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annotate deseq2.R @ 37:951876579237 draft

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
author iuc
date Wed, 25 Nov 2020 18:35:56 +0000
parents d9f48120c02b
children b30a443484ab
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1 #!/usr/bin/env Rscript
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3 # A command-line interface to DESeq2 for use with Galaxy
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4 # written by Bjoern Gruening and modified by Michael Love 2016.03.30
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5 #
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6 # This argument is required:
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7 #
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8 # 'factors' a JSON list object from Galaxy
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9 #
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10 # the output file has columns:
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11 #
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12 # baseMean (mean normalized count)
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13 # log2FoldChange (by default a moderated LFC estimate)
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14 # lfcSE (the standard error)
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15 # stat (the Wald statistic)
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16 # pvalue (p-value from comparison of Wald statistic to a standard Normal)
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17 # padj (adjusted p-value, Benjamini Hochberg correction on genes which pass the mean count filter)
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18 #
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19 # the first variable in 'factors' will be the primary factor.
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20 # the levels of the primary factor are used in the order of appearance in factors.
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21 #
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22 # by default, levels in the order A,B,C produces a single comparison of B vs A, to a single file 'outfile'
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23 #
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24 # for the 'many_contrasts' flag, levels in the order A,B,C produces comparisons C vs A, B vs A, C vs B,
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25 # to a number of files using the 'outfile' prefix: 'outfile.condition_C_vs_A' etc.
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26 # all plots will still be sent to a single PDF, named by the arg 'plots', with extra pages.
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27 #
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28 # fit_type is an integer valued argument, with the options from ?estimateDisperions
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29 # 1 "parametric"
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30 # 2 "local"
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31 # 3 "mean"
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33 # setup R error handling to go to stderr
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34 options(show.error.messages = F, error = function() {
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35 cat(geterrmessage(), file = stderr()); q("no", 1, F)
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36 })
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38 # we need that to not crash galaxy with an UTF8 error on German LC settings.
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39 loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
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41 library("getopt")
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42 library("tools")
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43 options(stringAsFactors = FALSE, useFancyQuotes = FALSE)
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44 args <- commandArgs(trailingOnly = TRUE)
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46 # get options, using the spec as defined by the enclosed list.
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47 # we read the options from the default: commandArgs(TRUE).
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48 spec <- matrix(c(
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49 "quiet", "q", 0, "logical",
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50 "help", "h", 0, "logical",
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51 "cores", "s", 0, "integer",
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52 "batch_factors", "w", 1, "character",
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53 "outfile", "o", 1, "character",
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54 "countsfile", "n", 1, "character",
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55 "rlogfile", "r", 1, "character",
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56 "vstfile", "v", 1, "character",
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57 "header", "H", 0, "logical",
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58 "factors", "f", 1, "character",
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59 "files_to_labels", "l", 1, "character",
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60 "plots", "p", 1, "character",
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61 "tximport", "i", 0, "logical",
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62 "txtype", "y", 1, "character",
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63 "tx2gene", "x", 1, "character", # a space-sep tx-to-gene map or GTF/GFF3 file
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64 "esf", "e", 1, "character",
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65 "fit_type", "t", 1, "integer",
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66 "many_contrasts", "m", 0, "logical",
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67 "outlier_replace_off", "a", 0, "logical",
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68 "outlier_filter_off", "b", 0, "logical",
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69 "auto_mean_filter_off", "c", 0, "logical",
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70 "beta_prior_off", "d", 0, "logical"
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71 ), byrow = TRUE, ncol = 4)
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72 opt <- getopt(spec)
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74 # if help was asked for print a friendly message
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75 # and exit with a non-zero error code
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76 if (!is.null(opt$help)) {
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77 cat(getopt(spec, usage = TRUE))
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78 q(status = 1)
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79 }
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81 # enforce the following required arguments
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82 if (is.null(opt$outfile)) {
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83 cat("'outfile' is required\n")
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84 q(status = 1)
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85 }
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86 if (is.null(opt$factors)) {
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87 cat("'factors' is required\n")
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88 q(status = 1)
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89 }
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90
37
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91 verbose <- is.null(opt$quiet)
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92
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93 source_local <- function(fname) {
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94 argv <- commandArgs(trailingOnly = FALSE)
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95 base_dir <- dirname(substring(argv[grep("--file=", argv)], 8))
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96 source(paste(base_dir, fname, sep = "/"))
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97 }
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98
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99 source_local("get_deseq_dataset.R")
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100
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101 suppressPackageStartupMessages({
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102 library("DESeq2")
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103 library("RColorBrewer")
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104 library("gplots")
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105 })
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106
33
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107 if (opt$cores > 1) {
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108 library("BiocParallel")
