Mercurial > repos > artbio > small_rna_maps
changeset 0:6d48150495e3 draft
planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
| author | artbio |
|---|---|
| date | Mon, 24 Jul 2017 06:28:45 -0400 |
| parents | |
| children | 40972a8dfab9 |
| files | small_rna_maps.py small_rna_maps.r small_rna_maps.xml test-data/coverage.pdf test-data/doubled.tab test-data/doubled_mean.pdf test-data/input1.bam test-data/input2.bam test-data/mean.pdf test-data/median.pdf test-data/output.tab test-data/sizes.pdf test-data/sizes.tab test-data/test/small_rna_map.bash |
| diffstat | 14 files changed, 14045 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/small_rna_maps.py Mon Jul 24 06:28:45 2017 -0400 @@ -0,0 +1,204 @@ +import argparse +from collections import defaultdict + +import numpy + +import pysam + + +def Parser(): + the_parser = argparse.ArgumentParser() + the_parser.add_argument('--input', dest='input', required=True, + nargs='+', help='input BAM files') + the_parser.add_argument('--sample_name', dest='sample_name', + required=True, nargs='+', help='sample name') + the_parser.add_argument('--output', action='store', + type=str, help='output tabular file') + the_parser.add_argument('-S', '--sizes', action='store', + help='use to output read sizes dataframe') + args = the_parser.parse_args() + return args + + +class Map: + + def __init__(self, bam_file, sample, computeSize=False): + self.sample_name = sample + self.bam_object = pysam.AlignmentFile(bam_file, 'rb') + self.chromosomes = dict(zip(self.bam_object.references, + self.bam_object.lengths)) + self.map_dict = self.create_map(self.bam_object) + self.max = self.compute_max(self.map_dict) + self.mean = self.compute_mean(self.map_dict) + self.median = self.compute_median(self.map_dict) + self.coverage = self.compute_coverage(self.map_dict) + if computeSize: + self.size = self.compute_size(self.map_dict) + + def create_map(self, bam_object): + ''' + Returns a map_dictionary {(chromosome,read_position,polarity): + [read_length, ...]} + ''' + map_dictionary = defaultdict(list) + # get empty value for start and end of each chromosome + for chrom in self.chromosomes: + map_dictionary[(chrom, 1, 'F')] = [] + map_dictionary[(chrom, self.chromosomes[chrom], 'F')] = [] + for chrom in self.chromosomes: + for read in bam_object.fetch(chrom): + positions = read.positions # a list of covered positions + for pos in positions: + if not map_dictionary[(chrom, pos+1, 'F')]: + map_dictionary[(chrom, pos+1, 'F')] = [] + if not map_dictionary[(chrom, pos+1, 'R')]: + map_dictionary[(chrom, pos+1, 'R')] = [] + if read.is_reverse: + map_dictionary[(chrom, positions[-1]+1, + 'R')].append(read.query_alignment_length) + else: + map_dictionary[(chrom, positions[0]+1, + 'F')].append(read.query_alignment_length) + return map_dictionary + + def compute_max(self, map_dictionary): + ''' + takes a map_dictionary as input and returns + a max_dictionary {(chromosome,read_position,polarity): + max_of_number_of_read_at_any_position} + ''' + merge_keylist = [(i[0], 0) for i in map_dictionary.keys()] + max_dictionary = dict(merge_keylist) + for key in map_dictionary: + if len(map_dictionary[key]) > max_dictionary[key[0]]: + max_dictionary[key[0]] = len(map_dictionary[key]) + return