diff mogsa.R @ 1:1f48d23544a5 draft default tip

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author mora-lab
date Thu, 20 May 2021 08:48:44 +0000
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/mogsa.R	Thu May 20 08:48:44 2021 +0000
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+###############################################################################
+# title: mogsa
+# author: Xiaowei
+# time: Mar.31 2021
+###############################################################################
+#=================================================================
+#how to pass parameters
+#=================================================================
+spec <- matrix(c("data_file", "D",1, "character", "mogsa data file, xlsx file",
+                 "geneSet_file", "G",1, "character", "gene set /pathway, rdata file, geneSet object",
+                 "design_file", "S",1, "character", "CSV file, colcode, label, sample",
+                 
+                 "PC_number", "P",1, "integer", "numbers for PCs",
+                 "w_data","W",1, "character", "uniform, lambdal, inertia",
+                 "proc_row", "O", 1, "character", "cnetre, center_ssq1, center_ssqN, center_ssqNm1",
+                 "ks_B","B",1, "character", "An integer to indicate the number of bootstrapping samples to calculated the p-value of KS statistic.",
+                 "p_adjust_method", "M", 1, "character", "p values adjust method",
+                 "output_file1", "R", 1, "character", "genesetScoreMatrix CSV file",
+                 "output_file2", "R2", 1, "character", "P value Matrix CSV file"
+                 
+),
+byrow = TRUE, ncol = 5)
+
+
+if (!requireNamespace("getopt", quietly = TRUE))
+  install.packages("getopt")
+
+opt <- getopt::getopt(spec)
+
+if (is.null(opt$PC_number)){PC_number = 3}else{PC_number = opt$PC_number}
+if (is.null(opt$w_data)){w_data = "inertia"}else{w_data = opt$w_data}
+if (is.null(opt$proc_row)){proc_row = "center_ssq1"}else{proc_row = opt$proc_row}
+if (is.null(opt$ks_B)){ks_B = 1000}else{ks_B = opt$ks_B}
+if (is.null(opt$p_adjust_method)){p_adjust_method = "fdr"}else{p_adjust_method = opt$p_adjust_method}
+
+##########################################################
+# load packages
+##########################################################
+library(mogsa)
+library(openxlsx) #for load the xlsx file
+##########################################################
+# Parameters
+##########################################################
+
+sheets <- getSheetNames(opt$data_file)
+mogsa_data <- vector(mode = "list", length = length(sheets))
+names(mogsa_data) = sheets
+for (sht in sheets){
+  mogsa_data[[sht]] <- read.xlsx(opt$data_file, sheet = sht, colNames = T, rowNames = T)
+}
+
+
+
+# design
+design <- read.csv(opt$design_file, header = T, stringsAsFactors = F) #分类别、分组别
+groups <- as.factor(design$label) 
+#if ("colcode" %in% colnames(design)){colcode <- design$colcode}else{colcode = NULL}
+
+
+# geneSet
+load(opt$geneSet_file)
+sup_data <- prepSupMoa(mogsa_data, geneSets=geneSet, minMatch = 1)
+
+
+##########################################################
+# mogsaBasicRun
+##########################################################
+mgsa1 <- mogsa(x = mogsa_data, sup=sup_data, nf=PC_number,
+               proc.row = proc_row, w.data = w_data, statis = TRUE, 
+               ks.B = ks_B, p.adjust.method = p_adjust_method)
+
+
+
+##########################################################
+# gene Set Score (GSS) Matrix 基因集打分矩阵  每个值表示该基因集在该样本的总体活性水平
+##########################################################
+# get the score matrix
+scores <- getmgsa(mgsa1, "score")
+write.csv(scores, file = opt$output_file1)
+
+
+##########################################################
+# P value Matrix 
+##########################################################
+# 获取p值矩阵,行是基因集/pathway名称,列为样本名称
+p.mat <- getmgsa(mgsa1, "p.val") # get p value matrix
+write.csv(p.mat, file = opt$output_file2)
+
+