Mercurial > repos > iuc > goseq

annotate goseq.r @ 5:49b3558dbf68 draft

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/goseq commit 11d5198120837fa4eecb0bef8e2c04106eab63c2
author iuc
date Sat, 09 Feb 2019 09:06:20 -0500
parents 9e6226b6d2ad
children 85f3b5ab2bf8
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1 options( show.error.messages=F, error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } )
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3 # we need that to not crash galaxy with an UTF8 error on German LC settings.
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4 loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
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6 suppressPackageStartupMessages({
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7 library("goseq")
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8 library("optparse")
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9 library("dplyr")
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10 library("ggplot2")
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11 })
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13 option_list <- list(
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14 make_option(c("-d", "--dge_file"), type="character", help="Path to file with differential gene expression result"),
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15 make_option(c("-w","--wallenius_tab"), type="character", help="Path to output file with P-values estimated using wallenius distribution."),
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16 make_option(c("-s","--sampling_tab"), type="character", default=FALSE, help="Path to output file with P-values estimated using sampling distribution."),
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17 make_option(c("-n","--nobias_tab"), type="character", default=FALSE, help="Path to output file with P-values estimated using hypergeometric distribution and no correction for gene length bias."),
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18 make_option(c("-l","--length_bias_plot"), type="character", default=FALSE, help="Path to length-bias plot."),
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19 make_option(c("-sw","--sample_vs_wallenius_plot"), type="character", default=FALSE, help="Path to plot comparing sampling with wallenius p-values."),
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20 make_option(c("-r", "--repcnt"), type="integer", default=100, help="Number of repeats for sampling"),
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21 make_option(c("-lf", "--length_file"), type="character", default="FALSE", help = "Path to tabular file mapping gene id to length"),
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22 make_option(c("-cat_file", "--category_file"), default="FALSE", type="character", help = "Path to tabular file with gene_id <-> category mapping."),
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23 make_option(c("-g", "--genome"), default=NULL, type="character", help = "Genome [used for looking up correct gene length]"),
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24 make_option(c("-i", "--gene_id"), default=NULL, type="character", help = "Gene ID format of genes in DGE file"),
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25 make_option(c("-p", "--p_adj_method"), default="BH", type="character", help="Multiple hypothesis testing correction method to use"),
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26 make_option(c("-cat", "--use_genes_without_cat"), default=FALSE, type="logical",
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27 help="A large number of gene may have no GO term annotated. If this option is set to FALSE, genes without category will be ignored in the calculation of p-values(default behaviour). If TRUE these genes will count towards the total number of genes outside the tested category (default behaviour prior to version 1.15.2)."),
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28 make_option(c("-plots", "--make_plots"), default=FALSE, type="logical", help="produce diagnostic plots?"),
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29 make_option(c("-fc", "--fetch_cats"), default=NULL, type="character", help="Categories to get can include one or more of GO:CC, GO:BP, GO:MF, KEGG"),
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30 make_option(c("-rd", "--rdata"), default=NULL, type="character", help="Path to RData output file."),
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31 make_option(c("-tp", "--top_plot"), default=NULL, type="logical", help="Output PDF with top10 over-rep GO terms?")