max_dictionary + + def compute_mean(self, map_dictionary): + ''' + takes a map_dictionary as input and returns + a mean_dictionary {(chromosome,read_position,polarity): + mean_value_of_reads} + ''' + mean_dictionary = dict() + for key in map_dictionary: + if len(map_dictionary[key]) == 0: + mean_dictionary[key] = 0 + else: + mean_dictionary[key] = round(numpy.mean(map_dictionary[key]), + 1) + return mean_dictionary + + def compute_median(self, map_dictionary): + ''' + takes a map_dictionary as input and returns + a mean_dictionary {(chromosome,read_position,polarity): + mean_value_of_reads} + ''' + median_dictionary = dict() + for key in map_dictionary: + if len(map_dictionary[key]) == 0: + median_dictionary[key] = 0 + else: + median_dictionary[key] = numpy.median(map_dictionary[key]) + return median_dictionary + + def compute_coverage(self, map_dictionary, quality=10): + ''' + takes a map_dictionary as input and returns + a coverage_dictionary {(chromosome,read_position,polarity): + coverage} + ''' + coverage_dictionary = dict() + for chrom in self.chromosomes: + coverage_dictionary[(chrom, 1, 'F')] = 0 + coverage_dictionary[(chrom, self.chromosomes[chrom], 'F')] = 0 + + for key in map_dictionary: + coverage = self.bam_object.count_coverage( + reference=key[0], + start=key[1]-1, + end=key[1], + quality_threshold=quality) + """ Add the 4 coverage values """ + coverage = [sum(x) for x in zip(*coverage)] + coverage_dictionary[key] = coverage[0] + # coverage_dictionary[(key[0], key[1], 'R')] = coverage + return coverage_dictionary + + def compute_size(self, map_dictionary): + ''' + Takes a map_dictionary and returns a dictionary of sizes: + {chrom: {polarity: {size: nbre of reads}}} + ''' + size_dictionary = defaultdict(lambda: defaultdict( + lambda: defaultdict( int ))) + # to track empty chromosomes + for chrom in self.chromosomes: + if self.bam_object.count(chrom) == 0: + size_dictionary[chrom]['F'][10] = 0 + for key in map_dictionary: + for size in map_dictionary[key]: + size_dictionary[key[0]][key[2]][size] += 1 + return size_dictionary + + def write_size_table(self, out): + ''' + Dataset, Chromosome, Polarity, Size, Nbr_reads + out is an *open* file handler + ''' + for chrom in sorted(self.size): + sizes = self.size[chrom]['F'].keys() + sizes.extend(self.size[chrom]['R'].keys()) + for polarity in sorted(self.size[chrom]): + for size in range(min(sizes), max(sizes)+1): + try: + line = [self.sample_name, chrom, polarity, size, + self.size[chrom][polarity][size]] + except KeyError: + line = [self.sample_name, chrom, polarity, size, 0] + line = [str(i) for i in line] + out.write('\t'.join(line) + '\n') + + def write_table(self, out): + ''' + Dataset, Chromosome, Chrom_length, Coordinate, Nbr_reads + Polarity, Max, Mean, Median, Coverage + out is an *open* file handler + ''' + for key in sorted(self.map_dict): + line = [self.sample_name, key[0], self.chromosomes[key[0]], + key[1], len(self.map_dict[key]), key[2], self.max[key[0]], + self.mean[key], self.median[key], self.coverage[key]] + line = [str(i) for i in line] + out.write('\t'.join(line) + '\n') + + +def main(inputs, samples, file_out, size_file_out=''): + F = open(file_out, 'w') + header = ["Dataset", "Chromosome", "Chrom_length", "Coordinate", + "Nbr_reads", "Polarity", "Max", "Mean", "Median", "Coverage"] + F.write('\t'.join(header) + '\n') + if size_file_out: + Fs = open(size_file_out, 'w') + header = ["Dataset", "Chromosome", "Polarity", "Size", "Nbr_reads"] + Fs.write('\t'.join(header) + '\n') + for file, sample in zip(inputs, samples): + mapobj = Map(file, sample, computeSize=True) + mapobj.write_table(F) + mapobj.write_size_table(Fs) + Fs.close() + else: + for file, sample in zip(inputs, samples): + mapobj = Map(file, sample, computeSize=False) + mapobj.write_table(F) + F.close() + + +if __name__ == "__main__": + args = Parser() + # if identical sample names + if len(set(args.sample_name)) != len(args.sample_name): + args.sample_name = [name + '_' + str(i) for + i, name in enumerate(args.sample_name)] + main(args.input, args.sample_name, args.output, args.sizes)
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/small_rna_maps.r Mon Jul 24 06:28:45 2017 -0400 @@ -0,0 +1,141 @@ +## Setup R error handling to go to stderr +options( show.error.messages=F, + error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } ) +warnings() +library(RColorBrewer) +library(lattice) +library(latticeExtra) +library(grid) +library(gridExtra) +library(optparse) + +option_list <- list( + make_option(c("-r", "--output_tab"), type="character", help="path to tabular file"), + make_option(c("-s", "--sizes"), type="character", help="path to size dataframe"), + make_option("--output_pdf", type = "character", help="path to the pdf file with plot"), + make_option("--extra_plot", type = "character", help="what additional data should be plotted") + ) + +parser <- OptionParser(usage = "%prog [options] file", option_list = option_list) +args = parse_args(parser) +if (length(args$sizes) != 0) { args$extra_plot <- "SizeDistribution"} + +# dataset manipulation + +Table = read.delim(args$output_tab, header=T, row.names=NULL) +Table <- within(Table, Nbr_reads[Polarity=="R"] <- (Nbr_reads[Polarity=="R"]*-1)) +n_samples=length(unique(Table$Dataset)) +genes=unique(levels(Table$Chromosome)) +per_gene_readmap=lapply(genes, function(x) subset(Table, Chromosome==x)) +per_gene_limit=lapply(genes, function(x) c(1, unique(subset(Table, Chromosome==x)$Chrom_length)) ) +n_genes=length(per_gene_readmap) +if (args$extra_plot == "SizeDistribution") { + size=read.delim(args$sizes, header=T, row.names=NULL) + size <- within(size, Nbr_reads[Polarity=="R"] <- (Nbr_reads[Polarity=="R"]*-1)) + per_gene_size=lapply(genes, function(x) subset(size, Chromosome==x)) + } + +## end of data frames implementation + +## functions + +plot_readmap=function(df, ...) { + combineLimits(xyplot(Nbr_reads~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)), + data=df, + type='h', + lwd=1.5, + scales= list(relation="free", x=list(rot=0, cex=0.7, axs="i", tck=0.5), y=list(tick.number=4, rot=90, cex=0.7)), + xlab=NULL, main=NULL, ylab=NULL, + as.table=T, + origin = 0, + horizontal=FALSE, + group=Polarity, + col=c("red","blue"), + par.strip.text = list(cex=0.7), + ...)) + } + + +plot_size=function(df, ...) { + #smR.prepanel=function(x,y,...) {; yscale=c(y*0, max(abs(y)));list(ylim=yscale);} + sizeplot = xyplot(eval(as.name(args$extra_plot))~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)), + data=df, + type='p', + cex=0.35, + pch=19, + scales= list(relation="free", x=list(rot=0, cex=0, axs="i", tck=0.5), y=list(tick.number=4, rot=90, cex=0.7)), + xlab=NULL, main=NULL, ylab=NULL, + as.table=T, + origin = 0, + horizontal=FALSE, + group=Polarity, + col=c("darkred","darkblue"), + par.strip.text = list(cex=0.7), + ...) + combineLimits(sizeplot) + } + +plot_size_distribution= function(df, ...) { +# smR.prepanel=function(x,y,...){; yscale=c(-max(abs(y)), max(abs(y)));list(ylim=yscale);} + bc= barchart(Nbr_reads~as.factor(Size)|factor(Dataset, levels=unique(Dataset))+Chromosome, data = df, origin = 0, + horizontal=FALSE, +group=Polarity, +stack=TRUE, + col=c('red', 'blue'), + cex=0.75, + scales=list(y=list(tick.number=4, rot=90, relation="free", cex=0.7), x=list(cex=0.7) ), +# prepanel=smR.prepanel, + xlab = NULL, + ylab = NULL, + main = NULL, + as.table=TRUE, + newpage = T, + par.strip.text = list(cex=0.7), + ...) + combineLimits(bc) + } + + +## end of functions + +## function parameters +par.settings.readmap=list(layout.heights=list(top.padding=0, bottom.padding=0), strip.background = list(col=c("lightblue","lightgreen")) ) +par.settings.size=list(layout.heights=list(top.padding=0, bottom.padding=0)) +graph_title=list(Coverage="Read Maps and Coverages", Median="Read Maps and Median sizes", Mean="Read Maps and Mean sizes", SizeDistribution="Read Maps and Size Distributions") +graph_legend=list(Coverage="Read counts / Coverage", Median="Read counts / Median size", Mean="Read counts / Mean size", SizeDistribution="Read counts") +graph_bottom=list(Coverage="Nucleotide coordinates", Median="Nucleotide coordinates", Mean="Nucleotide coordinates", SizeDistribution="Read sizes / Nucleotide coordinates") +## end of function parameters' + +## GRAPHS + +if (n_genes > 5) {page_height_simple = 11.69; page_height_combi=11.69; rows_per_page=6} else { + rows_per_page= n_genes; page_height_simple = 2.5*n_genes; page_height_combi=page_height_simple*2 } +if (n_samples > 4) {page_width = 8.2677*n_samples/4} else {page_width = 8.2677*n_samples/2} # to test + + +pdf(file=args$output_pdf, paper="special", height=page_height_simple, width=page_width) +if (rows_per_page %% 2 != 0) { rows_per_page = rows_per_page + 1} +for (i in seq(1,n_genes,rows_per_page/2)) { + start=i + end=i+rows_per_page/2-1 + if (end>n_genes) {end=n_genes} + readmap_plot.list=lapply(per_gene_readmap[start:end], function(x) plot_readmap(x, strip=FALSE, par.settings=par.settings.readmap)) + if (args$extra_plot == "SizeDistribution") { + size_plot.list=lapply(per_gene_size[start:end], function(x) plot_size_distribution(x, par.settings=par.settings.size)) + } + else { + size_plot.list=lapply(per_gene_readmap[start:end], function(x) plot_size(x, par.settings=par.settings.size)) + } + + + plot.list=rbind(size_plot.list, readmap_plot.list) + args_list=c(plot.list, list(nrow=rows_per_page+1, ncol=1, + top=textGrob(graph_title[[args$extra_plot]], gp=gpar(cex=1), just="top"), + left=textGrob(graph_legend[[args$extra_plot]], gp=gpar(cex=1), vjust=1, rot=90), + sub=textGrob(graph_bottom[[args$extra_plot]], gp=gpar(cex=1), just="bottom") + ) + ) +do.call(grid.arrange, args_list) +} +devname=dev.off() +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/small_rna_maps.xml