Mercurial > repos > genouest > askor_de
comparison AskoR.R @ 2:877d2be25a6a draft default tip
planemo upload for repository https://github.com/genouest/galaxy-tools/tree/master/tools/askor commit 994ecff7807bb0eb9dac740d67ad822415b0b464
author | genouest |
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date | Thu, 19 Apr 2018 03:44:31 -0400 |
parents | ceef9bc6bbc7 |
children |
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1:6bbc90a11c3f | 2:877d2be25a6a |
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276 print(table(ASKO_stat$Expression)) | 276 print(table(ASKO_stat$Expression)) |
277 colnames(ASKOlist$stat.table)[colnames(ASKOlist$stat.table)=="gene"] <- paste("is", "gene", sep="@") # header formatting for askomics | 277 colnames(ASKOlist$stat.table)[colnames(ASKOlist$stat.table)=="gene"] <- paste("is", "gene", sep="@") # header formatting for askomics |
278 colnames(ASKOlist$stat.table)[colnames(ASKOlist$stat.table)=="contrast"] <- paste("measured_in", "Contrast", sep="@") # header formatting for askomics | 278 colnames(ASKOlist$stat.table)[colnames(ASKOlist$stat.table)=="contrast"] <- paste("measured_in", "Contrast", sep="@") # header formatting for askomics |
279 o <- order(ASKOlist$stat.table$FDR) # ordering genes by FDR value | 279 o <- order(ASKOlist$stat.table$FDR) # ordering genes by FDR value |
280 ASKOlist$stat.table<-ASKOlist$stat.table[o,] | 280 ASKOlist$stat.table<-ASKOlist$stat.table[o,] |
281 | |
281 # | 282 # |
282 dir.create(parameters$out_dir) | 283 dir.create(parameters$out_dir) |
283 write.table(ASKOlist$stat.table,paste0(parameters$out_dir,"/", parameters$organism, contrasko, ".txt"), # | 284 write.table(ASKOlist$stat.table,paste0(parameters$out_dir,"/", parameters$organism, contrasko, ".txt"), # |
284 sep=parameters$sep, col.names = T, row.names = F, quote=FALSE) | 285 sep=parameters$sep, col.names = T, row.names = F, quote=FALSE) |
285 | 286 |
287 | |
286 if(parameters$heatmap==TRUE){ | 288 if(parameters$heatmap==TRUE){ |
287 cpm_gstats<-cpm(dge, log=TRUE)[o,][1:parameters$numhigh,] | 289 numhigh=parameters$numhigh |
290 if (numhigh>length(o)) {numhigh=length(o)} | |
291 cpm_gstats<-cpm(dge, log=TRUE)[o,][1:numhigh,] | |
288 heatmap.2(cpm_gstats, cexRow=0.5, cexCol=0.8, scale="row", labCol=dge$samples$Name, xlab=contrast, Rowv = FALSE, dendrogram="col") | 292 heatmap.2(cpm_gstats, cexRow=0.5, cexCol=0.8, scale="row", labCol=dge$samples$Name, xlab=contrast, Rowv = FALSE, dendrogram="col") |
289 } | 293 } |
290 | 294 |
291 return(ASKOlist) | 295 return(ASKOlist) |
292 | 296 |
360 count<-read.table(parameters$fileofcount, header=TRUE, sep = "\t", row.names = parameters$col_genes, comment.char = "") | 364 count<-read.table(parameters$fileofcount, header=TRUE, sep = "\t", row.names = parameters$col_genes, comment.char = "") |
361 } | 365 } |
362 select_counts<-row.names(samples) | 366 select_counts<-row.names(samples) |
363 #countT<-count[,c(parameters$col_counts:length(colnames(count)))] | 367 #countT<-count[,c(parameters$col_counts:length(colnames(count)))] |
364 countT<-count[,select_counts] | 368 countT<-count[,select_counts] |
