Mercurial > repos > fubar > bigwig_outlier_bed
changeset 6:eb17eb8a3658 draft
planemo upload commit 1baff96e75def9248afdcf21edec9bdc7ed42b1f-dirty
| author | fubar |
|---|---|
| date | Tue, 23 Jul 2024 23:12:23 +0000 |
| parents | 68cb8e7e266b |
| children | c8e22efcaeda |
| files | README.md bigwig_outlier_bed.py bigwig_outlier_bed.xml bigwigtobed.python.txt test-data/1.bigwig test-data/bedouthi2_sample test-data/bedouthi_qlo_notset_sample test-data/bedouthi_sample test-data/bedouthilo2_sample test-data/bedouthilo_qlo_notset_sample test-data/bedouthilo_sample test-data/bedoutlo2_sample test-data/bedoutlo_sample test-data/table2_sample test-data/table3_sample test-data/table_only_sample test-data/table_qlo_notset_sample test-data/table_sample |
| diffstat | 18 files changed, 5485 insertions(+), 538 deletions(-) [+] |
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--- a/README.md Mon Jul 01 05:02:05 2024 +0000 +++ b/README.md Tue Jul 23 23:12:23 2024 +0000 @@ -1,10 +1,10 @@ -## bigwig peak outlier to bed +## bigwig peak bed maker ### July 30 2024 for the VGP -This code will soon become a Galaxy tool, for building some of the [NIH MARBL T2T assembly polishing](https://github.com/marbl/training) tools as Galaxy workflows. +This is a Galaxy tool, for building some of the [NIH MARBL T2T assembly polishing](https://github.com/marbl/training) tools as Galaxy workflows. -The next JBrowse2 tool release will include a plugin for optional colours to distinguish bed features, shown being tested in the screenshots below. +JBrowse2 2.12.3 update will include a plugin for optional colours to distinguish bed features, shown being tested in the screenshots below. ### Find and mark BigWig peaks to a bed file for display @@ -29,3 +29,69 @@ better to sample across all chromosomes so as not to lose any systematic differences between them - the current method will hide those differences unfortunately. Sampling might be possible. Looking at the actual quantile values across a couple of test bigwigs suggests that there is not much variation between chromosomes but there's now a tabular report to check them for each input bigwig. + +### Table reports + +The optional table output report gives a crude histogram and the top/bottom 10 values to help +understand what is likely to be informative. In this example, there are 26700 zero values so +using a lower cutoff quantile is likely to have a lot of them, although a large window requirement +will decease the overload... + +Descriptive measures +bigwig test +contig chr10_PATERNAL +n 135711693 +mean 12.178164 +std 7.997467 +min 0.000000 +max 365.000000 +qtop 364.00 +qbot noqlo +First/Last 10 value counts +Value Count +0.00 26700 +1.00 82900 +2.00 261400 +3.00 676993 +4.00 1665500 +5.00 3125700 +6.00 5078000 +7.00 7469000 +8.00 10191700 +9.00 12544600 +355.00 100 +356.00 100 +357.00 300 +358.00 100 +360.00 500 +361.00 300 +362.00 200 +363.00 600 +364.00 900 +365.00 700 +Histogram of bigwig values +chr10_PATERNAL 18.25 | 127,047,593 | ************************************************************************** +chr10_PATERNAL 36.50 | 7,510,000 | **** +chr10_PATERNAL 54.75 | 818,900 | +chr10_PATERNAL 73.00 | 117,200 | +chr10_PATERNAL 91.25 | 51,900 | +chr10_PATERNAL 109.50 | 44,200 | +chr10_PATERNAL 127.75 | 21,600 | +chr10_PATERNAL 146.00 | 17,900 | +chr10_PATERNAL 164.25 | 16,400 | +chr10_PATERNAL 182.50 | 18,600 | +chr10_PATERNAL 200.75 | 5,400 | +chr10_PATERNAL 219.00 | 6,600 | +chr10_PATERNAL 237.25 | 6,200 | +chr10_PATERNAL 255.50 | 3,900 | +chr10_PATERNAL 273.75 | 4,500 | +chr10_PATERNAL 292.00 | 7,100 | +chr10_PATERNAL 310.25 | 3,000 | +chr10_PATERNAL 328.50 | 2,700 | +chr10_PATERNAL 346.75 | 3,500 | +chr10_PATERNAL 365.00 | 4,500 | +chr10_PATERNAL ------------ |------------ | +chr10_PATERNAL N= | 135,711,693 | +chr10_PATERNAL ------------ |------------ | + +
