Mercurial > repos > artbio > small_rna_maps
changeset 2:507383cce5a8 draft
planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit edbb53cb13b52bf8e71c562fa8acc2c3be2fb270
| author | artbio |
|---|---|
| date | Mon, 14 Aug 2017 05:52:34 -0400 |
| parents | 40972a8dfab9 |
| children | ed8b0142538d |
| files | small_rna_maps.py small_rna_maps.py.bak small_rna_maps.r small_rna_maps.xml test-data/coverage.tab test-data/double_mean.tab test-data/doubled.tab test-data/doubled_readmap.tab test-data/mean.tab test-data/median.tab test-data/output.tab test-data/readmap.tab test-data/size.tab test-data/sizes.pdf test-data/sizes.tab |
| diffstat | 15 files changed, 20233 insertions(+), 7493 deletions(-) [+] |
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--- a/small_rna_maps.py Mon Jul 24 12:31:04 2017 -0400 +++ b/small_rna_maps.py Mon Aug 14 05:52:34 2017 -0400 @@ -8,32 +8,28 @@ 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') + the_parser.add_argument('--inputs', dest='inputs', required=True, + nargs='+', help='list of input BAM files') + the_parser.add_argument('--sample_names', dest='sample_names', + required=True, nargs='+', + help='list of sample names') + the_parser.add_argument('--outputs', nargs='+', action='store', + help='list of two output paths (only two)') + the_parser.add_argument('-M', '--plot_methods', nargs='+', action='store', + help='list of 2 plot methods (only two) among:\ + Counts, Max, Mean, Median, Coverage and Size') args = the_parser.parse_args() return args class Map: - def __init__(self, bam_file, sample, computeSize=False): + def __init__(self, bam_file, sample): 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): ''' @@ -59,20 +55,33 @@ 'F')].append(read.query_alignment_length) return map_dictionary - def compute_max(self, map_dictionary): + def compute_map(self, map_dictionary, out): + ''' + takes a map_dictionary as input and writes + a readmap_dictionary {(chromosome,read_position,polarity): + number_of_reads} + in an open file handler out ''' - takes a map_dictionary as input and returns + readmap_dictionary = dict() + for key in map_dictionary: + readmap_dictionary[key] = len(map_dictionary[key]) + self.write_table(readmap_dictionary, out) + + def compute_max(self, map_dictionary, out): + ''' + takes a map_dictionary as input and writes a max_dictionary {(chromosome,read_position,polarity): max_of_number_of_read_at_any_position} + Not clear this function is still required ''' 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 + self.write_table(max_dictionary, out) - def compute_mean(self, map_dictionary): + def compute_mean(self, map_dictionary, out): ''' takes a map_dictionary as input and returns a mean_dictionary {(chromosome,read_position,polarity): @@ -85,9 +94,9 @@ else: mean_dictionary[key] = round(numpy.mean(map_dictionary[key]), 1) - return mean_dictionary + self.write_table(mean_dictionary, out) - def compute_median(self, map_dictionary): + def compute_median(self, map_dictionary, out): ''' takes a map_dictionary as input and returns a mean_dictionary {(chromosome,read_position,polarity): @@ -99,9 +108,9 @@ median_dictionary[key] = 0 else: median_dictionary[key] = numpy.median(map_dictionary[key]) - return median_dictionary + self.write_table(median_dictionary, out) - def compute_coverage(self, map_dictionary, quality=10): + def compute_coverage(self, map_dictionary, out, quality=10): ''' takes a map_dictionary as input and returns a coverage_dictionary {(chromosome,read_position,polarity): @@ -120,10 +129,9 @@ """ 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 + self.write_table(coverage_dictionary, out) - def compute_size(self, map_dictionary): + def compute_size(self, map_dictionary, out): ''' Takes a map_dictionary and