Mercurial > repos > fubar > bigwig_outlier_bed
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planemo upload for repository https://github.com/jackh726/bigtools commit ce6b9f638ebcebcad5a5b10219f252962f30e5cc-dirty
author | fubar |
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date | Mon, 01 Jul 2024 03:24:17 +0000 |
parents | d4c50cb2042d |
children | 68cb8e7e266b |
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<tool name="bigwig_outlier_bed" id="bigwig_outlier_bed" version="0.03" profile="22.05"> <!--Source in git at: https://github.com/fubar2/galaxy_tf_overlay--> <!--Created by toolfactory@galaxy.org at 30/06/2024 19:44:14 using the Galaxy Tool Factory.--> <description>Writes high and low bigwig regions as features in a bed file</description> <edam_topics> <edam_topic>topic_0157</edam_topic> <edam_topic>topic_0092</edam_topic> </edam_topics> <edam_operations> <edam_operation>operation_0337</edam_operation> </edam_operations> <requirements> <requirement type="package" version="3.12.3">python</requirement> <requirement type="package" version="2.0.0">numpy</requirement> <requirement type="package" version="0.1.4">pybigtools</requirement> </requirements> <version_command><![CDATA[python -c "import pybigtools; from importlib.metadata import version; print(version('pybigtools'))"]]></version_command> <command><![CDATA[python '$runme' --bigwig '$bigwig' --bedouthilo '$bedouthilo' --minwin '$minwin' --qhi '$qhi' --qlo '$qlo' #if $tableout == "set" --tableout #end if --bigwiglabels '$bigwiglabels']]></command> <configfiles> <configfile name="runme"><![CDATA[#raw """ Bigwigs are great, but hard to reliably "see" small low coverage or small very high coverage regions. Colouring in JB2 tracks will need a new plugin, so this code will find bigwig regions above and below a chosen percentile point. 0.99 and 0.01 work well in testing with a minimum span of 10 bp. Multiple bigwigs **with the same reference** can be combined - bed segments will be named appropriately Combining multiple references works but is silly because display will rely on one reference so features mapped to other references will not appear. Tricksy numpy method from http://gregoryzynda.com/python/numpy/contiguous/interval/2019/11/29/contiguous-regions.html takes about 95 seconds for a 17MB test wiggle JBrowse2 bed normally displays ignore the score, so could provide separate low/high bed file outputs as an option. Update june 30 2024: wrote a 'no-build' plugin for beds to display red/blue if >0/<0 so those are used for scores Bed interval naming must be short for JB2 but needs input bigwig name and (lo or hi). """ import argparse import numpy as np import pybigtools import sys from pathlib import Path class findOut(): def __init__(self, args): self.bwnames=args.bigwig self.bwlabels=args.bigwiglabels self.bedwin=args.minwin self.qlo=args.qlo self.qhi=args.qhi self.bedouthilo=args.bedouthilo self.bedouthi=args.bedouthi self.bedoutlo=args.bedoutlo self.tableout = args.tableout self.bedwin = args.minwin self.qhi = args.qhi self.qlo = args.qlo self.makeBed() def processVals(self, bw, isTop): # http://gregoryzynda.com/python/numpy/contiguous/interval/2019/11/29/contiguous-regions.html if isTop: bwex = np.r_[False, bw >= self.bwtop, False] # extend with 0s else: bwex = np.r_[False, bw <= self.bwbot, False] bwexd = np.diff(bwex) bwexdnz = bwexd.nonzero()[0] bwregions = np.reshape(bwexdnz, (-1,2)) return bwregions def writeBed(self, bed, bedfname): """ potentially multiple """ bed.sort() beds = ['%s\t%d\t%d\t%s\t%d' % x for x in bed] with open(bedfname, "w") as bedf: bedf.write('\n'.join(beds)) bedf.write('\n') print('Wrote %d bed regions to %s' % (len(bed), bedfname)) def makeBed(self): bedhi = [] bedlo = [] bwlabels = self.bwlabels bwnames = self.bwnames print('bwnames=', bwnames, "bwlabs=", bwlabels) for i, bwname in enumerate(bwnames): bwlabel = bwlabels[i].replace(" ",'') p = Path('in.bw') p.symlink_to( bwname ) # required by pybigtools (!) bwf = pybigtools.open('in.bw') chrlist = bwf.chroms() chrs = list(chrlist.keys()) chrs.sort() restab = ["contig\tn\tmean\tstd\tmin\tmax\tqtop\tqbot"] for chr in chrs: bw = bwf.values(chr) bw = bw[~np.isnan(bw)] # some have NaN if parts of a contig