--- a/bigwig_outlier_bed.py Mon Jul 01 05:02:05 2024 +0000 +++ b/bigwig_outlier_bed.py Tue Jul 23 23:12:23 2024 +0000 @@ -1,58 +1,149 @@ """ -Ross Lazarus June 2024 for VGP - +Ross Lazarus June 2024 for VGP 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 only display will rely on one reference so others will not be shown... - 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 os +import sys +from pathlib import Path -import argparse import numpy as np import pybigtools -import sys -from pathlib import Path +class asciihist: + + def __init__( + self, + data, + bins=10, + minmax=None, + str_tag="", + scale_output=80, + generate_only=True, + ): + """ + https://gist.github.com/bgbg/608d9ef4fd75032731651257fe67fc81 + Create an ASCII histogram from an interable of numbers. + Author: Boris Gorelik boris@gorelik.net. based on http://econpy.googlecode.com/svn/trunk/pytrix/pytrix.py + License: MIT + """ + self.data = data + self.minmax = minmax + self.str_tag = str_tag + self.bins = bins + self.generate_only = generate_only + self.scale_output = scale_output + self.itarray = np.asanyarray(self.data) + if self.minmax == "auto": + self.minmax = np.percentile(data, [5, 95]) + if self.minmax[0] == self.minmax[1]: + # for very ugly distributions + self.minmax = None + if self.minmax is not None: + # discard values that are outside minmax range + mn = self.minmax[0] + mx = self.minmax[1] + self.itarray = self.itarray[self.itarray >= mn] + self.itarray = self.itarray[self.itarray <= mx] -class findOut(): + def draw(self): + values, counts = np.unique(self.data, return_counts=True) + if len(values) <= 20: + self.bins = len(values) + ret = [] + if self.itarray.size: + total = len(self.itarray) + counts, cutoffs = np.histogram(self.itarray, bins=self.bins) + cutoffs = cutoffs[1:] + if self.str_tag: + self.str_tag = "%s " % self.str_tag + else: + self.str_tag = "" + if self.scale_output is not None: + scaled_counts = counts.astype(float) / counts.sum() * self.scale_output + else: + scaled_counts = counts + footerbar = "{:s}{:s} |{:s} |".format(self.str_tag, "-" * 12, "-" * 12,) + if self.minmax is not None: + ret.append( + "Trimmed to range (%s - %s)" + % (str(self.minmax[0]), str(self.minmax[1])) + ) + for cutoff, original_count, scaled_count in zip( + cutoffs, counts, scaled_counts + ): + ret.append( + "{:s}{:>12.2f} |{:>12,d} | {:s}".format( + self.str_tag, cutoff, original_count, "*" * int(scaled_count) + ) + ) + ret.append(footerbar) + ret.append("{:s}{:>12s} |{:>12,d} |".format(self.str_tag, "N=", total)) + ret.append(footerbar) + ret.append('') + else: + ret = [] + if not self.generate_only: + for line in ret: + print(line) + ret = "\n".join(ret) + return ret + + +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.bwnames = args.bigwig + self.bwlabels = args.bigwiglabels + self.bedwin = args.minwin + self.outbeds = args.outbeds + self.bedouthi = args.bedouthi + self.bedoutlo = args.bedoutlo + self.bedouthilo = args.bedouthilo + self.tableoutfile = args.tableoutfile self.bedwin = args.minwin - self.qhi = args.qhi - self.qlo = args.qlo + self.qlo = None + self.qhi = None + if args.outbeds != "outtab": + self.qhi = args.qhi + if args.qlo: + try: + f = float(args.qlo) + self.qlo = f + except Exception: + print('qlo not provided') + nbw = len(args.bigwig) + nlab = len(args.bigwiglabels) + if nlab < nbw: + self.bwlabels += ["Nolabel"] * (nbw - nlab) self.makeBed() def processVals(self, bw, isTop): - # http://gregoryzynda.com/python/numpy/contiguous/interval/2019/11/29/contiguous-regions.html + """ + idea from http://gregoryzynda.com/python/numpy/contiguous/interval/2019/11/29/contiguous-regions.html + Fast segmentation into regions by taking np.diff on the boolean array of over (under) cutpoint indicators in bwex. + This only gives non-zero values at the segment boundaries where there's a change, so those zeros are all removed in bwexdnz + leaving an array of segment start/end positions. That's twisted around into an array of start/end coordinates. + Magical. Fast. Could do the same for means or medians over windows for sparse bigwigs like repeat