returns a dictionary of sizes: {chrom: {polarity: {size: nbre of reads}}} @@ -137,65 +145,66 @@ for key in map_dictionary: for size in map_dictionary[key]: size_dictionary[key[0]][key[2]][size] += 1 - return size_dictionary + self.write_size_table(size_dictionary, out) - def write_size_table(self, out): + def write_table(self, mapdict, out): ''' - Dataset, Chromosome, Polarity, Size, Nbr_reads + Generic writer + Dataset, Chromosome, Chrom_length, Coordinate, Polarity, + <some mapped value> 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 key in sorted(mapdict): + line = [self.sample_name, key[0], self.chromosomes[key[0]], + key[1], key[2], mapdict[key]] + line = [str(i) for i in line] + out.write('\t'.join(line) + '\n') + + def write_size_table(self, sizedic, out): + ''' + Generic writer of summary values + Dataset, Chromosome, Chrom_length, <some category>, <some value> + out is an *open* file handler + ''' + for chrom in sorted(sizedic): + sizes = sizedic[chrom]['F'].keys() + sizes.extend(sizedic[chrom]['R'].keys()) + for polarity in sorted(sizedic[chrom]): for size in range(min(sizes), max(sizes)+1): try: line = [self.sample_name, chrom, polarity, size, - self.size[chrom][polarity][size]] + sizedic[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) +def main(inputs, samples, methods, outputs): + for method, output in zip(methods, outputs): + F = open(output, 'w') + if method == 'Size': + header = ["Dataset", "Chromosome", "Polarity", method, "Count"] + else: + header = ["Dataset", "Chromosome", "Chrom_length", "Coordinate", + "Polarity", method] + F.write('\t'.join(header) + '\n') + for input, sample in zip(inputs, samples): + mapobj = Map(input, sample) + token = {"Counts": mapobj.compute_map, + "Max": mapobj.compute_max, + "Mean": mapobj.compute_mean, + "Median": mapobj.compute_median, + "Coverage": mapobj.compute_coverage, + "Size": mapobj.compute_size} + token[method](mapobj.map_dict, 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) + if len(set(args.sample_names)) != len(args.sample_names): + args.sample_names = [name + '_' + str(i) for + i, name in enumerate(args.sample_names)] + main(args.inputs, args.sample_names, args.plot_methods, args.outputs)
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/small_rna_maps.py.bak Mon Aug 14 05:52:34 2017 -0400 @@ -0,0 +1,201 @@ +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 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)
--- a/small_rna_maps.r Mon Jul 24 12:31:04 2017 -0400 +++ b/small_rna_maps.r Mon Aug 14 05:52:34 2017 -0400 @@ -8,39 +8,39 @@ 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") + make_option(c("-f", "--first_dataframe"), type="character", help="path to first dataframe"), + make_option(c("-e", "--extra_dataframe"), type="character", help="path to additional dataframe"), + make_option("--extra_plot_method", type = "character", help="How additional data should be plotted"), + make_option("--output_pdf", type = "character", help="path to the pdf file with plots") ) 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 +# data frames implementation -Table = read.delim(args$output_tab, header=T, row.names=NULL) -Table <- within(Table, Nbr_reads[Polarity=="R"] <- (Nbr_reads[Polarity=="R"]*-1)) +Table = read.delim(args$first_dataframe, header=T, row.names=NULL) +Table <- within(Table, Counts[Polarity=="R"] <- (Counts[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$sizes, header=T, row.names=NULL) - size <- within(size, Nbr_reads[Polarity=="R"] <- (Nbr_reads[Polarity=="R"]*-1)) - per_gene_size=lapply(genes, function(x) subset(size, Chromosome==x)) + +ExtraTable=read.delim(args$extra_dataframe, header=T, row.names=NULL) +if (args$extra_plot_method=='Size') { + ExtraTable <- within(ExtraTable, Count[Polarity=="R"] <- (Count[Polarity=="R"]*-1)) } - +per_gene_size=lapply(genes, function(x) subset(ExtraTable, Chromosome==x)) + ## end of data frames implementation ## functions -plot_readmap=function(df, ...) { - combineLimits(xyplot(Nbr_reads~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)), +first_plot = function(df, ...) { + combineLimits(xyplot(Counts~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)), data=df, type='h', lwd=1.5, @@ -56,9 +56,9 @@ } -plot_size=function(df, ...) { +second_plot = function(df, ...) { #smR.prepanel=function(x,y,...) {; yscale=c(y*0, max(abs(y)));list(ylim=yscale);} - sizeplot = xyplot(eval(as.name(args$extra_plot))~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)), + sizeplot = xyplot(eval(as.name(args$extra_plot_method))~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)), data=df, type='p', cex=0.35, @@ -75,9 +75,9 @@ combineLimits(sizeplot) } -plot_size_distribution= function(df, ...) { +second_plot_size = function(df, ...) { # smR.prepanel=function(x,y,...){; yscale=c(-max(abs(y)), max(abs(y)));list(ylim=yscale);} - bc= barchart(Nbr_reads~as.factor(Size)|factor(Dataset, levels=unique(Dataset))+Chromosome, data = df, origin = 0, + bc= barchart(Count~as.factor(Size)|factor(Dataset, levels=unique(Dataset))+Chromosome, data = df, origin = 0, horizontal=FALSE, group=Polarity, stack=TRUE, @@ -103,7 +103,7 @@ par.settings.size=list(layout.heights=list(top.padding=0, bottom.padding=0)) graph_title=list(Coverage="Read Maps and Coverages", Median="Read Maps and Median sizes", Mean="Read Maps and Mean sizes", SizeDistribution="Read Maps and Size Distributions") graph_legend=list(Coverage="Read counts / Coverage", Median="Read counts / Median size", Mean="Read counts / Mean size", SizeDistribution="Read counts") -graph_bottom=list(Coverage="Nucleotide coordinates", Median="Nucleotide coordinates", Mean="Nucleotide coordinates", SizeDistribution="Read sizes / Nucleotide coordinates") +graph_bottom=list(Coverage="Nucleotide coordinates", Median="Nucleotide coordinates", Mean="Nucleotide coordinates", Size="Read sizes / Nucleotide coordinates") ## end of function parameters' ## GRAPHS @@ -119,20 +119,20 @@ start=i end=i+rows_per_page/2-1 if (end>n_genes) {end=n_genes} - readmap_plot.list=lapply(per_gene_readmap[start:end], function(x) plot_readmap(x, strip=FALSE, par.settings=par.settings.readmap)) - if (args$extra_plot == "SizeDistribution") { - size_plot.list=lapply(per_gene_size[start:end], function(x) plot_size_distribution(x, par.settings=par.settings.size)) + first_plot.list=lapply(per_gene_readmap[start:end], function(x) first_plot(x, strip=FALSE, par.settings=par.settings.readmap)) + if (args$extra_plot_method == "Size") { + second_plot.list=lapply(per_gene_size[start:end], function(x) second_plot_size(x, par.settings=par.settings.size)) } else { - size_plot.list=lapply(per_gene_readmap[start:end], function(x) plot_size(x, par.settings=par.settings.size)) + second_plot.list=lapply(per_gene_size[start:end], function(x) second_plot(x, par.settings=par.settings.size)) } - plot.list=rbind(size_plot.list, readmap_plot.list) + plot.list=rbind(second_plot.list, first_plot.list) args_list=c(plot.list, list(nrow=rows_per_page+1, ncol=1, - top=textGrob(graph_title[[args$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") + top=textGrob(graph_title[[args$extra_plot_method]], gp=gpar(cex=1), just="top"), + left=textGrob(graph_legend[[args$extra_plot_method]], gp=gpar(cex=1), vjust=1, rot=90), + sub=textGrob(graph_bottom[[args$extra_plot_method]], gp=gpar(cex=1), just="bottom") ) ) do.call(grid.arrange, args_list)
