Mercurial > repos > artbio > small_rna_signatures
changeset 0:a35e6f9c1d34 draft
planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_signatures commit 6719543c5017d581ae012b864d7c9088f0767fc8
| author | artbio |
|---|---|
| date | Mon, 28 Aug 2017 09:29:47 -0400 |
| parents | |
| children | 6f1378738798 |
| files | signature.py signature.r signature.xml test-data/global.pdf test-data/h.tab test-data/lattice.pdf test-data/sr_bowtie.bam test-data/z.tab tool-data/bowtie_indices.loc.sample tool_data_table_conf.xml.sample tool_dependencies.xml |
| diffstat | 11 files changed, 3152 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/signature.py Mon Aug 28 09:29:47 2017 -0400 @@ -0,0 +1,209 @@ +import argparse +from collections import defaultdict + +import numpy + +import pysam + + +def Parser(): + the_parser = argparse.ArgumentParser() + the_parser.add_argument( + '--input', action="store", type=str, help="bam alignment file") + the_parser.add_argument( + '--minquery', type=int, + help="Minimum readsize of query reads (nt) - must be an integer") + the_parser.add_argument( + '--maxquery', type=int, + help="Maximum readsize of query reads (nt) - must be an integer") + the_parser.add_argument( + '--mintarget', type=int, + help="Minimum readsize of target reads (nt) - must be an integer") + the_parser.add_argument( + '--maxtarget', type=int, + help="Maximum readsize of target reads (nt) - must be an integer") + the_parser.add_argument( + '--minscope', type=int, + help="Minimum overlap analyzed (nt) - must be an integer") + the_parser.add_argument( + '--maxscope', type=int, + help="Maximum overlap analyzed (nt) - must be an integer") + the_parser.add_argument( + '--output_h', action="store", type=str, + help="h-signature dataframe") + the_parser.add_argument( + '--output_z', action="store", type=str, + help="z-signature dataframe") + args = the_parser.parse_args() + return args + + +class Map: + + def __init__(self, bam_file): + 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) + + 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 + 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 signature_tables(self, minquery, maxquery, mintarget, maxtarget): + query_range = range(minquery, maxquery + 1) + target_range = range(mintarget, maxtarget + 1) + Query_table = defaultdict(dict) + Target_table = defaultdict(dict) + for key in self.map_dict: + for size in self.map_dict[key]: + if size in query_range or size in target_range: + if key[2] == 'F': + coordinate = key[1] + else: + coordinate = -key[1] + if size in query_range: + Query_table[key[0]][coordinate] = Query_table[key[0]].get( + coordinate, 0) + 1 + if size in target_range: + Target_table[key[0]][coordinate] = \ + Target_table[key[0]].get(coordinate, 0) + 1 + return Query_table, Target_table + + def compute_signature_z(self, minquery, maxquery, mintarget, maxtarget, + scope, zscore="no"): + Query_table, Target_table = self.signature_tables(minquery, maxquery, + mintarget, maxtarget) + frequency_table = defaultdict(dict) + for chrom in self.chromosomes: + for overlap in scope: + frequency_table[chrom][overlap] = 0 + for chrom in Query_table: + for coord in Query_table[chrom]: + for overlap in scope: + frequency_table[chrom][overlap] += min( + Query_table[chrom][coord], + Target_table[chrom].get(-coord - overlap + 1, 0)) + # since we want the number of pairs, not the number or paired reads + # to do: what in complex cases + # with query and target sizes partially overlap ? + for chrom in frequency_table: + for overlap in frequency_table[chrom]: + frequency_table[chrom][overlap] /= 2 + # compute overlaps for all chromosomes merged + for overlap in scope: + accumulator = [] + for chrom in frequency_table: + if chrom != 