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annotate egsea.R @ 4:fba1660fb717 draft default tip

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/egsea commit c2313b506b3b8ae860bb844b979397d87de4fb44"
author iuc
date Mon, 28 Jun 2021 09:45:14 +0000
parents ba2111ae6eb4
children
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a8a083193440 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/egsea commit 7d0c7d850cd56ea3e54d8c03266f719241b20b8b
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1 # Code based on (and inspired by) the Galaxy limma-voom/edgeR/DESeq2 wrappers
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3 options(show.error.messages = F, error = function() {
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4 cat(geterrmessage(), file = stderr()); q("no", 1, F)
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5 })
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7 # we need that to not crash galaxy with an UTF8 error on German LC settings.
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8 loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
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10 suppressPackageStartupMessages({
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11 library(EGSEA)
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12 library(limma)
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13 library(edgeR)
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14 library(optparse)
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15 })
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18 ## Function Declaration
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20 sanitise_equation <- function(equation) {
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21 equation <- gsub(" *[+] *", "+", equation)
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22 equation <- gsub(" *[-] *", "-", equation)
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23 equation <- gsub(" *[/] *", "/", equation)
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24 equation <- gsub(" *[*] *", "*", equation)
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25 equation <- gsub("^\\s+|\\s+$", "", equation)
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26 return(equation)
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27 }
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29 # Function to sanitise group information
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30 sanitise_groups <- function(string) {
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31 string <- gsub(" *[,] *", ",", string)
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32 string <- gsub("^\\s+|\\s+$", "", string)
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33 return(string)
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34 }
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36 # Generating design information
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37 paste_listname <- function(string) {
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38 return(paste0("factors$", string))
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39 }
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41 ## Input Processing
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43 option_list <- list(
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44 make_option("--threads", default = 2, type = "integer", help = "Number of threads for egsea"),
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45 make_option("--filesPath", type = "character", help = "JSON list object if multiple files input"),
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46 make_option("--matrixPath", type = "character", help = "Path to count matrix"),
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47 make_option("--factFile", type = "character", help = "Path to factor information file"),
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48 make_option("--factInput", type = "character", help = "String containing factors if manually input"),
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49 make_option("--contrastData", type = "character", help = "Contrasts of Interest (Groups to compare)"),
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50 make_option("--genes", type = "character", help = "Path to genes file"),
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51 make_option("--species", type = "character"),
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52 make_option("--base_methods", type = "character", help = "Gene set testing methods"),
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53 make_option("--msigdb", type = "character", help = "MSigDB Gene Set Collections"),
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54 make_option("--keggdb", type = "character", help = "KEGG Pathways"),
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55 make_option("--keggupdated", type = "logical", help = "Use updated KEGG"),
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56 make_option("--gsdb", type = "character", help = "GeneSetDB Gene Sets"),
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57 make_option("--display_top", type = "integer", help = "Number of top Gene Sets to display"),
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58 make_option("--min_size", type = "integer", help = "Minimum Size of Gene Set"),
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59 make_option("--fdr_cutoff", type = "double", help = "FDR cutoff"),
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60 make_option("--combine_method", type = "character", help = "Method to use to combine the p-values"),
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61 make_option("--sort_method", type = "character", help = "Method to sort the results"),
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62 make_option("--rdaOpt", type = "character", help = "Output RData file")
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63 )
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64
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65 parser <- OptionParser(usage = "%prog [options] file", option_list = option_list)
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66 args <- parse_args(parser)
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67
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69 ## Read in Files
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70
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71 if (!is.null(args$filesPath)) {
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72 # Process the separate count files (adapted from DESeq2 wrapper)
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73 library("rjson")
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74 parser <- newJSONParser()
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75 parser$addData(args$filesPath)
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76 factor_list <- parser$getObject()
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77 factors <- sapply(factor_list, function(x) x[[1]])
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78 filenames_in <- unname(unlist(factor_list[[1]][[2]]))
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79 sampletable <- data.frame(sample = basename(filenames_in),
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80 filename = filenames_in,
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81 row.names = filenames_in,
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82 stringsAsFactors = FALSE)
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83 for (factor in factor_list) {
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84 factorname <- factor[[1]]
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85 sampletable[[factorname]] <- character(nrow(sampletable))
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86 lvls <- sapply(factor[[2]], function(x) names(x))
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87 for (i in seq_along(factor[[2]])) {
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88 files <- factor[[2]][[i]][[1]]
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89 sampletable[files, factorname] <- lvls[i]
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90 }
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91 sampletable[[factorname]] <- factor(sampletable[[factorname]], levels = lvls)
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92 }
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93 rownames(sampletable) <- sampletable$sample
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94 rem <- c("sample", "filename")
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95 factors <- sampletable[, !(names(sampletable) %in% rem), drop = FALSE]
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96
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97 #read in count files and create single table
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98 countfiles <- lapply(sampletable$filename, function(x) {
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99 read.delim(x, row.names = 1)
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100 })
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101 counts <- do.call("cbind", countfiles)
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102
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103 } else {
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104 # Process the single count matrix
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105 counts <- read.table(args$matrixPath, header = TRUE, sep = "\t", stringsAsFactors = FALSE, check.names = FALSE)
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106 row.names(counts) <- counts[, 1]
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107 counts <- counts[, -1]
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108 countsrows <- nrow(counts)
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109
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110 # Process factors
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111 if (is.null(args$factInput)) {
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112 factordata <- read.table(args$factFile, header = TRUE, sep = "\t", strip.white = TRUE, stringsAsFactors = TRUE)
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113 # check samples names match
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114 if (!any(factordata[, 1] %in% colnames(counts)))
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115 stop("Sample IDs in factors file and count matrix don't match")
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116 # order samples as in counts matrix
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117 factordata <- factordata[match(colnames(counts), factordata[, 1]), ]
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118 factors <- factordata[, -1, drop = FALSE]
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119 } else {
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120 factors <- unlist(strsplit(args$factInput, "|", fixed = TRUE))
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121 factordata <- list()
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122 for (fact in factors) {
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123 newfact <- unlist(strsplit(fact, split = "::"))
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124 factordata <- rbind(factordata, newfact)
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125 } # Factors have the form: FACT_NAME::LEVEL,LEVEL,LEVEL,LEVEL,... The first factor is the Primary Factor.
