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annotate egsea.R @ 0:a8a083193440 draft

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/egsea commit 7d0c7d850cd56ea3e54d8c03266f719241b20b8b
author iuc
date Thu, 25 Jan 2018 02:23:23 -0500
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children 73281fbdf6c1
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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 () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } )
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5 # we need that to not crash galaxy with an UTF8 error on German LC settings.
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6 loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
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7
a8a083193440 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/egsea commit 7d0c7d850cd56ea3e54d8c03266f719241b20b8b
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8 suppressPackageStartupMessages({
a8a083193440 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/egsea commit 7d0c7d850cd56ea3e54d8c03266f719241b20b8b
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9 library(EGSEA)
a8a083193440 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/egsea commit 7d0c7d850cd56ea3e54d8c03266f719241b20b8b
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10 library(limma)
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11 library(edgeR)
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12 library(optparse)
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13 })
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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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16 ## Function Declaration
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18 sanitiseEquation <- function(equation) {
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19 equation <- gsub(" *[+] *", "+", equation)
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20 equation <- gsub(" *[-] *", "-", equation)
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21 equation <- gsub(" *[/] *", "/", equation)
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22 equation <- gsub(" *[*] *", "*", equation)
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23 equation <- gsub("^\\s+|\\s+$", "", equation)
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24 return(equation)
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25 }
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27 # Function to sanitise group information
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28 sanitiseGroups <- function(string) {
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29 string <- gsub(" *[,] *", ",", string)
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30 string <- gsub("^\\s+|\\s+$", "", string)
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31 return(string)
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32 }
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34 # Generating design information
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35 pasteListName <- function(string) {
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36 return(paste0("factors$", string))
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37 }
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38
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39 ## Input Processing
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41 option_list <- list(
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42 make_option(c("-threads", "--threads"), default=2, type="integer", help="Number of threads for egsea"),
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43 make_option(c("-filesPath", "--filesPath"), type="character", help="JSON list object if multiple files input"),
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44 make_option(c("-matrixPath", "--matrixPath"), type="character", help="Path to count matrix"),
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45 make_option(c("-factFile", "--factFile"), type="character", help="Path to factor information file"),
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46 make_option(c("-factInput", "--factInput"), type="character", help="String containing factors if manually input"),
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47 make_option(c("-contrastData", "--contrastData"), type="character", help="Contrasts of Interest (Groups to compare)"),
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48 make_option(c("-genes", "--genes"), type="character", help="Path to genes file"),
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49 make_option(c("-species", "--species"), type="character"),
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50 make_option(c("-base_methods", "--base_methods"), type="character", help="Gene set testing methods"),
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51 make_option(c("-msigdb", "--msigdb"), type="character", help="MSigDB Gene Set Collections"),
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52 make_option(c("-keggdb", "--keggdb"), type="character", help="KEGG Pathways"),
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53 make_option(c("-gsdb", "--gsdb"), type="character", help = "GeneSetDB Gene Sets"),
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54 make_option(c("-display_top", "--display_top"), type="integer", help = "Number of top Gene Sets to display"),
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55 make_option(c("-min_size", "--min_size"), type="integer", help = "Minimum Size of Gene Set"),
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56 make_option(c("-fdr_cutoff", "--fdr_cutoff"), type="double", help = "FDR cutoff"),
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57 make_option(c("-combine_method", "--combine_method"), type="character", help="Method to use to combine the p-values"),
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58 make_option(c("-sort_method", "--sort_method"), type="character", help="Method to sort the results"),
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59 make_option(c("-rdata", "--rdaOpt"), type="character", help="Output RData file")
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60 )
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61
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62 parser <- OptionParser(usage = "%prog [options] file", option_list=option_list)
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63 args = parse_args(parser)
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64
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65
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66 ## Read in Files
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67
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68 if (!is.null(args$filesPath)) {
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69 # Process the separate count files (adapted from DESeq2 wrapper)
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70 library("rjson")
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71 parser <- newJSONParser()
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72 parser$addData(args$filesPath)
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73 factorList <- parser$getObject()
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74 factors <- sapply(factorList, function(x) x[[1]])
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75 filenamesIn <- unname(unlist(factorList[[1]][[2]]))
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76 sampleTable <- data.frame(sample=basename(filenamesIn),
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77 filename=filenamesIn,
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78 row.names=filenamesIn,
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79 stringsAsFactors=FALSE)
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80 for (factor in factorList) {
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81 factorName <- factor[[1]]
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82 sampleTable[[factorName]] <- character(nrow(sampleTable))
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83 lvls <- sapply(factor[[2]], function(x) names(x))
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84 for (i in seq_along(factor[[2]])) {
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85 files <- factor[[2]][[i]][[1]]
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86 sampleTable[files,factorName] <- lvls[i]
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87 }
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88 sampleTable[[factorName]] <- factor(sampleTable[[factorName]], levels=lvls)
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89 }
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90 rownames(sampleTable) <- sampleTable$sample
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91 rem <- c("sample","filename")
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92 factors <- sampleTable[, !(names(sampleTable) %in% rem), drop=FALSE]
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93
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94 #read in count files and create single table
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95 countfiles <- lapply(sampleTable$filename, function(x){read.delim(x, row.names=1)})
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96 counts <- do.call("cbind", countfiles)
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97
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98 } else {
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99 # Process the single count matrix
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100 counts <- read.table(args$matrixPath, header=TRUE, sep="\t", stringsAsFactors=FALSE)
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101 row.names(counts) <- counts[, 1]
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102 counts <- counts[ , -1]
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103 countsRows <- nrow(counts)
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104
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105 # Process factors
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106 if (is.null(args$factInput)) {
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107 factorData <- read.table(args$factFile, header=TRUE, sep="\t")
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108 factors <- factorData[, -1, drop=FALSE]
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109 } else {
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110 factors <- unlist(strsplit(args$factInput, "|", fixed=TRUE))
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111 factorData <- list()
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112 for (fact in factors) {
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113 newFact <- unlist(strsplit(fact, split="::"))
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114 factorData <- rbind(factorData, newFact)
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115 } # Factors have the form: FACT_NAME::LEVEL,LEVEL,LEVEL,LEVEL,... The first factor is the Primary Factor.
