Mercurial > repos > proteore > proteore_clusterprofiler

annotate GO-enrich.R @ 13:f6107b8ae8f8 draft default tip

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"planemo upload commit be9070db4a3b178ab45ecd9c9c3ab369240f7617-dirty"
author proteore
date Fri, 09 Apr 2021 14:39:05 +0000
parents d951677a50d4
children
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
rev   line source
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1 options(warn = -1) #TURN OFF WARNINGS !!!!!!
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2 suppressMessages(library(clusterProfiler, quietly = TRUE))
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4 # Read file and return file content as data.frame
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5 read_file <- function(path, header) {
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6 file <- try(read.csv(path, header = header, sep = "\t",
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7 stringsAsFactors = FALSE, quote = "", check.names = F),
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8 silent = TRUE)
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9 if (inherits(file, "try-error")) {
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10 stop("File not found !")
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11 }else{
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12 file <- file[!apply(is.na(file) | file == "", 1, all), , drop = FALSE]
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13 return(file)
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14 }
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15 }
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18 #return the number of character from the longest description found
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19 #(from the 10 first)
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20 max_str_length_10_first <- function(vector) {
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21 vector <- as.vector(vector)
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22 nb_description <- length(vector)
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23 if (nb_description >= 10) {
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24 nb_description <- 10
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25 }
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26
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27 return(max(nchar(vector[1:nb_description])))
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28 }
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29
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30 str2bool <- function(x) {
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31 if (any(is.element(c("t", "true"), tolower(x)))) {
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32 return(TRUE)
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33 }else if (any(is.element(c("f", "false"), tolower(x)))) {
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34 return(FALSE)
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35
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36 }else{
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37 return(NULL)
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38 }
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39 }
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40
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41 #used before the limit was set to 50 characters
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42 width_by_max_char <- function(nb_max_char) {
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43 if (nb_max_char < 50) {
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44 width <- 600
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45 } else if (nb_max_char < 75) {
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46 width <- 800
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47 } else if (nb_max_char < 100) {
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48 width <- 900
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49 } else {
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50 width <- 1000
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51 }
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52 return(width)
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53 }
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55
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56 repartition_go <- function(geneid, orgdb, ontology,
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57 level = 3, readable = TRUE) {
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58 ggo <- groupGO(gene = geneid,
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59 OrgDb = orgdb,
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60 ont = ontology,
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61 level = level,
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62 readable = TRUE)
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63
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64
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65 if (length(ggo@result$ID) > 0) {
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66 ggo@result$Description <- sapply(as.vector(ggo@result$Description), #nolint
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67 function(x) {
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68 ifelse(nchar(x) > 50,
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69 substr(x, 1, 50), x)}, USE.NAMES = FALSE)
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70
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71
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72 name <- paste("GGO_", ontology, "_bar-plot", sep = "")
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73 png(name, height = 720, width = 600)
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74 p <- barplot(ggo, showCategory = 10)
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75 print(p)
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76 dev.off()
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77 ggo <- as.data.frame(ggo)
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78 return(ggo)
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79 }
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80 }
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81
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82 # nolint end
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83
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84 # GO over-representation test
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85 enrich_go <- function(geneid, universe, orgdb, ontology, pval_cutoff,
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86 qval_cutoff, plot) {
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87 ego <- enrichGO(gene = geneid,
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88
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89 universe = universe,
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90 OrgDb = orgdb,
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91 ont = ontology,
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92 pAdjustMethod = "BH",
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93 pvalueCutoff = pval_cutoff,
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94 qvalueCutoff = qval_cutoff,
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95 readable = TRUE)
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96
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97 # Plot bar & dot plots
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98 #if there are enriched GoTerms
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99
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101
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102 if (length(ego$ID) > 0) {
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103
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104 ego@result$Description <- sapply(ego@result$Description, function(x) { #nolint
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105 ifelse(nchar(x) > 50, substr(x, 1, 50), x)
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106 }, USE.NAMES = FALSE)
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107
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108
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109 if ("dotplot" %in% plot) {
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110 dot_name <- paste("EGO_", ontology, "_dot-plot", sep = "")
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111 png(dot_name, height = 720, width = 600)
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112 p <- dotplot(ego, showCategory = 10) #nolint
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113 print(p)
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114 dev.off()
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115 }
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116
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117 if ("barplot" %in% plot) {
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118 bar_name <- paste("EGO_", ontology, "_bar-plot", sep = "")
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119 png(bar_name, height = 720, width = 600)
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120 p <- barplot(ego, showCategory = 10)
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121 print(p)
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122 dev.off()