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109 register(MulticoreParam(opt$cores))
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110 parallel <- TRUE
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111 } else {
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112 parallel <- FALSE
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113 }
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114
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115 # build or read sample table
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116
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117 trim <- function(x) gsub("^\\s+|\\s+$", "", x)
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118
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119 # switch on if 'factors' was provided:
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120 library("rjson")
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121 parser <- newJSONParser()
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122 parser$addData(opt$factors)
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123 factor_list <- parser$getObject()
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124 filenames_to_labels <- fromJSON(opt$files_to_labels)
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125 factors <- sapply(factor_list, function(x) x[[1]])
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126 primary_factor <- factors[1]
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127 filenames_in <- unname(unlist(factor_list[[1]][[2]]))
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128 labs <- unname(unlist(filenames_to_labels[basename(filenames_in)]))
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129 sample_table <- data.frame(
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130 sample = basename(filenames_in),
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131 filename = filenames_in,
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132 row.names = filenames_in,
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133 stringsAsFactors = FALSE
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134 )
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135 for (factor in factor_list) {
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136 factor_name <- trim(factor[[1]])
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137 sample_table[[factor_name]] <- character(nrow(sample_table))
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138 lvls <- sapply(factor[[2]], function(x) names(x))
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139 for (i in seq_along(factor[[2]])) {
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140 files <- factor[[2]][[i]][[1]]
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141 sample_table[files, factor_name] <- trim(lvls[i])
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142 }
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143 sample_table[[factor_name]] <- factor(sample_table[[factor_name]], levels = lvls)
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144 }
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145 rownames(sample_table) <- labs
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146
37
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147 design_formula <- as.formula(paste("~", paste(rev(factors), collapse = " + ")))
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148
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149 # these are plots which are made once for each analysis
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150 generate_generic_plots <- function(dds, factors) {
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151 library("ggplot2")
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152 library("ggrepel")
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153 library("pheatmap")
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154
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155 rld <- rlog(dds)
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156 p <- plotPCA(rld, intgroup = rev(factors))
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157 print(p + geom_text_repel(aes_string(x = "PC1", y = "PC2", label = factor(colnames(dds))), size = 3) + geom_point())
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158 dat <- assay(rld)
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159 dists_rl <- dist(t(dat))
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160 mat <- as.matrix(dists_rl)
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161 colors <- colorRampPalette(rev(brewer.pal(9, "Blues")))(255)
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162 pheatmap(
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163 mat,
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164 clustering_distance_rows = dists_rl,
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165 clustering_distance_cols = dists_rl,
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166 col = colors,
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167 main = "Sample-to-sample distances"
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168 )
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169 plotDispEsts(dds, main = "Dispersion estimates")
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170 }
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171
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172 # these are plots which can be made for each comparison, e.g.
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173 # once for C vs A and once for B vs A
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174 generate_specific_plots <- function(res, threshold, title_suffix) {
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175 use <- res$baseMean > threshold
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176 if (sum(!use) == 0) {
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177 h <- hist(res$pvalue, breaks = 0:50 / 50, plot = FALSE)
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178 barplot(
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179 height = h$counts,
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180 col = "powderblue",
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181 space = 0,
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182 xlab = "p-values",
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183 ylab = "frequency",
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184 main = paste("Histogram of p-values for", title_suffix)
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185 )
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186 text(x = c(0, length(h$counts)), y = 0, label = paste(c(0, 1)), adj = c(0.5, 1.7), xpd = NA)
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187 } else {
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188 h1 <- hist(res$pvalue[!use], breaks = 0:50 / 50, plot = FALSE)
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189 h2 <- hist(res$pvalue[use], breaks = 0:50 / 50, plot = FALSE)
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190 colori <- c("filtered (low count)" = "khaki", "not filtered" = "powderblue")
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191 barplot(
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192 height = rbind(h1$counts, h2$counts),
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193 beside = FALSE,
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194 col = colori,
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195 space = 0,
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196 xlab = "p-values",
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197 ylab = "frequency",
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198 main = paste("Histogram of p-values for", title_suffix)
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199 )
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200 text(x = c(0, length(h1$counts)), y = 0, label = paste(c(0, 1)), adj = c(0.5, 1.7), xpd = NA)
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201 legend("topright", fill = rev(colori), legend = rev(names(colori)), bg = "white")
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202 }
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203 plotMA(res, main = paste("MA-plot for", title_suffix), ylim = range(res$log2FoldChange, na.rm = TRUE))
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204 }
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205
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206 if (verbose) {
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207 cat(paste("primary factor:", primary_factor, "\n"))
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208 if (length(factors) > 1) {
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209 cat(paste("other factors in design:", paste(factors[-length(factors)], collapse = ","), "\n"))
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210 }
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211 cat("\n---------------------\n")
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212 }