'all_chromosomes': + accumulator.append(frequency_table[chrom][overlap]) + frequency_table['all_chromosomes'][overlap] = sum(accumulator) + return self.stringify_table(frequency_table) + + def compute_signature_h(self, minquery, maxquery, mintarget, + maxtarget, scope): + Query_table, Target_table = self.signature_tables(minquery, maxquery, + mintarget, maxtarget) + frequency_table = defaultdict(dict) + for chrom in self.chromosomes: + for overlap in scope: + frequency_table[chrom][overlap] = 0 + for chrom in Query_table: + Total_Query_Numb = 0 + for coord in Query_table[chrom]: + Total_Query_Numb += Query_table[chrom][coord] + for coord in Query_table[chrom]: + local_table = dict([(overlap, 0) for overlap in scope]) + number_of_targets = 0 + for overlap in scope: + local_table[overlap] += Query_table[chrom][coord] * \ + Target_table[chrom].get(-coord - overlap + 1, 0) + number_of_targets += Target_table[chrom].get( + -coord - overlap + 1, 0) + for overlap in scope: + try: + frequency_table[chrom][overlap] += \ + local_table[overlap] / number_of_targets \ + / float(Total_Query_Numb) + except ZeroDivisionError: + continue + # compute overlap probabilities for all chromosomes merged + general_frequency_table = dict([(overlap, 0) for overlap in scope]) + total_aligned_reads = 0 + for chrom in frequency_table: + for overlap in frequency_table[chrom]: + total_aligned_reads += self.bam_object.count(chrom) + for chrom in frequency_table: + for overlap in frequency_table[chrom]: + try: + general_frequency_table[overlap] += \ + frequency_table[chrom][overlap] / total_aligned_reads \ + * self.bam_object.count(chrom) + except ZeroDivisionError: + continue + for overlap in general_frequency_table: + frequency_table['all_chromosomes'][overlap] = \ + general_frequency_table[overlap] + return self.stringify_table(frequency_table) + + def stringify_table(self, frequency_table): + ''' + method both to compute z-score and to return a writable string + ''' + tablestring = [] + for chrom in sorted(frequency_table): + accumulator = [] + for overlap in frequency_table[chrom]: + accumulator.append(frequency_table[chrom][overlap]) + z_mean = numpy.mean(accumulator) + z_std = numpy.std(accumulator) + if z_std == 0: + for overlap in sorted(frequency_table[chrom]): + tablestring.append('%s\t%s\t%s\t%s\n' % ( + chrom, str(overlap), + str(frequency_table[chrom][overlap]), str(0))) + else: + for overlap in sorted(frequency_table[chrom]): + tablestring.append('%s\t%s\t%s\t%s\n' % ( + chrom, str(overlap), + str(frequency_table[chrom][overlap]), + str((frequency_table[chrom][overlap] - z_mean)/z_std))) + return ''.join(tablestring) + + + +def main(input, minquery, maxquery, mintarget, maxtarget, minscope, maxscope, + output_h, output_z, genome_wide=False, zscore="no"): + H = open(output_h, 'w') + Z = open(output_z, 'w') + mapobj = Map(input) + scope = range(minscope, maxscope + 1) + Z.write(mapobj.compute_signature_z(minquery, maxquery, mintarget, + maxtarget, scope, zscore="no")) + H.write(mapobj.compute_signature_h(minquery, maxquery, mintarget, + maxtarget, scope)) + H.close() + Z.close() + + +if __name__ == "__main__": + args = Parser() + main(args.input, args.minquery, args.maxquery, args.mintarget, + args.maxtarget, args.minscope, args.maxscope, args.output_h, + args.output_z)