regions. + """ if isTop: - bwex = np.r_[False, bw >= self.bwtop, False] # extend with 0s + 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)) + bwregions = np.reshape(bwexdnz, (-1, 2)) return bwregions def writeBed(self, bed, bedfname): @@ -60,89 +151,151 @@ potentially multiple """ bed.sort() - beds = ['%s\t%d\t%d\t%s\t%d' % x for x in bed] + 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)) - + bedf.write("\n".join(beds)) + bedf.write("\n") + + def makeTableRow(self, bw, bwlabel, chr): + """ + called for every contig, but messy inline + """ + bwmean = np.mean(bw) + bwstd = np.std(bw) + bwmax = np.max(bw) + nrow = np.size(bw) + bwmin = np.min(bw) + row = "%s\t%s\t%d\t%f\t%f\t%f\t%f" % ( + bwlabel, + chr, + nrow, + bwmean, + bwstd, + bwmin, + bwmax, + ) + if self.qhi is not None: + row += "\t%.2f" % self.bwtop + else: + row += "\tnoqhi" + if self.qlo is not None: + row += "\t%.2f" % self.bwbot + else: + row += "\tnoqlo" + return row + def makeBed(self): bedhi = [] bedlo = [] + restab = [] bwlabels = self.bwlabels bwnames = self.bwnames - print('bwnames=', bwnames, "bwlabs=", bwlabels) + reshead = "bigwig\tcontig\tn\tmean\tstd\tmin\tmax\tqtop\tqbot" 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') + bwlabel = bwlabels[i].replace(" ", "") + fakepath = "in%d.bw" % i + if os.path.isfile(fakepath): + os.remove(fakepath) + p = Path(fakepath) + p.symlink_to(bwname) # required by pybigtools (!) + bwf = pybigtools.open(fakepath) chrlist = bwf.chroms() chrs = list(chrlist.keys()) - chrs.sort() - restab = ["contig\tn\tmean\tstd\tmin\tmax\tqtop\tqbot"] for chr in chrs: + first_few = None bw = bwf.values(chr) - bw = bw[~np.isnan(bw)] # some have NaN if parts of a contig not covered + values, counts = np.unique(bw, return_counts=True) + nvalues = len(values) + if nvalues <= 20: + histo = '\n'.join(['%s: %f occurs %d times' % (chr, values[x], counts[x]) for x in range(len(values))]) + else: + last10 = range(nvalues-10, nvalues) + first_few = ['%.2f\t%d' % (values[x],counts[x]) for x in range(10)] + first_few += ['%.2f\t%d' % (values[x],counts[x]) for x in last10] + first_few.insert(0,'First/Last 10 value counts\nValue\tCount') + ha = asciihist(data=bw, bins=20, str_tag=chr) + histo = ha.draw() + histo = '\n'.join(first_few) + '\nHistogram of bigwig values\n' + histo + 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)) + for j, seg in enumerate(bwhi): + seglen = seg[1] - seg[0] + if seglen >= self.bedwin: + score = np.sum(bw[seg[0]:seg[1]])/float(seglen) + bedhi.append( + ( + chr, + seg[0], + seg[1], + "%s_%d" % (bwlabel, score), + score, + ) + ) 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): + bwlo = self.processVals(bw, isTop=False) + for j, 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: + score = -1 * np.sum(bw[seg[0]:seg[1]])/float(seglen) + bedlo.append( + ( + chr, + seg[0], + seg[1], + "%s_%d" % (bwlabel, score), + score, + ) + ) + if self.tableoutfile: + row = self.makeTableRow(bw, bwlabel, chr) + resheadl = reshead.split('\t') + rowl = row.split() + desc = ['%s\t%s' % (resheadl[x], rowl[x]) for x in range(len(rowl))] + desc.insert(0, 'Descriptive measures') + descn = '\n'.join(desc) + restab.append(descn) + restab.append(histo) + if os.path.isfile(fakepath): + os.remove(fakepath) + if self.tableoutfile: + stable = "\n".join(restab) + with open(self.tableoutfile, "w") as t: + t.write(stable) + t.write("\n") + some = False + if self.qlo: + if self.outbeds in ["outall", "outlo", "outlohi"]: self.writeBed(bedlo, self.bedoutlo) - if self.bedouthi: - if self.qhi: + some = True + if self.qhi: + if self.outbeds in ["outall", "outlohi", "outhi"]: self.writeBed(bedhi, self.bedouthi) - if self.bedouthilo: + some = True + if self.outbeds in ["outall", "outhilo"]: allbed = bedlo + bedhi self.writeBed(allbed, self.bedouthilo) - return restab - + some = True + if not ((self.outbeds == 'outtab') or some): + sys.stderr.write( + "Invalid configuration - no output could be created. Was qlo missing and only low output requested for example?" + ) + sys.exit(2) + 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) + a("-m", "--minwin", default=10, type=int) + a("-l", "--qlo", default=None) + a("-i", "--qhi", default=None, type=float) + a("--bedouthi", default=None) + a("--bedoutlo", default=None) + a("--bedouthilo", default=None) + a("-w", "--bigwig", nargs="+") + a("-n", "--bigwiglabels", nargs="+") + a("-o", "--outbeds", default="outhilo", help="optional high and low combined bed") + a("-t", "--tableoutfile", 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') - - + findOut(args)