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213
37
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214 dds <- get_deseq_dataset(sample_table, header = opt$header, design_formula = design_formula, tximport = opt$tximport, txtype = opt$txtype, tx2gene = opt$tx2gene)
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215 # estimate size factors for the chosen method
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216 if (!is.null(opt$esf)) {
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217 dds <- estimateSizeFactors(dds, type = opt$esf)
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218 }
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219 apply_batch_factors <- function(dds, batch_factors) {
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220 rownames(batch_factors) <- batch_factors$identifier
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221 batch_factors <- subset(batch_factors, select = -c(identifier, condition))
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222 dds_samples <- colnames(dds)
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223 batch_samples <- rownames(batch_factors)
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224 if (!setequal(batch_samples, dds_samples)) {
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225 stop("Batch factor names don't correspond to input sample names, check input files")
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226 }
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227 dds_data <- colData(dds)
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228 # Merge dds_data with batch_factors using indexes, which are sample names
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229 # Set sort to False, which maintains the order in dds_data
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230 reordered_batch <- merge(dds_data, batch_factors, by.x = 0, by.y = 0, sort = F)
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231 batch_factors <- reordered_batch[, ncol(dds_data):ncol(reordered_batch)]
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232 for (factor in colnames(batch_factors)) {
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233 dds[[factor]] <- batch_factors[[factor]]
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234 }
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235 colnames(dds) <- reordered_batch[, 1]
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236 return(dds)
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237 }
27
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238
29
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239 if (!is.null(opt$batch_factors)) {
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240 batch_factors <- read.table(opt$batch_factors, sep = "\t", header = T)
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241 dds <- apply_batch_factors(dds = dds, batch_factors = batch_factors)
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242 batch_design <- colnames(batch_factors)[-c(1, 2)]
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243 design_formula <- as.formula(paste("~", paste(c(batch_design, rev(factors)), collapse = " + ")))
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244 design(dds) <- design_formula
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245 }
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246
27
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247 if (verbose) {
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248 cat("DESeq2 run information\n\n")
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249 cat("sample table:\n")
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250 print(sample_table[, -c(1:2), drop = FALSE])
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251 cat("\ndesign formula:\n")
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252 print(design_formula)
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253 cat("\n\n")
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254 cat(paste(ncol(dds), "samples with counts over", nrow(dds), "genes\n"))
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255 }
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256
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257 # optional outlier behavior
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258 if (is.null(opt$outlier_replace_off)) {
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259 min_rep <- 7
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260 } else {
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261 min_rep <- Inf
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262 if (verbose) cat("outlier replacement off\n")
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263 }
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264 if (is.null(opt$outlier_filter_off)) {
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265 cooks_cutoff <- TRUE
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266 } else {
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267 cooks_cutoff <- FALSE
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268 if (verbose) cat("outlier filtering off\n")
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269 }
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270
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271 # optional automatic mean filtering
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272 if (is.null(opt$auto_mean_filter_off)) {
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273 independent_filtering <- TRUE
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274 } else {
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275 independent_filtering <- FALSE
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276 if (verbose) cat("automatic filtering on the mean off\n")
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277 }
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278
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279 # shrinkage of LFCs
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280 if (is.null(opt$beta_prior_off)) {
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281 beta_prior <- TRUE
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282 } else {
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283 beta_prior <- FALSE
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284 if (verbose) cat("beta prior off\n")
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285 }
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286
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287 # dispersion fit type
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288 if (is.null(opt$fit_type)) {
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289 fit_type <- "parametric"
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290 } else {
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291 fit_type <- c("parametric", "local", "mean")[opt$fit_type]
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292 }
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293
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294 if (verbose) cat(paste("using disperion fit type:", fit_type, "\n"))
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295
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296 # run the analysis
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297 dds <- DESeq(dds, fitType = fit_type, betaPrior = beta_prior, minReplicatesForReplace = min_rep, parallel = parallel)
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298
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299 # create the generic plots and leave the device open
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300 if (!is.null(opt$plots)) {
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301 if (verbose) cat("creating plots\n")
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302 pdf(opt$plots)
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303 generate_generic_plots(dds, factors)
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304 }
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305
37
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306 n <- nlevels(colData(dds)[[primary_factor]])
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307 all_levels <- levels(colData(dds)[[primary_factor]])
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308
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309 if (!is.null(opt$countsfile)) {
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310 normalized_counts <- counts(dds, normalized = TRUE)
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311 write.table(normalized_counts, file = opt$countsfile, sep = "\t", col.names = NA, quote = FALSE)
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312 }
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313
30
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314 if (!is.null(opt$rlogfile)) {
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315 rlog_normalized <- rlogTransformation(dds)
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316 rlog_normalized_mat <- assay(rlog_normalized)
