Mercurial > repos > mora-lab > gsva
view GSVA.R @ 1:b83133fd91d5 draft default tip
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author | mora-lab |
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date | Thu, 20 May 2021 08:30:52 +0000 |
parents | f94ef9b31552 |
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############################################################################### # title: Gene set variation analysis # author: Xiaowei # time: Mar.31 2021 ############################################################################### #================================================================= #how to pass parameters #================================================================= spec <- matrix(c("expr", 'E', 1, 'character', 'Gene expression data which is an CSV file of expression values where rows correspond to genes and columns correspond to samples.', "geneSet", 'G', 1, 'character', 'Gene set', 'gene_Identifier_class','C', 1, 'character', 'Gene Identifier class of GeneSet', 'method', "M", 1,'character', 'One of gsva, ssgsea, zscore, plage', 'img_file', 'I', 1,'character', 'img_file', 'img_type', 'T', 1,'character', 'PDF, PNG, JPEG', 'img_width', 'W', 1, 'integer', 'the img file width', 'img_height', 'H', 1, 'integer', 'the img file height', 'GSVA_result', 'R', 1, 'character', 'Result of GSVA, an CSV file.' ), byrow = TRUE, ncol = 5) if (!requireNamespace("getopt", quietly = TRUE)) install.packages("getopt") opt <- getopt::getopt(spec) #---------------- #整理参数 #---------------- if(is.null(opt$gene_Identifier_class)){gene_Identifier_class = 'Symbol'}else{gene_Identifier_class = opt$gene_Identifier_class } if(is.null(opt$method)){opt$method = 'gsva'} if(is.null(opt$img_type)){opt$img_type = 'PNG'} if(is.null(opt$img_width)){img_width = 900}else{img_width = opt$img_width} if(is.null(opt$img_height)){img_height = 900}else{img_height = opt$img_height} #================================================================ #run codes #================================================================ gsva_input_data <- read.csv(opt$expr, row.names = 1) # if (gene_Identifier_class == 'Symbol'){ # geneset <- GSEABase::getGmt(opt$geneSet, # geneIdType = GSEABase::SymbolIdentifier()) # }else{ # geneset <- GSEABase::getGmt(opt$geneSet, # geneIdType = GSEABase::EntrezIdentifier()) # } load(opt$geneSet) result <- GSVA::gsva(as.matrix(gsva_input_data), geneSet, mx.diff=FALSE, verbose=FALSE, parallel.sz=2, method = opt$method) #================================================================ #output #================================================================ write.csv(result, file = opt$GSVA_result) if (opt$img_type == 'PNG'){ png(filename = opt$img_file, width = img_width, height = img_height) }else if(opt$img_type == 'JPG'){ jpeg(filename = opt$img_file, width = img_width, height = img_height) }else{ pdf(file = opt$img_file, width = img_width, height = img_height) } pheatmap::pheatmap(result, scale = "row", main = "heatmap", show_colnames=T) dev.off()