--- a/bigwig_outlier_bed.xml Mon Jul 01 05:02:05 2024 +0000 +++ b/bigwig_outlier_bed.xml Tue Jul 23 23:12:23 2024 +0000 @@ -1,208 +1,198 @@ -<tool name="bigwig_outlier_bed" id="bigwig_outlier_bed" version="0.04" 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> +<tool name="Bigwig extremes to bed features" id="bigwig_outlier_bed" version="@TOOL_VERSION@" profile="22.05"> + <description>Writes high and low bigwig runs as features in a bed file</description> + <macros> + <token name="@TOOL_VERSION@">0.2.0</token> + <token name="@NUMPY_VERSION@">2.0.0</token> + <token name="@PYTHON_VERSION@">3.12.3</token> + </macros> <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> + </edam_operations> + <xrefs> + <xref type="bio.tools">bigtools</xref> + </xrefs> <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> + <requirement type="package" version="@PYTHON_VERSION@">python</requirement> + <requirement type="package" version="@NUMPY_VERSION@">numpy</requirement> + <requirement type="package" version="@TOOL_VERSION@">pybigtools</requirement> </requirements> + <required_files> + <include path="bigwig_outlier_bed.py"/> + </required_files> <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 $tableout == "set" - --tableout -#end if + <command><![CDATA[python '${__tool_directory__}/bigwig_outlier_bed.py' +--bigwig +#for bw in $bigwig: + '$bw' +#end for --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> +#for bw in $bigwig: + '$bw.name' +#end for +--outbeds '$outbeds' +#if $outbeds in ['outhilo', 'outall']: + --bedouthilo '$bedouthilo' +#end if +#if $outbeds in ['outhi', 'outall', 'outlohi']: + --bedouthi '$bedouthi' +#end if +#if $outbeds in ['outlo', 'outall', 'outlohi']: + --bedoutlo '$bedoutlo' +#end if +--minwin '$minwin' +#if $qhi: +--qhi '$qhi' +#end if +#if $qlo: +--qlo '$qlo' +#end if +#if $tableout == "create" or $outbeds == "outtab": + --tableoutfile '$tableoutfile' +#end if +]]></command> <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 name="bigwig" type="data" optional="false" label="Choose one or more bigwig file(s) to return outlier regions as a bed file" + 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="Continuous features as long or longer than this window size will appear as bed features"/> + <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="Required" optional="false"/> + <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="Optional" optional="true"/> + <param name="outbeds" type="select" label="Select the required bed file outputs" help="Any combination of the 3 different kinds of bed file output can be made"> + <option value="outhilo" selected="true">Make 1 bed output with both low and high regions</option> + <option value="outhi">Make 1 bed output with high regions only</option> + <option value="outlo">Make 1 bed output with low regions only</option> + <option value="outall">Make 3 bed outputs with low and high together in one, high in one and low in the other</option> + <option value="outlohi">Make 2 bed outputs with high in one and low in the other</option> + <option value="outtab">NO bed outputs. Report bigwig value distribution only</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=""/> + <param name="tableout" type="select" label="Write a table showing contig statistics for each bigwig input" help=""> + <option value="donotmake">Do not create this report</option> + <option