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126
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127 # Set the row names to be the name of the factor and delete first row
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128 row.names(factordata) <- factordata[, 1]
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129 factordata <- factordata[, -1]
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130 factordata <- sapply(factordata, sanitise_groups)
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131 factordata <- sapply(factordata, strsplit, split = ",")
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132 factordata <- sapply(factordata, make.names)
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133 # Transform factor data into data frame of R factor objects
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134 factors <- data.frame(factordata, stringsAsFactors = TRUE)
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135 }
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136 }
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137
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138 # Create a DGEList object
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139 counts <- DGEList(counts)
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140
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141 # Set group to be the Primary Factor input
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142 group <- factors[, 1, drop = FALSE]
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143
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144 # Split up contrasts separated by comma into a vector then sanitise
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145 contrast_data <- unlist(strsplit(args$contrastData, split = ","))
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146 contrast_data <- sanitise_equation(contrast_data)
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147 contrast_data <- gsub(" ", ".", contrast_data, fixed = TRUE)
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148
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149 # Creating design
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150 row.names(factors) <- colnames(counts)
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151 factor_list <- sapply(names(factors), paste_listname)
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152
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153 formula <- "~0"
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154 for (i in seq_along(factor_list)) {
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155 formula <- paste(formula, factor_list[i], sep = "+")
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156 }
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157 formula <- formula(formula)
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158
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159 design <- model.matrix(formula)
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160
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161 for (i in seq_along(factor_list)) {
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162 colnames(design) <- gsub(factor_list[i], "", colnames(design), fixed = TRUE)
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163 }
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164
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165 ## Generate Contrasts information
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166 contrasts <- makeContrasts(contrasts = contrast_data, levels = design)
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167
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168
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169 ## Add Gene Symbol information
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170
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171 genes <- read.table(args$genes, sep = "\t", header = TRUE)
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172
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173
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174 ## Set Gene Set Testing Methods
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175
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176 base_methods <- unlist(strsplit(args$base_methods, ","))
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177
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178
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179 ## Set Gene Sets
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180
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181 if (args$msigdb != "None") {
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182 msigdb <- unlist(strsplit(args$msigdb, ","))
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183 } else {
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184 msigdb <- "none"
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185 }
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186
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187 if (args$keggdb != "None") {
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188 keggdb <- unlist(strsplit(args$keggdb, ","))
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189 kegg_all <- c("Metabolism" = "keggmet", "Signaling" = "keggsig", "Disease" = "keggdis")
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190 kegg_exclude <- names(kegg_all[!(kegg_all %in% keggdb)])
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191 } else {
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192 kegg_exclude <- "all"
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193 }
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194
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195 if (args$gsdb != "None") {
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196 gsdb <- unlist(strsplit(args$gsdb, ","))
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197 } else {
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198 gsdb <- "none"
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199 }
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200
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201 ## Index gene sets
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202
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203 gs_annots <- buildIdx(entrezIDs = rownames(counts), species = args$species, msigdb.gsets = msigdb, gsdb.gsets = gsdb, kegg.exclude = kegg_exclude, kegg.updated = args$keggupdated)
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204
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205
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206 ## Run egsea.cnt
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207
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208 gsa <- egsea.cnt(counts = counts, group = group, design = design, contrasts = contrasts, gs.annots = gs_annots, symbolsMap = genes, baseGSEAs = base_methods, minSize = args$min_size, display.top = args$display_top, combineMethod = args$combine_method, sort.by = args$sort_method, report.dir = "./report_dir", fdr.cutoff = args$fdr_cutoff, num.threads = args$threads, report = TRUE)
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209
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210
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211 ## Output RData file
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212
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213 if (!is.null(args$rdaOpt)) {
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214 save.image(file = "EGSEA_analysis.RData")
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215 }