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32 )
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34 parser <- OptionParser(usage = "%prog [options] file", option_list=option_list)
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35 args = parse_args(parser)
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37 # Vars:
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38 dge_file = args$dge_file
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39 category_file = args$category_file
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40 length_file = args$length_file
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41 genome = args$genome
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42 gene_id = args$gene_id
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43 wallenius_tab = args$wallenius_tab
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44 sampling_tab = args$sampling_tab
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45 nobias_tab = args$nobias_tab
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46 length_bias_plot = args$length_bias_plot
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47 sample_vs_wallenius_plot = args$sample_vs_wallenius_plot
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48 repcnt = args$repcnt
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49 p_adj_method = args$p_adj_method
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50 use_genes_without_cat = args$use_genes_without_cat
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51 make_plots = args$make_plots
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52 rdata = args$rdata
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54 if (!is.null(args$fetch_cats)) {
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55 fetch_cats = unlist(strsplit(args$fetch_cats, ","))
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56 } else {
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57 fetch_cats = "Custom"
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58 }
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59
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60 # format DE genes into named vector suitable for goseq
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61 # check if header is present
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62 first_line = read.delim(dge_file, header = FALSE, nrow=1)
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63 second_col = toupper(first_line[, ncol(first_line)])
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64 if (second_col == TRUE || second_col == FALSE) {
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65 dge_table = read.delim(dge_file, header = FALSE, sep="\t")
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66 } else {
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67 dge_table = read.delim(dge_file, header = TRUE, sep="\t")
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68 }
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69 genes = as.numeric(as.logical(dge_table[,ncol(dge_table)])) # Last column contains TRUE/FALSE
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70 names(genes) = dge_table[,1] # Assuming first column contains gene names
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71
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72 # gene lengths, assuming last column
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73 if (length_file != "FALSE" ) {
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74 first_line = read.delim(length_file, header = FALSE, nrow=1)
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75 if (is.numeric(first_line[, ncol(first_line)])) {
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76 length_table = read.delim(length_file, header=FALSE, sep="\t", check.names=FALSE)
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77 } else {
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78 length_table = read.delim(length_file, header=TRUE, sep="\t", check.names=FALSE)
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79 }
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80 row.names(length_table) = length_table[,1]
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81 gene_lengths = length_table[names(genes),][,ncol(length_table)]
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82 } else {
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83 gene_lengths = getlength(names(genes), genome, gene_id)
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84 }
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85
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86 # Estimate PWF
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87
2
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88 if (make_plots != 'false') {
0
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89 pdf(length_bias_plot)
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90 }
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91 pwf=nullp(genes, genome = genome, id = gene_id, bias.data = gene_lengths, plot.fit=make_plots)
2
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92 if (make_plots != 'false') {
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93 dev.off()
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94 }
0
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95
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96 # Fetch GO annotations if category_file hasn't been supplied:
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97 if (category_file == "FALSE") {
2
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98 go_map=getgo(genes = names(genes), genome=genome, id=gene_id, fetch.cats=fetch_cats)
0
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99 } else {
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100 # check for header: first entry in first column must be present in genes, else it's a header
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101 first_line = read.delim(category_file, header = FALSE, nrow=1)
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102 if (first_line[,1] %in% names(genes)) {
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103 go_map = read.delim(category_file, header = FALSE)
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104 } else {
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105 go_map = read.delim(category_file, header= TRUE)
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106 }
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107 }
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108
2
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109 results <- list()
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110
0
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111 # wallenius approximation of p-values
3
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112 if (wallenius_tab != FALSE) {
0
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113 GO.wall=goseq(pwf, genome = genome, id = gene_id, use_genes_without_cat = use_genes_without_cat, gene2cat=go_map)
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114 GO.wall$p.adjust.over_represented = p.adjust(GO.wall$over_represented_pvalue, method=p_adj_method)
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115 GO.wall$p.adjust.under_represented = p.adjust(GO.wall$under_represented_pvalue, method=p_adj_method)
