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comparison tools/spades_3_0/plot_spades_stats.xml @ 8:ff058438080a draft

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Version 0.8, supports SPAdes 3.0.0
author lionelguy
date Wed, 05 Feb 2014 05:19:03 -0500
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7:95ddc2380130 8:ff058438080a
1 <tool id="plot_spades_stats" name="SPAdes stats" version="0.1">
2 <description>coverage vs. length plot</description>
3 <requirements>
4 <requirement type="package">R</requirement>
5 </requirements>
6 <command interpreter="bash">r_wrapper.sh $script_file</command>
7
8 <inputs>
9 <param name="input_scaffolds" type="data" format="tabular" label="Scaffold stats"/>
10 <param name="input_contigs" type="data" format="tabular" label="Contig stats"/>
11 <param name="length_co" type="integer" value="1000" min="0" label="Length cut-off" help="Contigs with length under that value are shown in red"/>
12 <param name="coverage_co" type="integer" value="10" min="0" label="Coverage cut-off" help="Contigs with length under that value are shown in red"/>
13 </inputs>
14 <configfiles>
15 <configfile name="script_file">
16 ## Setup R error handling to go to stderr
17 options( show.error.messages=F,
18 error = function () {
19 cat( geterrmessage(), file=stderr() ); q( "no", 1, F )
20 } )
21 files = c("${input_contigs}", "${input_scaffolds}")
22 types = c("Contigs", "Scaffolds")
23
24 ## Start plotting device
25 png("${out_file}", w=500, h=1000)
26 par(mfrow=c(2,1))
27
28 ## Loop over the two files
29 for (i in 1:length(types)){
30 seqs = read.table(files[i], header=FALSE, comment.char="#")
31 colnames = c("name", "length", "coverage")
32 names(seqs) = colnames
33
34 ## Stats over all sequences
35 sl_all = sort(seqs\$length, decreasing=TRUE)
36 cs_all = cumsum(sl_all)
37 s_all = sum(seqs\$length)
38 n50_idx_all = which.min(sl_all[cs_all &lt; 0.5*s_all])
39 n90_idx_all = which.min(sl_all[cs_all &lt; 0.9*s_all])
40 n50_all = sl_all[n50_idx_all]
41 n90_all = sl_all[n90_idx_all]
42
43 ## Filter short seqs, redo stats
44 seqs_filt = seqs[seqs\$length >= ${length_co} &amp; seqs\$coverage >= ${coverage_co},]
45 if (nrow(seqs_filt) > 0){
46 sl_filt = sort(seqs_filt\$length, decreasing=TRUE)
47 cs_filt = cumsum(sl_filt)
48 s_filt = sum(seqs_filt\$length)
49 n50_idx_filt = which.min(sl_filt[cs_filt &lt; 0.5*s_filt])
50 n90_idx_filt = which.min(sl_filt[cs_filt &lt; 0.9*s_filt])
51 n50_filt = sl_filt[n50_idx_filt]
52 n90_filt = sl_filt[n90_idx_filt]
53 }
54 seqs_bad = seqs[seqs\$length &lt; ${length_co} | seqs\$coverage &lt; ${coverage_co},]
55
56 ## Length vs coverage
57 plot(length~coverage, data=seqs, log="xy", type="n", main=paste(types[i], ": coverage vs. length", sep=""), xlab="Coverage", ylab="Length")
58 if (nrow(seqs_bad) > 0){
59 points(length~coverage, data=seqs_bad, cex=0.5, col="red")
60 }
61 if (nrow(seqs_filt) > 0){
62 points(length~coverage, data=seqs_filt, cex=0.5, col="black")
63 }
64 abline(v=${coverage_co}, h=${length_co}, lty=2, col=grey(0.3))
65 legend(x="topleft", legend=c("Before/after filtering", paste(c("N50: ", "N90: ", "Median cov.: "), c(n50_all, n90_all, round(median(seqs\$coverage))), rep("/", 3), c(n50_filt, n90_filt, round(median(seqs_filt\$coverage))), sep="")), cex=0.8)
66 }
67 dev.off()
68 </configfile>
69 </configfiles>
70 <outputs>
71 <data format="png" name="out_file" />
72 </outputs>
73 <help>
74 **What it does**
75
76 Using the output of SPAdes (a pair of fasta file and stat file for each of the contigs and scaffolds), it produces a coverage vs. contig plot. Each dot represent a contig/scaffold. Given a coverage and a length cutoff, sequences that do not meet those criteria are shown in red. Some statistics are also given (N50, N90, median contig/scaffold length) both before and after filtering.
77
78 Use the "filter SPAdes output" tool to actually filter sequences.
79 </help>
80 </tool>