369 #print(countT) | |
365 dge<-DGEList(counts=countT, samples=samples) | 370 dge<-DGEList(counts=countT, samples=samples) |
366 # if(is.null(parameters$select_sample)==FALSE){ | 371 # if(is.null(parameters$select_sample)==FALSE){ |
367 # slct<-grep(parameters$select_sample, colnames(countT)) | 372 # slct<-grep(parameters$select_sample, colnames(countT)) |
368 # countT<-countT[,slct] | 373 # countT<-countT[,slct] |
369 # } | 374 # } |
478 cex=0.5) | 483 cex=0.5) |
479 return(filtered_counts) | 484 return(filtered_counts) |
480 } | 485 } |
481 | 486 |
482 GEnorm <- function(filtered_GE, parameters){ | 487 GEnorm <- function(filtered_GE, parameters){ |
483 filtered_cpm <- cpm(filtered_GE, log=TRUE) #nouveau calcul Cpm sur donn?es filtr?es, si log=true alors valeurs cpm en log2 | 488 filtered_cpm=log2(1000000*filtered_GE$counts/colSums(filtered_GE$counts)) |
489 #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 | |
484 colnames(filtered_cpm)<-rownames(filtered_GE$samples) | 490 colnames(filtered_cpm)<-rownames(filtered_GE$samples) |
485 boxplot(filtered_cpm, | 491 boxplot(filtered_cpm, |
486 col=filtered_GE$samples$color, #boxplot des scores cpm non normalis?s | 492 col=filtered_GE$samples$color, #boxplot des scores cpm non normalis?s |
487 main="A. Before normalization", | 493 main="A. Before normalization", |
488 cex.axis=0.5, | 494 cex.axis=0.5, |
507 lcpm<-cpm(dge, log=TRUE) | 513 lcpm<-cpm(dge, log=TRUE) |
508 colnames(lcpm)<-rownames(dge$samples) | 514 colnames(lcpm)<-rownames(dge$samples) |
509 cormat<-cor(lcpm) | 515 cormat<-cor(lcpm) |
510 # color<- colorRampPalette(c("yellow", "white", "green"))(20) | 516 # color<- colorRampPalette(c("yellow", "white", "green"))(20) |
511 color<-colorRampPalette(c("black","red","yellow","white"),space="rgb")(28) | 517 color<-colorRampPalette(c("black","red","yellow","white"),space="rgb")(28) |
512 heatmap(cormat, col=color, symm=TRUE,RowSideColors =as.character(dge$samples$color), ColSideColors = as.character(dge$samples$color)) | 518 heatmap.2(cormat, col=color, symm=TRUE,RowSideColors =as.character(dge$samples$color), ColSideColors = as.character(dge$samples$color)) |
513 #MDS | 519 #MDS |
514 mds <- cmdscale(dist(t(lcpm)),k=3, eig=TRUE) | 520 mds <- cmdscale(dist(t(lcpm)),k=3, eig=TRUE) |
515 eigs<-round((mds$eig)*100/sum(mds$eig[mds$eig>0]),2) | 521 eigs<-round((mds$eig)*100/sum(mds$eig[mds$eig>0]),2) |
516 | 522 |
517 mds1<-ggplot(as.data.frame(mds$points), aes(V1, V2, label = rownames(mds$points))) + labs(title="MDS Axes 1 and 2") + geom_point(color =as.character(dge$samples$color) ) + xlab(paste('dim 1 [', eigs[1], '%]')) +ylab(paste('dim 2 [', eigs[2], "%]")) + geom_label_repel(aes(label = rownames(mds$points)), color = 'black',size = 3.5) | 523 mds1<-ggplot(as.data.frame(mds$points), aes(V1, V2, label = rownames(mds$points))) + labs(title="MDS Axes 1 and 2") + geom_point(color =as.character(dge$samples$color) ) + xlab(paste('dim 1 [', eigs[1], '%]')) +ylab(paste('dim 2 [', eigs[2], "%]")) + geom_label_repel(aes(label = rownames(mds$points)), color = 'black',size = 3.5) |