2
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116 write.table(GO.wall, args$wallenius_tab, sep="\t", row.names = FALSE, quote = FALSE)
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117 results[['Wallenius']] <- GO.wall
0
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118 }
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119
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120 # hypergeometric (no length bias correction)
3
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121 if (nobias_tab != FALSE) {
0
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122 GO.nobias=goseq(pwf, genome = genome, id = gene_id, method="Hypergeometric", use_genes_without_cat = use_genes_without_cat, gene2cat=go_map)
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123 GO.nobias$p.adjust.over_represented = p.adjust(GO.nobias$over_represented_pvalue, method=p_adj_method)
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124 GO.nobias$p.adjust.under_represented = p.adjust(GO.nobias$under_represented_pvalue, method=p_adj_method)
2
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125 write.table(GO.nobias, args$nobias_tab, sep="\t", row.names = FALSE, quote = FALSE)
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126 results[['Hypergeometric']] <- GO.nobias
0
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127 }
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128
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129 # Sampling distribution
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130 if (repcnt > 0) {
2
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131
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132 # capture the sampling progress so it doesn't fill stdout
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133 zz <- file("/dev/null", open = "wt")
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134 sink(zz)
0
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135 GO.samp=goseq(pwf, genome = genome, id = gene_id, method="Sampling", repcnt=repcnt, use_genes_without_cat = use_genes_without_cat, gene2cat=go_map)
2
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136 sink()
4
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137
0
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138 GO.samp$p.adjust.over_represented = p.adjust(GO.samp$over_represented_pvalue, method=p_adj_method)
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139 GO.samp$p.adjust.under_represented = p.adjust(GO.samp$under_represented_pvalue, method=p_adj_method)
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140 write.table(GO.samp, sampling_tab, sep="\t", row.names = FALSE, quote = FALSE)
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141 # Compare sampling with wallenius
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142 if (make_plots == TRUE) {
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143 pdf(sample_vs_wallenius_plot)
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144 plot(log10(GO.wall[,2]), log10(GO.samp[match(GO.samp[,1],GO.wall[,1]),2]),
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145 xlab="log10(Wallenius p-values)",ylab="log10(Sampling p-values)",
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146 xlim=c(-3,0))
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147 abline(0,1,col=3,lty=2)
2
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148 dev.off()
0
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149 }
2
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150 results[['Sampling']] <- GO.samp
0
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151 }
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152
2
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153 if (!is.null(args$top_plot)) {
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154 cats_title <- gsub("GO:","", args$fetch_cats)
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155 # modified from https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2018/RNASeq2018/html/06_Gene_set_testing.nb.html
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156 pdf("top10.pdf")
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157 for (m in names(results)) {
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158 p <- results[[m]] %>%
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159 top_n(10, wt=-over_represented_pvalue) %>%
2
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160 mutate(hitsPerc=numDEInCat*100/numInCat) %>%
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161 ggplot(aes(x=hitsPerc,
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162 y=substr(term, 1, 40), # only use 1st 40 chars of terms otherwise squashes plot
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163 colour=over_represented_pvalue,
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164 size=numDEInCat)) +
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165 geom_point() +
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166 expand_limits(x=0) +
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167 labs(x="% DE in category", y="Category", colour="P value", size="Count", title=paste("Top over-represented categories in", cats_title), subtitle=paste(m, " method")) +
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168 theme(plot.title = element_text(hjust = 0.5), plot.subtitle = element_text(hjust = 0.5))
25e1e7b40e55 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/goseq commit 46c4278d292ab4d76dc5f3f74c3109c3179be7ef
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169 print(p)
25e1e7b40e55 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/goseq commit 46c4278d292ab4d76dc5f3f74c3109c3179be7ef
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170 }
25e1e7b40e55 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/goseq commit 46c4278d292ab4d76dc5f3f74c3109c3179be7ef
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171 dev.off()
25e1e7b40e55 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/goseq commit 46c4278d292ab4d76dc5f3f74c3109c3179be7ef
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172 }
25e1e7b40e55 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/goseq commit 46c4278d292ab4d76dc5f3f74c3109c3179be7ef
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173
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174 # Output RData file
25e1e7b40e55 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/goseq commit 46c4278d292ab4d76dc5f3f74c3109c3179be7ef
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175 if (!is.null(args$rdata)) {
25e1e7b40e55 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/goseq commit 46c4278d292ab4d76dc5f3f74c3109c3179be7ef
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176 save.image(file = "goseq_analysis.RData")
25e1e7b40e55 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/goseq commit 46c4278d292ab4d76dc5f3f74c3109c3179be7ef
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177 }
25e1e7b40e55 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/goseq commit 46c4278d292ab4d76dc5f3f74c3109c3179be7ef
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178
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179
0
084d77515343 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/goseq commit b7dcd020c6a15fa55f392cc09cbc37580d6e75c4
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180 sessionInfo()