Mon Jul 24 06:28:45 2017 -0400 @@ -0,0 +1,129 @@ +<tool id="small_rna_maps" name="small_rna_maps" version="0.9.0"> + <description></description> + <requirements> + <requirement type="package" version="1.11.2=py27_0">numpy</requirement> + <requirement type="package" version="0.11.2.1=py27_0">pysam</requirement> + <requirement type="package" version="1.3.2=r3.3.1_0">r-optparse</requirement> + <requirement type="package" version="0.6_28=r3.3.1_0">r-latticeextra</requirement> + <requirement type="package" version="2.2.1=r3.3.1_0">r-gridextra</requirement> + </requirements> + <stdio> + <exit_code range="1:" level="fatal" description="Tool exception" /> + </stdio> + <command detect_errors="exit_code"><![CDATA[ + #for $file in $input + samtools index '$file' && + #end for + python '$__tool_directory__'/small_rna_maps.py + --input + #for $file in $input + '$file' + #end for + --sample_name + #for $sample in $input + '$sample.name' + #end for + #if $extra_plot == 'Sizes': + --sizes '$output_sizes' + #end if + --output '$output_tab' && + Rscript '$__tool_directory__'/small_rna_maps.r --output_tab '$output_tab' + --output_pdf '$output_pdf' + #if $extra_plot != 'Sizes': + --extra_plot '$extra_plot' + #else + --sizes $output_sizes + #end if + ]]></command> + <inputs> + <param name="input" type="data" format="bam" label="Select multiple alignments to parse" multiple="True"/> + <param name="extra_plot" type="select" label="select the type of extra plot in addition to read map"> + <option value="Coverage">Coverage</option> + <option value="Mean">Mean Sizes</option> + <option value="Median">Median Sizes</option> + <option value="Sizes">Size Distributions</option> + </param> + </inputs> + + <outputs> + <data format="tabular" name="output_tab" label="Map dataframe" /> + <data format="tabular" name="output_sizes" label="Size dataframe" > + <filter>extra_plot == "Sizes"</filter> + </data> + <data format="pdf" name="output_pdf" label="PDF file" /> + +</outputs> + + <tests> + <test> + <param name="input" value="input1.bam,input2.bam" ftype="bam"/> + <param name="extra_plot" value="Mean" /> + <output file="output.tab" name="output_tab" /> + <output file="mean.pdf" name="output_pdf" /> + </test> + <test> + <param name="input" value="input1.bam,input1.bam" ftype="bam"/> + <param name="extra_plot" value="Mean" /> + <output file="doubled.tab" name="output_tab" /> + <output file="doubled_mean.pdf" name="output_pdf" /> + </test> + <test> + <param name="input" value="input1.bam,input2.bam" ftype="bam"/> + <param name="extra_plot" value="Median" /> + <output file="output.tab" name="output_tab" /> + <output file="median.pdf" name="output_pdf" /> + </test> + <test> + <param name="input" value="input1.bam,input2.bam" ftype="bam"/> + <param name="extra_plot" value="Coverage" /> + <output file="output.tab" name="output_tab" /> + <output file="coverage.pdf" name="output_pdf" /> + </test> + <test> + <param name="input" value="input1.bam,input2.bam" ftype="bam"/> + <param name="extra_plot" value="Sizes" /> + <output file="output.tab" name="output_tab" /> + <output file="sizes.tab" name="output_sizes" /> + <output file="sizes.pdf" name="output_pdf" /> + </test> + </tests> + + +<help> + +**What