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123 }
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124
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125 ego <- as.data.frame(ego)
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126 return(ego)
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127 } else {
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128 warning(paste("No Go terms enriched (EGO) found for ",
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129 ontology, "ontology"), immediate. = TRUE, noBreaks. = TRUE, call. = FALSE)
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130 }
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131 }
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132
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133
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134 clean_ids <- function(ids) {
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135 ids <- gsub(" ", "", ids)
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136 ids <- ids[which(ids != "")]
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137 ids <- ids[which(ids != "NA")]
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138 ids <- ids[!is.na(ids)]
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139
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140 return(ids)
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141 }
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142
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143 check_ids <- function(vector, type) {
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144 uniprot_pattern <- "^([OPQ][0-9][A-Z0-9]{3}[0-9]|[A-NR-Z][0-9]([A-Z][A-Z0-9]{2}[0-9]){1,2})$" #nolint
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145 entrez_id <- "^([0-9]+|[A-Z]{1,2}_[0-9]+|[A-Z]{1,2}_[A-Z]{1,4}[0-9]+)$" #nolint
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146 if (type == "entrez") {
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147 return(grepl(entrez_id, vector))
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148 }else if (type == "uniprot") {
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149 return(grepl(uniprot_pattern, vector))
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150 }
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151 }
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152
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153 get_args <- function() {
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154 args <- commandArgs(TRUE)
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155 if (length(args) < 1) {
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156 args <- c("--help")
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157 }
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158
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159 # Help section
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160 if ("--help" %in% args) {
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161 cat("clusterProfiler Enrichment Analysis
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162 Arguments:
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163 --input_type: type of input (list of id or filename)
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164 --input: input
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165 --ncol: the column number which contains list of input IDs
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166 --header: true/false if your file contains a header
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167 --id_type: the type of input IDs (UniProt/EntrezID)
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168 --universe_type: list or filename
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169 --universe: background IDs list
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170 --uncol: the column number which contains background IDs list
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171 --uheader: true/false if the background IDs file contains header
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172 --universe_id_type: the type of universe IDs (UniProt/EntrezID)
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173 --species
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174 --onto_opt: ontology options
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175 --go_function: groupGO/enrichGO
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176 --level: 1-3
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177 --pval_cutoff
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178 --qval_cutoff
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179 --text_output: text output filename
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180 --plot : type of visualization, dotplot or/and barplot \n")
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181 q(save = "no")
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182 }
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183 # Parse arguments
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184
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185 parseargs <- function(x) strsplit(sub("^--", "", x), "=")
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186 argsdf <- as.data.frame(do.call("rbind", parseargs(args)))
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187 args <- as.list(as.character(argsdf$V2))
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188 names(args) <- argsdf$V1
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189 return(args)
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190 }
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191
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192 main <- function() { #nolint
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193 #get args from command
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194 args <- get_args()
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195
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196 go_represent <- str2bool(args$go_represent)
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197 go_enrich <- str2bool(args$go_enrich)
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198 if (go_enrich) {
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199 plot <- unlist(strsplit(args$plot, ","))
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200 }
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201
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202 suppressMessages(library(args$species, character.only = TRUE, quietly = TRUE))
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203
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204 # Extract OrgDb
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205 if (args$species == "org.Hs.eg.db") {
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206 orgdb <- org.Hs.eg.db #nolint
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207 } else if (args$species == "org.Mm.eg.db") {
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208 orgdb <- org.Mm.eg.db #nolint
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209 } else if (args$species == "org.Rn.eg.db") {
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210 orgdb <- org.Rn.eg.db #nolint
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211 }
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212
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213 # Extract input IDs
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214 input_type <- args$input_type
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215 id_type <- args$id_type
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216
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217 if (input_type == "text") {
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218 input <- unlist(strsplit(strsplit(args$input, "[ \t\n]+")[[1]], ";"))
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219 } else if (input_type == "file") {
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220 filename <- args$input
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221 ncol <- args$ncol
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222 # Check ncol
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223 if (! as.numeric(gsub("c", "", ncol)) %% 1 == 0) {
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224 stop("Please enter the right format for column number: c[number]")
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225 } else {
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226 ncol <- as.numeric(gsub("c", "", ncol))
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227 }
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228
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229 header <- str2bool(args$header) # Get file content
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230 file <- read_file(filename, header) # Extract Protein IDs list
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231 input <- unlist(sapply(as.character(file[, ncol]),
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232 function(x) rapply(strsplit(x, ";"), c), USE.NAMES = FALSE))
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233 }
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234 input <- clean_ids(input)
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235
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236 ## Get input gene list from input IDs
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237 #ID format Conversion
