# HG changeset patch # User genouest # Date 1524123871 14400 # Node ID 877d2be25a6a020cd70e6c331711e80ef8773037 # Parent 6bbc90a11c3f2dfa5273acbca4bfc3b113edc547 planemo upload for repository https://github.com/genouest/galaxy-tools/tree/master/tools/askor commit 994ecff7807bb0eb9dac740d67ad822415b0b464 diff -r 6bbc90a11c3f -r 877d2be25a6a AskoR.R --- a/AskoR.R Wed Apr 18 06:26:17 2018 -0400 +++ b/AskoR.R Thu Apr 19 03:44:31 2018 -0400 @@ -278,13 +278,17 @@ colnames(ASKOlist$stat.table)[colnames(ASKOlist$stat.table)=="contrast"] <- paste("measured_in", "Contrast", sep="@") # header formatting for askomics o <- order(ASKOlist$stat.table$FDR) # ordering genes by FDR value ASKOlist$stat.table<-ASKOlist$stat.table[o,] + # dir.create(parameters$out_dir) write.table(ASKOlist$stat.table,paste0(parameters$out_dir,"/", parameters$organism, contrasko, ".txt"), # sep=parameters$sep, col.names = T, row.names = F, quote=FALSE) - + + if(parameters$heatmap==TRUE){ - cpm_gstats<-cpm(dge, log=TRUE)[o,][1:parameters$numhigh,] + numhigh=parameters$numhigh + if (numhigh>length(o)) {numhigh=length(o)} + cpm_gstats<-cpm(dge, log=TRUE)[o,][1:numhigh,] heatmap.2(cpm_gstats, cexRow=0.5, cexCol=0.8, scale="row", labCol=dge$samples$Name, xlab=contrast, Rowv = FALSE, dendrogram="col") } @@ -362,6 +366,7 @@ select_counts<-row.names(samples) #countT<-count[,c(parameters$col_counts:length(colnames(count)))] countT<-count[,select_counts] + #print(countT) dge<-DGEList(counts=countT, samples=samples) # if(is.null(parameters$select_sample)==FALSE){ # slct<-grep(parameters$select_sample, colnames(countT)) @@ -480,7 +485,8 @@ } GEnorm <- function(filtered_GE, parameters){ - filtered_cpm <- cpm(filtered_GE, log=TRUE) #nouveau calcul Cpm sur donn?es filtr?es, si log=true alors valeurs cpm en log2 + filtered_cpm=log2(1000000*filtered_GE$counts/colSums(filtered_GE$counts)) + #filtered_cpm <- cpm(filtered_GE, log=TRUE, normalized.lib.sizes=TRUE) #nouveau calcul Cpm sur donn?es filtr?es, si log=true alors valeurs cpm en log2 colnames(filtered_cpm)<-rownames(filtered_GE$samples) boxplot(filtered_cpm, col=filtered_GE$samples$color, #boxplot des scores cpm non normalis?s @@ -509,7 +515,7 @@ cormat<-cor(lcpm) # color<- colorRampPalette(c("yellow", "white", "green"))(20) color<-colorRampPalette(c("black","red","yellow","white"),space="rgb")(28) - heatmap(cormat, col=color, symm=TRUE,RowSideColors =as.character(dge$samples$color), ColSideColors = as.character(dge$samples$color)) + heatmap.2(cormat, col=color, symm=TRUE,RowSideColors =as.character(dge$samples$color), ColSideColors = as.character(dge$samples$color)) #MDS mds <- cmdscale(dist(t(lcpm)),k=3, eig=TRUE) eigs<-round((mds$eig)*100/sum(mds$eig[mds$eig>0]),2) diff -r 6bbc90a11c3f -r 877d2be25a6a AskoR_DE.R --- a/AskoR_DE.R Wed Apr 18 06:26:17 2018 -0400 +++ b/AskoR_DE.R Thu Apr 19 03:44:31 2018 -0400 @@ -2,7 +2,7 @@ source(paste0(askor_path,"/AskoR.R")) ############################################## -## Parameters ## +## Parameters ## ############################################## parameters<-Asko_start() @@ -31,7 +31,7 @@ cat("Total number of genes : ", dim(data$dge$counts)[1], "\n") cat("Total number of samples : ", dim(data$dge$counts)[2], "\n") cat("summary of CPM by samples\n") -summary(cpm(data$dge)) +summary(cpm(data$dge, normalized.lib.sizes=FALSE)) pdf(parameters$output_pdf) asko_data<-asko3c(data) cat("Filtering genes with more than ", parameters$threshold_cpm, " CPM in ",parameters$replicate_cpm,"samples\n") @@ -42,3 +42,5 @@ cat("Statistical analysis\n") DEanalysis(asko_norm,data, asko_data,parameters) dev.off() + + diff -r 6bbc90a11c3f -r 877d2be25a6a askor_de.xml --- a/askor_de.xml Wed Apr 18 06:26:17 2018 -0400 +++ b/askor_de.xml Thu Apr 19 03:44:31 2018 -0400 @@ -59,7 +59,7 @@ #end if ]]> - +
diff -r 6bbc90a11c3f -r 877d2be25a6a test-data/out.pdf Binary file test-data/out.pdf has changed