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317 write.table(rlog_normalized_mat, file = opt$rlogfile, sep = "\t", col.names = NA, quote = FALSE)
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318 }
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319
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320 if (!is.null(opt$vstfile)) {
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321 vst_normalized <- varianceStabilizingTransformation(dds)
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322 vst_normalized_mat <- assay(vst_normalized)
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323 write.table(vst_normalized_mat, file = opt$vstfile, sep = "\t", col.names = NA, quote = FALSE)
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324 }
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325
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326
17
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327 if (is.null(opt$many_contrasts)) {
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328 # only contrast the first and second level of the primary factor
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329 ref <- all_levels[1]
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330 lvl <- all_levels[2]
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331 res <- results(
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diff changeset
332 dds,
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333 contrast = c(primary_factor, lvl, ref),
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334 cooksCutoff = cooks_cutoff,
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diff changeset
335 independentFiltering = independent_filtering
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diff changeset
336 )
17
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337 if (verbose) {
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338 cat("summary of results\n")
37
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339 cat(paste0(primary_factor, ": ", lvl, " vs ", ref, "\n"))
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340 print(summary(res))
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341 }
37
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342 res_sorted <- res[order(res$padj), ]
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343 out_df <- as.data.frame(res_sorted)
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344 out_df$geneID <- rownames(out_df) # nolint
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345 out_df <- out_df[, c("geneID", "baseMean", "log2FoldChange", "lfcSE", "stat", "pvalue", "padj")]
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346 filename <- opt$outfile
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347 write.table(out_df, file = filename, sep = "\t", quote = FALSE, row.names = FALSE, col.names = FALSE)
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348 if (independent_filtering) {
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349 threshold <- unname(attr(res, "filterThreshold"))
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350 } else {
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351 threshold <- 0
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352 }
37
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353 title_suffix <- paste0(primary_factor, ": ", lvl, " vs ", ref)
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354 if (!is.null(opt$plots)) {
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355 generate_specific_plots(res, threshold, title_suffix)
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356 }
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357 } else {
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358 # rotate through the possible contrasts of the primary factor
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359 # write out a sorted table of results with the contrast as a suffix
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360 # add contrast specific plots to the device
37
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361 for (i in seq_len(n - 1)) {
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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362 ref <- all_levels[i]
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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363 contrast_levels <- all_levels[(i + 1):n]
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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364 for (lvl in contrast_levels) {
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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365 res <- results(
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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366 dds,
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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367 contrast = c(primary_factor, lvl, ref),
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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368 cooksCutoff = cooks_cutoff,
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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369 independentFiltering = independent_filtering
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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370 )
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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371 res_sorted <- res[order(res$padj), ]
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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372 out_df <- as.data.frame(res_sorted)
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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373 out_df$geneID <- rownames(out_df) # nolint
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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374 out_df <- out_df[, c("geneID", "baseMean", "log2FoldChange", "lfcSE", "stat", "pvalue", "padj")]
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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375 filename <- paste0(primary_factor, "_", lvl, "_vs_", ref)
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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376 write.table(out_df, file = filename, sep = "\t", quote = FALSE, row.names = FALSE, col.names = FALSE)
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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377 if (independent_filtering) {
17
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378 threshold <- unname(attr(res, "filterThreshold"))
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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379 } else {
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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380 threshold <- 0
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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381 }
37
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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382 title_suffix <- paste0(primary_factor, ": ", lvl, " vs ", ref)
17
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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383 if (!is.null(opt$plots)) {
37
951876579237 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 9eb6d07510ccf27d6499172d62c81661078ec57b"
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384 generate_specific_plots(res, threshold, title_suffix)
17
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385 }
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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386 }
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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387 }
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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388 }
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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389
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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390 # close the plot device
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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391 if (!is.null(opt$plots)) {
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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392 cat("closing plot device\n")
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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393 dev.off()
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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394 }
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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395
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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396 cat("Session information:\n\n")
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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397
24930eeff731 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 commit 23559e873291b04840f186edb0b4b85e76359e05
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398 sessionInfo()