not covered if self.qhi is not None: self.bwtop = np.quantile(bw, self.qhi) bwhi = self.processVals(bw, isTop=True) for i, seg in enumerate(bwhi): if seg[1] - seg[0] >= self.bedwin: bedhi.append((chr, seg[0], seg[1], '%s_hi' % (bwlabel), 1)) if self.qlo is not None: self.bwbot = np.quantile(bw, self.qlo) bwlo = self.processVals(bw, isTop=False) for i, seg in enumerate(bwlo): if seg[1] - seg[0] >= self.bedwin: bedlo.append((chr, seg[0], seg[1], '%s_lo' % (bwlabel), -1)) bwmean = np.mean(bw) bwstd = np.std(bw) bwmax = np.max(bw) nrow = np.size(bw) bwmin = np.min(bw) restab.append('%s\t%d\t%f\t%f\t%f\t%f\t%f\t%f' % (chr,nrow,bwmean,bwstd,bwmin,bwmax,self.bwtop,self.bwbot)) print('\n'.join(restab), '\n') if self.tableout: with open(self.tableout) as t: t.write('\n'.join(restab)) t.write('\n') if self.bedoutlo: if self.qlo: self.writeBed(bedlo, self.bedoutlo) if self.bedouthi: if self.qhi: self.writeBed(bedhi, self.bedouthi) if self.bedouthilo: allbed = bedlo + bedhi self.writeBed(allbed, self.bedouthilo) return restab if __name__ == "__main__": parser = argparse.ArgumentParser() a = parser.add_argument a('-m', '--minwin',default=10, type=int) a('-l', '--qlo',default=None, type=float) a('-i', '--qhi',default=None, type=float) a('-w', '--bigwig', nargs='+') a('-n', '--bigwiglabels', nargs='+') a('-o', '--bedouthilo', default=None, help="optional high and low combined bed") a('-u', '--bedouthi', default=None, help="optional high only bed") a('-b', '--bedoutlo', default=None, help="optional low only bed") a('-t', '--tableout', default=None) args = parser.parse_args() print('args=', args) if not (args.bedouthilo or args.bedouthi or args.bedoutlo): sys.stderr.write("bigwig_outlier_bed.py cannot usefully run - need a bed output choice - must be one of low only, high only or both combined") sys.exit(2) if not (args.qlo or args.qhi): sys.stderr.write("bigwig_outlier_bed.py cannot usefully run - need one or both of quantile cutpoints qhi and qlo") sys.exit(2) restab = findOut(args) if args.tableout: with open(args.tableout, 'w') as tout: tout.write('\n'.join(restab)) tout.write('\n') #end raw]]></configfile> </configfiles> <inputs> <param name="bigwig" type="data" optional="false" label="Bigwig file(s) to process. " help="If more than one, MUST all use the same reference sequence to be displayable. Feature names will include the bigwig label." format="bigwig" multiple="true"/> <param name="minwin" type="integer" value="10" label="Minimum continuous bases to count as a high or low bed feature" help="Actual run length will be found and used for continuous features as long or longer."/> <param name="qhi" type="float" value="0.99" label="Quantile cutoff for a high region - 0.99 will cut off at or above the 99th percentile" help=""/> <param name="qlo" type="float" value="0.01" label="Quantile cutoff for a low region - 0.01 will cut off at or below the 1st percentile." help=""/> <param name="tableout" type="select" label="Write a table showing contig statistics for each bigwig" help="" display="radio"> <option value="notset">Do not set this flag</option> <option value="set">Set this flag</option> </param> <param name="bigwiglabels" type="text" value="outbed" label="Label to use in bed feature names to indicate source bigwig contents - such as coverage" help=""/> </inputs> <outputs> <data name="bedouthilo" format="bed" label="Both high and low contiguous regions as long or longer than window length into one bed " hidden="false"/> </outputs> <tests> <test> <output name="bedouthilo" value="bedouthilo_sample" compare="diff" lines_diff="0"/> <param name="bigwig" value="bigwig_sample"/> <param name="minwin" value="10"/> <param name="qhi" value="0.99"/> <param name="qlo" value="0.01"/> <param name="tableout" value="notset"/> <param name="bigwiglabels" value="outbed"/> </test> </tests> <help><![CDATA[ **What it Does** Takes one or more bigwigs mapped to the same reference and finds all the minimum window sized or greater contiguous regions above or below an upper and lower quantile cutoff. A window size of 10 works well, and quantiles set at 0.01 and 0.99 will generally work well. ]]></help> <citations> <citation type="doi">10.1093/bioinformatics/btae350</citation> </citations> </tool>