--- a/small_rna_maps.xml Mon Jul 24 12:31:04 2017 -0400 +++ b/small_rna_maps.xml Mon Aug 14 05:52:34 2017 -0400 @@ -1,4 +1,4 @@ -<tool id="small_rna_maps" name="small_rna_maps" version="0.9.1"> +<tool id="small_rna_maps" name="small_rna_maps" version="1.0.0"> <description></description> <requirements> <requirement type="package" version="1.11.2=py27_0">numpy</requirement> @@ -11,79 +11,77 @@ <exit_code range="1:" level="fatal" description="Tool exception" /> </stdio> <command detect_errors="exit_code"><![CDATA[ - #for $file in $input + #for $file in $inputs samtools index '$file' && #end for python '$__tool_directory__'/small_rna_maps.py - --input - #for $file in $input + --inputs + #for $file in $inputs '$file' #end for - --sample_name - #for $sample in $input + --sample_names + #for $sample in $inputs '$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 + --plot_methods Counts $extra_plot + --outputs $output_tab $extra_output_tab && + Rscript '$__tool_directory__'/small_rna_maps.r + --first_dataframe '$output_tab' + --extra_dataframe '$extra_output_tab' + --extra_plot_method '$extra_plot' + --output_pdf '$output_pdf' ]]></command> <inputs> - <param name="input" type="data" format="bam" label="Select multiple alignments to parse" multiple="True"/> + <param name="inputs" 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> + <option value="Size">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="tabular" name="output_tab" label="Read Count dataframe" /> + <data format="tabular" name="extra_output_tab" label="$extra_plot dataframe" /> <data format="pdf" name="output_pdf" label="PDF file" /> </outputs> <tests> <test> - <param name="input" value="input1.bam,input2.bam" ftype="bam"/> + <param name="inputs" value="input1.bam,input2.bam" ftype="bam"/> <param name="extra_plot" value="Mean" /> - <output file="output.tab" name="output_tab" /> + <output file="readmap.tab" name="output_tab" /> + <output file="mean.tab" name="extra_output_tab" /> <output file="mean.pdf" name="output_pdf" /> </test> <test> - <param name="input" value="input1.bam,input1.bam" ftype="bam"/> + <param name="inputs" value="input1.bam,input1.bam" ftype="bam"/> <param name="extra_plot" value="Mean" /> - <output file="doubled.tab" name="output_tab" /> + <output file="doubled_readmap.tab" name="output_tab" /> + <output file="double_mean.tab" name="extra_output_tab" /> <output file="doubled_mean.pdf" name="output_pdf" /> </test> <test> - <param name="input" value="input1.bam,input2.bam" ftype="bam"/> + <param name="inputs" value="input1.bam,input2.bam" ftype="bam"/> <param name="extra_plot" value="Median" /> - <output file="output.tab" name="output_tab" /> + <output file="readmap.tab" name="output_tab" /> + <output file="median.tab" name="extra_output_tab" /> <output file="median.pdf" name="output_pdf" /> </test> <test> - <param name="input" value="input1.bam,input2.bam" ftype="bam"/> + <param name="inputs" value="input1.bam,input2.bam" ftype="bam"/> <param name="extra_plot" value="Coverage" /> - <output file="output.tab" name="output_tab" /> + <output file="readmap.tab" name="output_tab" /> + <output file="coverage.tab" name="extra_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" /> + <param name="inputs" value="input1.bam,input2.bam" ftype="bam"/> + <param name="extra_plot" value="Size" /> + <output file="readmap.tab" name="output_tab" /> + <output file="size.tab" name="extra_output_tab" /> <output file="sizes.pdf" name="output_pdf" /> </test> </tests> @@ -99,7 +97,7 @@ **Inputs** -bam alignment files that *must* be +bam alignment files that must be - single-read - sorted