it does** + +Generate read count maps from alignment BAM files, using pysam and lattice. + +In addition to the read counts (lower graphs), median size, mean size and coverage depth of reads(lower graphs) mapping at a given position are plotted. + +**Inputs** + +bam alignment files that *must* be + + - single-read + - sorted + - mapping to the same reference + +**Output** + +A pdf file generated by the R package lattice + +One or two dataframes used to plot data + +</help> + +<citations> + <citation type="doi">10.1093/bioinformatics/btp352</citation> + <citation type="bibtex">@Book{, + title = {Lattice: Multivariate Data Visualization with R}, + author = {Deepayan Sarkar}, + publisher = {Springer}, + address = {New York}, + year = {2008}, + note = {ISBN 978-0-387-75968-5}, + url = {http://lmdvr.r-forge.r-project.org}, + }</citation> +</citations> +</tool> +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/doubled.tab Mon Jul 24 06:28:45 2017 -0400 @@ -0,0 +1,6339 @@ +Dataset Chromosome Chrom_length Coordinate Nbr_reads Polarity Max Mean Median Coverage +input1.bam_0 FBtr0070001 72 1 1 F 27 17.0 17.0 1 +input1.bam_0 FBtr0070001 72 1 0 R 27 0 0 1 +input1.bam_0 FBtr0070001 72 2 0 F 27 0 0 1 +input1.bam_0 FBtr0070001 72 2 0 R 27 0 0 1 +input1.bam_0 FBtr0070001 72 3 0 F 27 0 0 1 +input1.bam_0 FBtr0070001 72 3 0 R 27 0 0 1 +input1.bam_0 FBtr0070001 72 4 0 F 27 0 0 1 +input1.bam_0 FBtr0070001 72 4 0 R 27 0 0 1 +input1.bam_0 FBtr0070001 72 5 0 F 27 0 0 1 +input1.bam_0 FBtr0070001 72 5 0 R 27 0 0 1 +input1.bam_0 FBtr0070001 72 6 0 F 27 0 0 1 +input1.bam_0 FBtr0070001 72 6 0 R 27 0 0 1 +input1.bam_0 FBtr0070001 72 7 6 F 27 20.3 21.0 7 +input1.bam_0 FBtr0070001 72 7 0 R 27 0 0 7 +input1.bam_0 FBtr0070001 72 8 3 F 27 21.3 21.0 10 +input1.bam_0 FBtr0070001 72 8 0 R 27 0 0 10 +input1.bam_0 FBtr0070001 72 9 0 F 27 0 0 10 +input1.bam_0 FBtr0070001 72 9 0 R 27 0 0 10 +input1.bam_0 FBtr0070001 72 10 0 F 27 0 0 10 +input1.bam_0 FBtr0070001 72 10 0 R 27 0 0 10 +input1.bam_0 FBtr0070001 72 11 2 F 27 20.5 20.5 12 +input1.bam_0 FBtr0070001 72 11 0 R 27 0 0 12 +input1.bam_0 FBtr0070001 72 12 0 F 27 0 0 12 +input1.bam_0 FBtr0070001 72 12 0 R 27 0 0 12 +input1.bam_0 FBtr0070001 72 13 0 F 27 0 0 12 +input1.bam_0 FBtr0070001 72 13 0 R 27 0 0 12 +input1.bam_0 FBtr0070001 72 14 0 F 27 0 0 12 +input1.bam_0 FBtr0070001 72 14 0 R 27 0 0 12 +input1.bam_0 FBtr0070001 72 15 0 F 27 0 0 12 +input1.bam_0 FBtr0070001 72 15 0 R 27 0 0 12 +input1.bam_0 FBtr0070001 72 16 1 F 27 19.0 19.0 13 +input1.bam_0 FBtr0070001 72 16 0 R 27 0 0 13 +input1.bam_0 FBtr0070001 72 17 1 F 27 23.0 23.0 14 +input1.bam_0 FBtr0070001 72 17 0 R 27 0 0 14 +input1.bam_0 FBtr0070001 72 18 1 F 27 16.0 16.0 14 +input1.bam_0 FBtr0070001 72 18 0 R 27 0 0 14 +input1.bam_0 FBtr0070001 72 19 0 F 27 0 0 14 +input1.bam_0 FBtr0070001 72 19 0 R 27 0 0 14 +input1.bam_0 FBtr0070001 72 20 0 F 27 0 0 14 +input1.bam_0 FBtr0070001 72 20 0 R 27 0 0 14 +input1.bam_0 FBtr0070001 72 21 0 F 27 0 0 14 +input1.bam_0 FBtr0070001 72 21 0 R 27 0 0 14 +input1.bam_0 FBtr0070001 72 22 0 F 27 0 0 14 +input1.bam_0 FBtr0070001 72 22 0 R 27 0 0 14 +input1.bam_0 FBtr0070001 72 23 0 F 27 0 0 13 +input1.bam_0 FBtr0070001 72 23 0 R 27 0 0 13 +input1.bam_0 FBtr0070001 72 