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238 #This case : from UNIPROT (protein id) to ENTREZ (gene id)
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239 #bitr = conversion function from clusterProfiler
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240 if (id_type == "Uniprot" & any(check_ids(input, "uniprot"))) {
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241 any(check_ids(input, "uniprot"))
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242
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243 idfrom <- "UNIPROT"
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244 idto <- "ENTREZID"
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245 suppressMessages(gene <- bitr(input, fromType = idfrom, toType = idto,
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246 OrgDb = orgdb))
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247
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248 gene <- unique(gene$ENTREZID)
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249 } else if (id_type == "Entrez" & any(check_ids(input, "entrez"))) {
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250 gene <- unique(input)
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251 } else {
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252
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253 stop(paste(id_type, "not found in your ids list,
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254 please check your IDs in input or the selected column of your input file"))
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255
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256 }
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257
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258 ontology <- strsplit(args$onto_opt, ",")[[1]]
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259
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260 ## Extract GGO/EGO arguments
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261 if (go_represent) {
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262 level <- as.numeric(args$level)
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263
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264 }
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265
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266 if (go_enrich) {
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267 pval_cutoff <- as.numeric(args$pval_cutoff)
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268 qval_cutoff <- as.numeric(args$qval_cutoff)
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269 # Extract universe background genes (same as input file)
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270 if (!is.null(args$universe_type)) {
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271 universe_type <- args$universe_type
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272 if (universe_type == "text") {
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273 universe <- unlist(strsplit(strsplit(args$input, "[ \t\n]+")[[1]], ";"))
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274 } else if (universe_type == "file") {
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275 universe_filename <- args$universe
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276 universe_ncol <- args$uncol
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277 # Check ncol
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278 if (! as.numeric(gsub("c", "", universe_ncol)) %% 1 == 0) {
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279 stop("Please enter the right format for column number: c[number]")
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280 } else {
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281 universe_ncol <- as.numeric(gsub("c", "", universe_ncol))
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282 }
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283 universe_header <- str2bool(args$uheader)
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284 # Get file content
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285 universe_file <- read_file(universe_filename, universe_header)
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286 # Extract Protein IDs list
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287 universe <- unlist(sapply(universe_file[, universe_ncol],
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288 function(x) rapply(strsplit(x, ";"), c), USE.NAMES = FALSE))
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289 }
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290 universe <- clean_ids(input)
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291 universe_id_type <- args$universe_id_type
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292 ##to initialize
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293 if (universe_id_type == "Uniprot" & any(check_ids(universe, "uniprot"))) {
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294 idfrom <- "UNIPROT"
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295 idto <- "ENTREZID"
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296 suppressMessages(universe_gene <- bitr(universe, fromType = idfrom,
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297 toType = idto, OrgDb = orgdb))
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298 universe_gene <- unique(universe_gene$ENTREZID)
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299 } else if (universe_id_type == "Entrez" &
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300 any(check_ids(universe, "entrez"))) {
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301 universe_gene <- unique(unlist(universe))
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302 } else {
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303 if (universe_type == "text") {
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304 print(paste(universe_id_type, "not found in your background IDs list",
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305 sep = " "))
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306 } else {
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307 print(paste(universe_id_type, "not found in the column",
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308 universe_ncol, "of your background IDs file", sep = " "))
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309
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310 }
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311 universe_gene <- NULL
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312 }
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313 } else {
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314 universe_gene <- NULL
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315 }
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316 } else {
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317 universe_gene <- NULL
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318 }
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319
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320 ##enrichGO : GO over-representation test
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321 for (onto in ontology) {
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322 if (go_represent) {
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323 ggo <- repartition_go(gene, orgdb, onto, level, readable = TRUE)
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324 if (is.list(ggo)) {
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325 ggo <- as.data.frame(apply(ggo, c(1, 2),
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326 function(x) gsub("^$|^ $", NA, x)))
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327 } #convert "" and " " to NA
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328 output_path <- paste("cluster_profiler_GGO_", onto, ".tsv", sep = "")
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329 write.table(ggo, output_path, sep = "\t",
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330 row.names = FALSE, quote = FALSE)
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331
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332 }
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333
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334 if (go_enrich) {
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335 ego <- enrich_go(gene, universe_gene, orgdb, onto, pval_cutoff,
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336 qval_cutoff, plot)
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337 if (is.list(ego)) {
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338 ego <- as.data.frame(apply(ego, c(1, 2),
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339 function(x) gsub("^$|^ $", NA, x)))
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340 } #convert "" and " " to NA
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341 output_path <- paste("cluster_profiler_EGO_", onto, ".tsv", sep = "")
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342 write.table(ego, output_path, sep = "\t",
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343 row.names = FALSE, quote = FALSE)
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344 }
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345 }
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346 }
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347
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348 if (!interactive()) {
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349 main()
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350 }