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/coverage.tab Mon Aug 14 05:52:34 2017 -0400 @@ -0,0 +1,3109 @@ +Dataset Chromosome Chrom_length Coordinate Polarity Coverage +input1.bam FBtr0070001 72 1 F 1 +input1.bam FBtr0070001 72 2 F 1 +input1.bam FBtr0070001 72 3 F 1 +input1.bam FBtr0070001 72 4 F 1 +input1.bam FBtr0070001 72 5 F 1 +input1.bam FBtr0070001 72 6 F 1 +input1.bam FBtr0070001 72 7 F 7 +input1.bam FBtr0070001 72 8 F 10 +input1.bam FBtr0070001 72 9 F 10 +input1.bam FBtr0070001 72 10 F 10 +input1.bam FBtr0070001 72 11 F 12 +input1.bam FBtr0070001 72 12 F 12 +input1.bam FBtr0070001 72 13 F 12 +input1.bam FBtr0070001 72 14 F 12 +input1.bam FBtr0070001 72 15 F 12 +input1.bam FBtr0070001 72 16 F 13 +input1.bam FBtr0070001 72 17 F 14 +input1.bam FBtr0070001 72 18 F 14 +input1.bam FBtr0070001 72 19 F 14 +input1.bam FBtr0070001 72 20 F 14 +input1.bam FBtr0070001 72 21 F 14 +input1.bam FBtr0070001 72 22 F 14 +input1.bam FBtr0070001 72 23 F 13 +input1.bam FBtr0070001 72 24 F 13 +input1.bam FBtr0070001 72 25 F 13 +input1.bam FBtr0070001 72 26 F 13 +input1.bam FBtr0070001 72 27 F 14 +input1.bam FBtr0070001 72 28 F 11 +input1.bam FBtr0070001 72 29 F 8 +input1.bam FBtr0070001 72 30 F 9 +input1.bam FBtr0070001 72 31 F 18 +input1.bam FBtr0070001 72 32 F 44 +input1.bam FBtr0070001 72 33 F 44 +input1.bam FBtr0070001 72 34 F 44 +input1.bam FBtr0070001 72 35 F 43 +input1.bam FBtr0070001 72 36 F 43 +input1.bam FBtr0070001 72 37 F 43 +input1.bam FBtr0070001 72 38 F 43 +input1.bam FBtr0070001 72 39 F 43 +input1.bam FBtr0070001 72 40 F 42 +input1.bam FBtr0070001 72 41 F 42 +input1.bam FBtr0070001 72 42 F 42 +input1.bam FBtr0070001 72 43 F 42 +input1.bam FBtr0070001 72 44 F 42 +input1.bam FBtr0070001 72 45 F 42 +input1.bam FBtr0070001 72 46 F 42 +input1.bam FBtr0070001 72 47 F 42 +input1.bam FBtr0070001 72 48 F 42 +input1.bam FBtr0070001 72 49 F 42 +input1.bam FBtr0070001 72 50 F 41 +input1.bam FBtr0070001 72 51 F 40 +input1.bam FBtr0070001 72 52 F 40 +input1.bam FBtr0070001 72 53 F 39 +input1.bam FBtr0070001 72 72 F 0 +input1.bam FBtr0070533 72 1 F 1 +input1.bam FBtr0070533 72 2 F 1 +input1.bam FBtr0070533 72 3 F 1 +input1.bam FBtr0070533 72 4 F 1 +input1.bam FBtr0070533 72 5 F 1 +input1.bam FBtr0070533 72 6 F 1 +input1.bam FBtr0070533 72 7 F 1 +input1.bam FBtr0070533 72 8 F 1 +input1.bam FBtr0070533 72 9 F 1 +input1.bam FBtr0070533 72 10 F 1 +input1.bam FBtr0070533 72 11 F 1 +input1.bam FBtr0070533 72 12 F 3 +input1.bam FBtr0070533 72 13 F 3 +input1.bam FBtr0070533 72 14 F 3 +input1.bam FBtr0070533 72 15 F 4 +input1.bam FBtr0070533 72 16 F 3 +input1.bam FBtr0070533 72 17 F 3 +input1.bam FBtr0070533 72 18 F 3 +input1.bam FBtr0070533 72 19 F 8 +input1.bam FBtr0070533 72 20 F 9 +input1.bam FBtr0070533 72 21 F 10 +input1.bam FBtr0070533 72 22 F 11 +input1.bam FBtr0070533 72 23 F 11 +input1.bam FBtr0070533 72 24 F 11 +input1.bam FBtr0070533 72 25 F 12 +input1.bam FBtr0070533 72 26 F 13 +input1.bam FBtr0070533 72 27 F 13 +input1.bam FBtr0070533 72 28 F 14 +input1.bam FBtr0070533 72 29 F 14 +input1.bam FBtr0070533 72 30 F 11 +input1.bam FBtr0070533 72 31 F 11 +input1.bam FBtr0070533 72 32 F 15 +input1.bam FBtr0070533 72 33 F 15 +input1.bam FBtr0070533 72 34 F 15 +input1.bam FBtr0070533 72 35 F 16 +input1.bam FBtr0070533 72 36 F 16 +input1.bam FBtr0070533 72 37 F 18 +input1.bam FBtr0070533 72 38 F 20 +input1.bam FBtr0070533 72 39 F 19 +input1.bam FBtr0070533 72 40 F 17 +input1.bam FBtr0070533 72 41 F 15 +input1.bam FBtr0070533 72 42 F 11 +input1.bam FBtr0070533 72 43 F 10 +input1.bam FBtr0070533 72 44 F 10 +input1.bam FBtr0070533 72 45 F 10 +input1.bam FBtr0070533 72 46 F 10 +input1.bam FBtr0070533 72 47 F 10 +input1.bam FBtr0070533 72 48 F 10 +input1.bam FBtr0070533 72 49 F 10 +input1.bam FBtr0070533 72 50 F 9 +input1.bam FBtr0070533 72 51 F 9 +input1.bam FBtr0070533 72 52 F 8 +input1.bam FBtr0070533 72 53 F 7 +input1.bam FBtr0070533 72 54 F 4 +input1.bam FBtr0070533 72 55 F 4 +input1.bam FBtr0070533 72 72 F 0 +input1.bam 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