24 0 F 27 0 0 13 +input1.bam_0 FBtr0070001 72 24 0 R 27 0 0 13 +input1.bam_0 FBtr0070001 72 25 0 F 27 0 0 13 +input1.bam_0 FBtr0070001 72 25 0 R 27 0 0 13 +input1.bam_0 FBtr0070001 72 26 0 F 27 0 0 13 +input1.bam_0 FBtr0070001 72 26 0 R 27 0 0 13 +input1.bam_0 FBtr0070001 72 27 2 F 27 23.5 23.5 14 +input1.bam_0 FBtr0070001 72 27 0 R 27 0 0 14 +input1.bam_0 FBtr0070001 72 28 0 F 27 0 0 11 +input1.bam_0 FBtr0070001 72 28 0 R 27 0 0 11 +input1.bam_0 FBtr0070001 72 29 0 F 27 0 0 8 +input1.bam_0 FBtr0070001 72 29 0 R 27 0 0 8 +input1.bam_0 FBtr0070001 72 30 1 F 27 23.0 23.0 9 +input1.bam_0 FBtr0070001 72 30 0 R 27 0 0 9 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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/sizes.tab Mon Jul 24 06:28:45 2017 -0400 @@ -0,0 +1,1045 @@ +Dataset Chromosome Polarity Size Nbr_reads +input1.bam FBtr0070001 F 16 2 +input1.bam FBtr0070001 F 17 1 +input1.bam FBtr0070001 F 18 0 +input1.bam FBtr0070001 F 19 1 +input1.bam FBtr0070001 F 20 4 +input1.bam FBtr0070001 F 21 4 +input1.bam FBtr0070001 F 22 29 +input1.bam FBtr0070001 F 23 15 +input1.bam FBtr0070001 F 24 1 +input1.bam FBtr0070001 R 16 0 +input1.bam FBtr0070001 R 17 0 +input1.bam FBtr0070001 R 18 0 +input1.bam FBtr0070001 R 19 0 +input1.bam FBtr0070001 R 20 0 +input1.bam FBtr0070001 R 21 0 +input1.bam FBtr0070001 R 22 0 +input1.bam FBtr0070001 R 23 0 +input1.bam FBtr0070001 R 24 0 +input1.bam FBtr0070533 F 15 2 +input1.bam FBtr0070533 F 16 1 +input1.bam FBtr0070533 F 17 1 +input1.bam FBtr0070533 F 18 6 +input1.bam FBtr0070533 F 19 3 +input1.bam FBtr0070533 F 20 2 +input1.bam FBtr0070533 F 21 2 +input1.bam FBtr0070533 F 22 4 +input1.bam FBtr0070533 F 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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test/small_rna_map.bash Mon Jul 24 06:28:45 2017 -0400 @@ -0,0 +1,43 @@ +#! /bin/bash +# Execution command : bash small_rna_map.bash <sam file> +samtools view -h -o input.sam ../test-data/input.bam +samfile="input.sam" +cut -f2,3,4,5,6 ../test-data/output.tab > test-data.dat +grep -e "^@SQ" $samfile > header.tab +cat $samfile | perl -ne 'print unless /^@/ or ( (split /\t/)[1] != 0 and (split /\t/)[1] != 16 )' > output1.tab + +cat << EOF > pyscript.py +lendic = {} +for line in open("header.tab"): + fields = line[:-1].split() + lendic[fields[1][3:]] = fields[2][3:] +readdic = {} +for line in (open("output1.tab")): + fields = line[:-1].split() + key = "-".join([fields[2],fields[3],"F" if fields[1]=="0" else "R"]) + try: + readdic[key] += 1 + except KeyError: + readdic[key] = 1 +Out = open("output.tab", "w") +Out.write("Chromosome\tChrom_length\tCoordinate\tNbr_reads\tPolarity\n") +for key in sorted(readdic): + fields = key.split("-") + Chromosome, Coordinate, Polarity = fields[0], fields[1], fields[2] + Chrom_length = lendic[Chromosome] + Nbr_reads = str(readdic[key]) + Out.write("\t".join([Chromosome, Chrom_length, Coordinate, Nbr_reads, Polarity]) ) + Out.write("\n") +Out.close +EOF + +python ./pyscript.py +rm output1.tab header.tab pyscript.py +sort -k 1,1 -k 3,3n -k 5,5 output.tab -o output.tab +if ! diff -q output.tab test-data.dat &>/dev/null; then + >&2 echo "different" +else + >&2 echo "Test passed" +fi + +rm output.tab input.sam test-data.dat