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/signature.r Mon Aug 28 09:29:47 2017 -0400 @@ -0,0 +1,99 @@ +## 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("--h_dataframe", type="character", help="path to h-signature dataframe"), + make_option("--z_dataframe", type="character", help="path to z-signature dataframe"), + make_option("--plot_method", type = "character", help="How data should be plotted (global or lattice)"), + make_option("--pdf", type = "character", help="path to the pdf file with plots"), + make_option("--title", type = "character", help="Graph Title") + ) + +parser <- OptionParser(usage = "%prog [options] file", option_list = option_list) +args = parse_args(parser) + + + + +# data frames implementation +h_dataframe = read.delim(args$h_dataframe, header=F) +colnames(h_dataframe) = c("chrom", "overlap", "sig", "z-score") +h_dataframe$sig = h_dataframe$sig * 100 # to get probs in % +z_dataframe = read.delim(args$z_dataframe, header=F) +colnames(z_dataframe) = c("chrom", "overlap", "sig", "z-score") + +# functions + globalgraph = function () { + pdf(args$pdf) + par(mfrow=c(2,2),oma = c(0, 0, 3, 0)) + + plot(z_dataframe[z_dataframe$chrom == "all_chromosomes", c(2,3)], + type = "h", main="Numbers of pairs", cex.main=1, xlab="overlap (nt)", + ylab="Numbers of pairs", col="darkslateblue", lwd=4) + + plot(z_dataframe[z_dataframe$chrom == "all_chromosomes", c(2,4)], + type = "l", main="Number of pairs Z-scores", cex.main=1, xlab="overlap (nt)", + ylab="z-score", pch=19, cex=0.2, col="darkslateblue", lwd=2) + + plot(h_dataframe[h_dataframe$chrom == "all_chromosomes", c(2,3)], + type = "l", main="Overlap probabilities", cex.main=1, xlab="overlap (nt)", + ylab="Probability [%]", ylim=c(0,50), pch=19, col="darkslateblue", lwd=2) + + plot(h_dataframe[h_dataframe$chrom == "all_chromosomes", c(2,4)], + type = "l", main="Overlap Probability Z-scores", cex.main=1, + xlab="overlap (nt)", ylab="z-score", pch=19, cex=0.2, + col="darkslateblue", lwd=2) + + mtext(args$title, outer = TRUE, cex=1) + dev.off() + } + + treillisgraph = function (df, ...) { + pdf(args$pdf, paper="special", height=11.69, width=6 ) # 8.2677 + p = xyplot(sig ~ overlap|factor(method, levels=unique(method))+chrom, data = df, + type = "l", + col='darkblue', + cex=0.5, + scales=list(y=list(tick.number=4, relation="free", cex=0.6, rot=0), x=list(cex=0.6, alternating=FALSE)), + xlab = "Overlap", + ylab = "signature (Nbr of pairs / Overlap prob.)", + main = args$title, + par.strip.text=list(cex=.5), + pch=19, lwd =2, + as.table=TRUE, + layout=c(2,12), + newpage = T, + ...) + plot(p) + dev.off() + } + +# main + +if (args$plot_method=="global") { + globalgraph() + } + +if(args$plot_method=="lattice") { + # rearrange dataframes + h_sig = h_dataframe[,c(1,2,3)] + h_sig = cbind(rep("Overlap Prob (%)", length(h_sig[,1])), h_sig) + colnames(h_sig) = c("method", "chrom", "overlap", "sig") + z_pairs = z_dataframe[,c(1,2,3)] + z_pairs = cbind(rep("Nbr of pairs", length(z_pairs[,1])), z_pairs) + colnames(z_pairs) = c("method", "chrom", "overlap", "sig") + lattice_df = rbind(z_pairs, h_sig) + par.settings.treillis=list(strip.background = list( + col = c("lightblue", "lightgreen"))) + + treillisgraph(lattice_df, par.settings=par.settings.treillis) +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/signature.xml Mon Aug 28 09:29:47 2017 -0400 @@ -0,0 +1,119 @@ +<tool id="signature" name="Small RNA Signatures" version="3.0.0"> + <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[ + samtools index '$input' && + python '$__tool_directory__'/signature.py + --input '$input' + --minquery '$minquery' + --maxquery '$maxquery' + --mintarget '$mintarget' + --maxtarget '$maxtarget' + --minscope '$minscope' + --maxscope '$maxscope' + --output_h '$h_dataframe' + --output_z '$z_dataframe' && + Rscript '$__tool_directory__'/signature.r + --h_dataframe '$h_dataframe' + --z_dataframe '$z_dataframe' + --plot_method '$plot_method' + --pdf '$pdf' + --title "Overlap Signatures of ${minquery}-${maxquery} against ${mintarget}-${maxtarget}nt small RNAs" + ]]></command> + <inputs> + <param format="bam" label="Compute signature from this bowtie standard output" name="input" type="data" /> + <param