Mercurial > repos > mvdbeek > r_goseq_1_22_0

annotate goseq.r @ 14:ade115e181d7 draft

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author mvdbeek
date Thu, 25 Feb 2016 07:23:02 -0500
parents fe71b97cc1a5
children 8ce951313688
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fe71b97cc1a5 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/goseq_1_22_0 commit 85e0f34aec3045f48ca9b1a00db02de199a99c95-dirty
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1 sink(stdout(), type = "message")
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2 library(goseq)
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3 library(optparse)
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4
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5 option_list <- list(
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6 make_option(c("-d", "--dge_file"), type="character", help="Path to file with differential gene expression result"),
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7 make_option(c("-w","--wallenius_tab"), type="character", help="Path to output file with P-values estimated using wallenius distribution."),
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8 make_option(c("-s","--sampling_tab"), type="character", default=FALSE, help="Path to output file with P-values estimated using wallenius distribution."),
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9 make_option(c("-n","--nobias_tab"), type="character", default=FALSE, help="Path to output file with P-values estimated using wallenius distribution and no correction for gene length bias."),
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10 make_option(c("-l","--length_bias_plot"), type="character", default=FALSE, help="Path to length-bias plot."),
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11 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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12 make_option(c("-padj", "--p_adj_column"), type="integer",help="Column that contains p. adjust values"),
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13 make_option(c("-c", "--cutoff"), type="double",dest="p_adj_cutoff",
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14 help="Genes with p.adjust below cutoff are considered not differentially expressed and serve as control genes"),
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15 make_option(c("-r", "--repcnt"), type="integer", default=100, help="Number of repeats for sampling"),
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16 make_option(c("-g", "--genome"), type="character", help = "Genome [used for looking up correct gene length]"),
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17 make_option(c("-i", "--gene_id"), type="character", help="Gene ID of gene column in DGE file")
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18 )
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19 parser <- OptionParser(usage = "%prog [options] file", option_list=option_list)
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20 args = parse_args(parser)
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22 # Vars:
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23 dge_file = args$dge_file
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24 p_adj_column = args$p_adj_colum
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25 p_adj_cutoff = args$p_adj_cutoff
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26 genome = args$genome
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27 gene_id = args$gene_id
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28 wallenius_tab = args$wallenius_tab
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29 sampling_tab = args$sampling_tab
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30 nobias_tab = args$nobias_tab
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31 length_bias_plot = args$length_bias_plot
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32 sample_vs_wallenius_plot = args$sample_vs_wallenius_plot
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33 repcnt = args$repcnt
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36 # format DE genes into vector suitable for use with goseq
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37 dge_table = read.delim(dge_file, header = TRUE, sep="\t", check.names = FALSE)
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38 genes = as.integer(dge_table[,p_adj_column]<p_adj_cutoff)
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39 names(genes) = dge_table[,1] # Assuming first row contains gene names
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40
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41 # Estimate PWF
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42
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43 pdf(length_bias_plot)
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44 pwf=nullp(genes, genome , gene_id)
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45 dev.off()
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46 # Null dstribution wallenius
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47 GO.wall=goseq(pwf, genome, gene_id)
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49 GO.nobias=goseq(pwf, genome, gene_id, method="Hypergeometric")
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51 # Sampling dsitribution
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52 GO.samp=goseq(pwf,genome, gene_id, method="Sampling",repcnt=repcnt)
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54 # Compare sampling with wallenius
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55 pdf(sample_vs_wallenius_plot)
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56 plot(log10(GO.wall[,2]), log10(GO.samp[match(GO.samp[,1],GO.wall[,1]),2]),
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57 xlab="log10(Wallenius p-values)",ylab="log10(Sampling p-values)",
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58 xlim=c(-3,0))
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59 abline(0,1,col=3,lty=2)
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60 dev.off()
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63 write.table(GO.wall, wallenius_tab, sep="\t", row.names = FALSE, quote = FALSE)
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64 write.table(GO.samp, sampling_tab, sep="\t", row.names = FALSE, quote = FALSE)
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65 write.table(GO.nobias, nobias_tab, sep="\t", row.names = FALSE, quote = FALSE)
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67 # Use the following to get a list of supported genomes / gene ids
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69 # write.table(supportedGenomes(), "available_genomes.tab", row.names = FALSE, quote=FALSE)
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70 # write.table(supportedGeneIDs(), "supported_gene_ids.tab", row.name = FALSE, quote = FALSE)
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71 # write.table(table.summary, "input_gene_count_matrix.tab", row.names = FALSE, quote = FALSE)