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116
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117 # Set the row names to be the name of the factor and delete first row
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118 row.names(factorData) <- factorData[, 1]
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119 factorData <- factorData[, -1]
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120 factorData <- sapply(factorData, sanitiseGroups)
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121 factorData <- sapply(factorData, strsplit, split=",")
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122 factorData <- sapply(factorData, make.names)
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123 # Transform factor data into data frame of R factor objects
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124 factors <- data.frame(factorData)
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125 }
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126 }
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127
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128 # Create a DGEList object
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129 counts <- DGEList(counts)
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130
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131 # Set group to be the Primary Factor input
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132 group <- factors[, 1, drop=FALSE]
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133
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134 # Split up contrasts separated by comma into a vector then sanitise
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135 contrastData <- unlist(strsplit(args$contrastData, split=","))
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136 contrastData <- sanitiseEquation(contrastData)
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137 contrastData <- gsub(" ", ".", contrastData, fixed=TRUE)
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138
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139 # Creating design
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140 row.names(factors) <- colnames(counts)
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141 factorList <- sapply(names(factors), pasteListName)
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142
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143 formula <- "~0"
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144 for (i in 1:length(factorList)) {
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145 formula <- paste(formula, factorList[i], sep="+")
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146 }
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147 formula <- formula(formula)
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148
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149 design <- model.matrix(formula)
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150
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151 for (i in 1:length(factorList)) {
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152 colnames(design) <- gsub(factorList[i], "", colnames(design), fixed=TRUE)
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153 }
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154
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155 ## Generate Contrasts information
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156 contrasts <- makeContrasts(contrasts=contrastData, levels=design)
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157
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158
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159 ## Add Gene Symbol information
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160
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161 genes <- read.table(args$genes, sep='\t', header=TRUE)
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162
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163
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164 ## Set Gene Set Testing Methods
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165
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166 base_methods <- unlist(strsplit(args$base_methods, ","))
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167
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168
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169 ## Set Gene Sets
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170
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171 if (args$msigdb != "None") {
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172 msigdb <- unlist(strsplit(args$msigdb, ","))
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173 } else {
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174 msigdb <- "none"
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175 }
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176
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177 if (args$keggdb != "None") {
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178 keggdb <- unlist(strsplit(args$keggdb, ","))
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179 kegg_all <- c("Metabolism"="keggmet", "Signaling"="keggsig", "Disease"="keggdis")
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180 kegg_exclude <- names(kegg_all[!(kegg_all %in% keggdb)])
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181 } else {
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182 kegg_exclude <- "all"
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183 }
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184
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185 if (args$gsdb != "None") {
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186 gsdb <- unlist(strsplit(args$gsdb, ","))
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187 } else {
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188 gsdb <- "none"
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189 }
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190
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191
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192 ## Index gene sets
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193
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194 gs.annots <- buildIdx(entrezIDs=rownames(counts), species=args$species, msigdb.gsets=msigdb, gsdb.gsets=gsdb, kegg.exclude=kegg_exclude)
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195
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196
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197 ## Run egsea.cnt
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198
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199 gsa <- egsea.cnt(counts=counts, group=group, design=design, contrasts=contrasts, gs.annots=gs.annots, symbolsMap=genes, baseGSEAs=base_methods, minSize=args$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$threads, report=TRUE)
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200
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201
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202 ## Output RData file
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203
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204 if (!is.null(args$rdata)) {
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205 save.image(file = "EGSEA_analysis.RData")
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206 }