help="'23' = 23 nucleotides" label="Min size of query small RNAs" name="minquery" size="3" type="integer" value="23" /> + <param help="'29' = 29 nucleotides" label="Max size of query small RNAs" name="maxquery" size="3" type="integer" value="29" /> + <param help="'23' = 23 nucleotides" label="Min size of target small RNAs" name="mintarget" size="3" type="integer" value="23" /> + <param help="'29' = 29 nucleotides" label="Max size of target small RNAs" name="maxtarget" size="3" type="integer" value="29" /> + <param help="'1' = 1 nucleotide overlap" label="Minimal relative overlap analyzed" name="minscope" size="3" type="integer" value="1" /> + <param help="'1' = 1 nucleotide overlap" label="Maximal relative overlap analyzed" name="maxscope" size="3" type="integer" value="26" /> + <param help="Signature can be computed globally or by item present in the alignment file" label="Graph type" name="plot_method" type="select"> + <option selected="True" value="global">Global</option> + <option value="lattice">Lattice</option> + </param> + </inputs> + <outputs> + <data format="tabular" label="z-signature data frame" name="z_dataframe"> + <actions> + <action name="column_names" type="metadata" default="Chromosome,Overlap,Number_of_pairs,z-score" /> + </actions> + </data> + <data format="tabular" label="h-signature data frame" name="h_dataframe"> + <actions> + <action name="column_names" type="metadata" default="Chromosome,Overlap,overlap_probability,z-score" /> + </actions> + </data> + <data format="pdf" label="Overlap probabilities" name="pdf" /> + </outputs> + <tests> + <test> + <param ftype="bam" name="input" value="sr_bowtie.bam" /> + <param name="minquery" value="23" /> + <param name="maxquery" value="29" /> + <param name="mintarget" value="23" /> + <param name="maxtarget" value="29" /> + <param name="minscope" value="5" /> + <param name="maxscope" value="15" /> + <param name="plot_method" value="global" /> + <output file="h.tab" ftype="tabular" name="h_dataframe" /> + <output file="z.tab" ftype="tabular" name="z_dataframe" /> + <output file="global.pdf" ftype="pdf" name="pdf" /> + </test> + <test> + <param ftype="bam" name="input" value="sr_bowtie.bam" /> + <param name="minquery" value="23" /> + <param name="maxquery" value="29" /> + <param name="mintarget" value="23" /> + <param name="maxtarget" value="29" /> + <param name="minscope" value="5" /> + <param name="maxscope" value="15" /> + <param name="plot_method" value="lattice" /> + <output file="h.tab" ftype="tabular" name="h_dataframe" /> + <output file="z.tab" ftype="tabular" name="z_dataframe" /> + <output file="lattice.pdf" ftype="pdf" name="pdf" /> + </test> + </tests> + <help> + +**What it does** + +Compute small RNA (piRNA, siRNA, ...) signatures. + +This tool computes (i) the number of pairs by overlap classes (in nt) and associated the z-scores, +and (ii) the ping-pong signal (`Brennecke et al, 2009`_) and associated z-scores. +Options set the min and max size of both the query small rna class and the target small rna class, +the range over which to compute the signatures, and whether the signatures should be reported at +genome-wide level or by item (chromosomes, genes, etc.). For details on computational algorithmes +for piRNA and siRNA signatures, see `Antoniewski (2014)`_. + +.. _Brennecke et al, 2009: http://dx.doi.org/10.1126/science.1165171 +.. _Antoniewski (2014): https://link.springer.com/protocol/10.1007%2F978-1-4939-0931-5_12 + +**Input** + +A **sorted** BAM alignment file. + +**Outputs** + +**Global**: The number of pairs founds, the ping-pong signal and the associated z-scores +are computed at genome-wide level and returned in a pdf file. + +**Lattice**: The number of pairs founds, the ping-pong signals and the associated z-scores +are computed for each items described in the BAM alignment input and returned in a pdf file as a lattice graph. + + + </help> + <citations> + <citation type="doi">10.1007/978-1-4939-0931-5_12</citation> + </citations> +</tool>
