf"){ pdf(paste(c("./plotDir/Volcanos_",volcanoFileName,".pdf"),collapse=""))}else{ png(paste(c("./plotDir/Volcanos_",volcanoFileName,".png"),collapse="")) } multiplot(plotlist=plotVector,cols=1) dev.off() if(iVolcano<nbVolcanosToPlot){ #prepare for a new ploting file if necessary plotVector=list() iToPlot=iToPlot+1 } } } remove(dataToPlot,dataSignifToPlot) addComment("[INFO]Volcanos drawn",T,opt$log,T,display=FALSE) #now add anotation infos about genes rowItemInfo=NULL if(!is.null(opt$rowNameType) && !is.null(opt$organismID)){ ##get gene information from BioMart #if(!require("biomaRt")){ # source("https://bioconductor.org/biocLite.R") # biocLite("biomaRt") #} ensembl_hs_mart <- useMart(biomart="ensembl", dataset=opt$organismID) ensembl_df <- getBM(attributes=c(opt$rowNameType,"description"),mart=ensembl_hs_mart) rowItemInfo=ensembl_df[which(ensembl_df[,1]!=""),2] rowItemInfo=unlist(lapply(rowItemInfo,function(x)substr(unlist(strsplit(x," \\[Source"))[1],1,30))) names(rowItemInfo)=ensembl_df[which(ensembl_df[,1]!=""),1] } #filter out genes with higher p-values for all comparisons genesToKeep=names(which(apply(dataFrame$adj_p.value,1,function(x)length(which(x<=opt$fdrThreshold))>0))) #filter out genes with lower FC for all comparisons genesToKeep=intersect(genesToKeep,names(which(apply(dataFrame$coefficients,1,function(x)length(which(abs(x)>=logFCthreshold))>0)))) if(length(genesToKeep)>0){ dataFrameNew=data.frame(row.names=genesToKeep) dataFrameNew$adj_p.value=matrix(dataFrame$adj_p.value[genesToKeep,,drop=FALSE],ncol=ncol(dataFrame$adj_p.value)) rownames(dataFrameNew$adj_p.value)=genesToKeep colnames(dataFrameNew$adj_p.value)=colnames(dataFrame$p.value) dataFrameNew$p.value=matrix(dataFrame$p.value[genesToKeep,,drop=FALSE],ncol=ncol(dataFrame$p.value)) rownames(dataFrameNew$p.value)=genesToKeep colnames(dataFrameNew$p.value)=colnames(dataFrame$adj_p.value) dataFrameNew$coefficients=matrix(dataFrame$coefficients[genesToKeep,,drop=FALSE],ncol=ncol(dataFrame$coefficients)) rownames(dataFrameNew$coefficients)=genesToKeep colnames(dataFrameNew$coefficients)=colnames(dataFrame$adj_p.value) dataFrame=dataFrameNew rm(dataFrameNew) }else{ addComment("[WARNING]No significative genes",T,opt$log,display=FALSE) } addComment("[INFO]Significant genes filtering done",T,opt$log,T,display=FALSE) #plot VennDiagramm for genes below threshold between comparisons #t=apply(dataFrame$adj_p.value[,1:4],2,function(x)names(which(x<=opt$threshold))) #get.venn.partitions(t) #vennCounts(dataFrame$adj_p.value[,1:4]<=opt$threshold) #make a simple sort genes based only on the first comparison #newOrder=order(dataFrame$adj_p.value[,1]) #dataFrame$adj_p.value=dataFrame$adj_p.value[newOrder,] #alternative sorting strategy based on the mean gene rank over all comparisons if(length(genesToKeep)>1){ currentRank=rep(0,nrow(dataFrame$adj_p.value)) for(iVolcano in 1:ncol(dataFrame$adj_p.value)){ currentRank=currentRank+rank(dataFrame$adj_p.value[,iVolcano]) } currentRank=currentRank/ncol(dataFrame$adj_p.value) newOrder=order(currentRank) rownames(dataFrame)=rownames(dataFrame)[newOrder] dataFrame$adj_p.value=matrix(dataFrame$adj_p.value[newOrder,],ncol=ncol(dataFrame$adj_p.value)) rownames(dataFrame$adj_p.value)=rownames(dataFrame$p.value)[newOrder] colnames(dataFrame$adj_p.value)=colnames(dataFrame$p.value) dataFrame$p.value=matrix(dataFrame$p.value[newOrder,],ncol=ncol(dataFrame$p.value)) rownames(dataFrame$p.value)=rownames(dataFrame$adj_p.value) colnames(dataFrame$p.value)=colnames(dataFrame$adj_p.value) dataFrame$coefficients=matrix(dataFrame$coefficients[newOrder,],ncol=ncol(dataFrame$coefficients)) rownames(dataFrame$coefficients)=rownames(dataFrame$adj_p.value) colnames(dataFrame$coefficients)=colnames(dataFrame$adj_p.value) } #formating output matrix depending on genes to keep if(length(genesToKeep)==0){ outputData=matrix(0,ncol=ncol(dataFrame$adj_p.value)*4+2,nrow=3) outputData[1,]=c("X","X",rep(volcanoNameList,each=4)) outputData[2,]=c("X","X",rep(c("p-val","Adjusted.p-val","FC","log2(FC)"),ncol(dataFrame$adj_p.value))) outputData[,1]=c("Volcano","Gene","noGene") outputData[,2]=c("Comparison","Info","noInfo") }else{ if(length(genesToKeep)==1){ outputData=matrix(0,ncol=ncol(dataFrame$adj_p.value)*4+2,nrow=3) outputData[1,]=c("X","X",rep(volcanoNameList,each=4)) outputData[2,]=c("X","X",rep(c("p-val","Adjusted.p-val","FC","log2(FC)"),ncol(dataFrame$adj_p.value))) outputData[,1]=c("Volcano","Gene",genesToKeep) outputData[,2]=c("Comparison","Info","na") if(!is.null(rowItemInfo))outputData[3,2]=rowItemInfo[genesToKeep] outputData[3,seq(3,ncol(outputData),4)]=prettyNum(dataFrame$p.value,digits=4) outputData[3,seq(4,ncol(outputData),4)]=prettyNum(dataFrame$adj_p.value,digits=4) outputData[3,seq(5,ncol(outputData),4)]=prettyNum(2^dataFrame$coefficients,digits=4) outputData[3,seq(6,ncol(outputData),4)]=prettyNum(dataFrame$coefficients,digits=4) }else{ #format matrix to be correctly read by galaxy (move headers in first column and row) outputData=matrix(0,ncol=ncol(dataFrame$adj_p.value)*4+2,nrow=nrow(dataFrame$adj_p.value)+2) outputData[1,]=c("X","X",rep(volcanoNameList,each=4)) outputData[2,]=c("X","X",rep(c("p-val","Adjusted.p-val","FC","log2(FC)"),ncol(dataFrame$adj_p.value))) outputData[,1]=c("Volcano","Gene",rownames(dataFrame$adj_p.value)) outputData[,2]=c("Comparison","Info",rep("na",nrow(dataFrame$adj_p.value))) if(!is.null(rowItemInfo))outputData[3:nrow(outputData),2]=rowItemInfo[rownames(dataFrame$adj_p.value)] outputData[3:nrow(outputData),seq(3,ncol(outputData),4)]=prettyNum(dataFrame$p.value,digits=4) outputData[3:nrow(outputData),seq(4,ncol(outputData),4)]=prettyNum(dataFrame$adj_p.value,digits=4) outputData[3:nrow(outputData),seq(5,ncol(outputData),4)]=prettyNum(2^dataFrame$coefficients,digits=4) outputData[3:nrow(outputData),seq(6,ncol(outputData),4)]=prettyNum(dataFrame$coefficients,digits=4) } } addComment("[INFO]Formated output",T,opt$log,display=FALSE) #write output results write.table(outputData,file=opt$outputFile,quote=FALSE,sep="\t",col.names = F,row.names = F) end.time <- Sys.time() addComment(c("[INFO]Total execution time for R script:",as.numeric(end.time - start.time,units="mins"),"mins"),T,opt$log,display=FALSE) addComment("[INFO]End of R script",T,opt$log,display=FALSE) printSessionInfo(opt$log) #sessionInfo()