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/tool-data/bowtie_indices.loc.sample Mon Aug 28 09:29:47 2017 -0400 @@ -0,0 +1,37 @@ +#This is a sample file distributed with Galaxy that enables tools +#to use a directory of Bowtie indexed sequences data files. You will +#need to create these data files and then create a bowtie_indices.loc +#file similar to this one (store it in this directory) that points to +#the directories in which those files are stored. The bowtie_indices.loc +#file has this format (longer white space characters are TAB characters): +# +#<unique_build_id> <dbkey> <display_name> <file_base_path> +# +#So, for example, if you had hg18 indexed stored in +#/depot/data2/galaxy/bowtie/hg18/, +#then the bowtie_indices.loc entry would look like this: +# +#hg18 hg18 hg18 /depot/data2/galaxy/bowtie/hg18/hg18 +# +#and your /depot/data2/galaxy/bowtie/hg18/ directory +#would contain hg18.*.ebwt files: +# +#-rw-r--r-- 1 james universe 830134 2005-09-13 10:12 hg18.1.ebwt +#-rw-r--r-- 1 james universe 527388 2005-09-13 10:12 hg18.2.ebwt +#-rw-r--r-- 1 james universe 269808 2005-09-13 10:12 hg18.3.ebwt +#...etc... +# +#Your bowtie_indices.loc file should include an entry per line for each +#index set you have stored. The "file" in the path does not actually +#exist, but it is the prefix for the actual index files. For example: +# +#hg18canon hg18 hg18 Canonical /depot/data2/galaxy/bowtie/hg18/hg18canon +#hg18full hg18 hg18 Full /depot/data2/galaxy/bowtie/hg18/hg18full +#/orig/path/hg19 hg19 hg19 /depot/data2/galaxy/bowtie/hg19/hg19 +#...etc... +# +#Note that for backwards compatibility with workflows, the unique ID of +#an entry must be the path that was in the original loc file, because that +#is the value stored in the workflow for that parameter. That is why the +#hg19 entry above looks odd. New genomes can be better-looking. +#
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/tool_data_table_conf.xml.sample Mon Aug 28 09:29:47 2017 -0400 @@ -0,0 +1,8 @@ +<!-- Use the file tool_data_table_conf.xml.oldlocstyle if you don't want to update your loc files as changed in revision 4550:535d276c92bc--> +<tables> + <!-- Locations of indexes in the Bowtie mapper format --> + <table name="bowtie_indexes" comment_char="#"> + <columns>value, dbkey, name, path</columns> + <file path="tool-data/bowtie_indices.loc" /> + </table> +</tables>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/tool_dependencies.xml Mon Aug 28 09:29:47 2017 -0400 @@ -0,0 +1,18 @@ +<?xml version="1.0"?> +<tool_dependency> + <package name="bowtie" version="1.1.2"> + <repository changeset_revision="a1c1a92e13a6" name="package_bowtie_1_1_2" owner="iuc" toolshed="https://toolshed.g2.bx.psu.edu" /> + </package> + <package name="pysam" version="0.8.3"> + <repository changeset_revision="08db58be052a" name="package_python_2_7_pysam_0_8_3" owner="iuc" toolshed="https://toolshed.g2.bx.psu.edu" /> + </package> + <package name="numpy" version="1.9"> + <repository changeset_revision="f24fc0b630fc" name="package_python_2_7_numpy_1_9" owner="iuc" toolshed="https://toolshed.g2.bx.psu.edu" /> + </package> + <package name="R" version="3.1.2"> + <repository changeset_revision="4d2fd1413b56" name="package_r_3_1_2" owner="iuc" toolshed="https://toolshed.g2.bx.psu.edu" /> + </package> + <package name="biocbasics" version="2.14"> + <repository changeset_revision="f0ef1a7b157e" name="package_biocbasics_2_14" owner="mvdbeek" toolshed="https://toolshed.g2.bx.psu.edu" /> + </package> +</tool_dependency>