value="create" selected="true">Create this report</option> + </param> </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"/> + <data name="bedouthilo" format="bed" label="High_and_low_bed" hidden="false"> + <filter>outbeds in ["outall", "outhilo"]</filter> + </data> + <data name="bedouthi" format="bed" label="High bed" hidden="false"> + <filter>outbeds in ["outall", "outlohi", "outhi"]</filter> + </data> + <data name="bedoutlo" format="bed" label="Low bed" hidden="false"> + <filter>outbeds in ["outall", "outlohi", "outlo"]</filter> + </data> + <data name="tableoutfile" format="tabular" label="Contig statistics" hidden="false"> + <filter>tableout == "create"</filter> + </data> </outputs> <tests> - <test> + <test expect_num_outputs="1"> <output name="bedouthilo" value="bedouthilo_sample" compare="diff" lines_diff="0"/> + <param name="outbeds" value="outhilo"/> <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"/> + <param name="tableout" value="donotmake"/> + </test> + <test expect_num_outputs="1"> + <output name="tableoutfile" value="table_only_sample" compare="diff" lines_diff="0"/> + <param name="outbeds" value="outtab"/> + <param name="bigwig" value="bigwig_sample,1.bigwig"/> + <param name="minwin" value="10"/> + <param name="qhi" value="0.99"/> + <param name="qlo" value="0.01"/> + <param name="tableout" value="create"/> + </test> + <test expect_num_outputs="2"> + <output name="bedouthilo" value="bedouthilo_sample" compare="diff" lines_diff="0"/> + <output name="tableoutfile" value="table_sample" compare="diff" lines_diff="0"/> + <param name="outbeds" value="outhilo"/> + <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="create"/> + </test> + <test expect_num_outputs="2"> + <output name="bedouthi" value="bedouthi_qlo_notset_sample" compare="diff" lines_diff="0"/> + <output name="tableoutfile" value="table_qlo_notset_sample" compare="diff" lines_diff="0"/> + <param name="outbeds" value="outhi"/> + <param name="bigwig" value="bigwig_sample"/> + <param name="minwin" value="10"/> + <param name="qhi" value="0.99"/> + <param name="qlo" value=""/> + <param name="tableout" value="create"/> + </test> + <test expect_num_outputs="3"> + <output name="bedouthi" value="bedouthi_sample" compare="diff" lines_diff="0"/> + <output name="bedoutlo" value="bedoutlo_sample" compare="diff" lines_diff="0"/> + <output name="tableoutfile" value="table3_sample" compare="diff" lines_diff="0"/> + <param name="outbeds" value="outlohi"/> + <param name="bigwig" value="bigwig_sample"/> + <param name="minwin" value="1"/> + <param name="qhi" value="0.9"/> + <param name="qlo" value="0.1"/> + <param name="tableout" value="create"/> + </test> + <test expect_num_outputs="4"> + <output name="bedouthilo" value="bedouthilo2_sample" compare="diff" lines_diff="0"/> + <output name="bedoutlo" value="bedoutlo2_sample" compare="diff" lines_diff="0"/> + <output name="bedouthi" value="bedouthi2_sample" compare="diff" lines_diff="0"/> + <output name="tableoutfile" value="table2_sample" compare="diff" lines_diff="0"/> + <param name="outbeds" value="outall"/> + <param name="bigwig" value="bigwig_sample,1.bigwig"/> + <param name="minwin" value="1"/> + <param name="qhi" value="0.9"/> + <param name="qlo" value="0.1"/> + <param name="tableout" value="create"/> </test> </tests> <help><![CDATA[ - **What it Does** + + **Purpose** + + *Combine bigwig outlier regions into bed files* - 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. + Bigwigs allow quantative tracks to be viewed in an interactive genome browser like JBrowse2. + Peaks are easy to see. Unusually low regions can be harder to spot, even if they are relatively large, unless the view is zoomed right in. + Automated methods for combining evidence from multiple bigwigs can be useful for constructing browseable *issues* or other kinds of summary bed format tracks. + For example, combining coverage outlier regions, with the frequency of specific dicnucleotide short tandem repeats, + for evaluating technical sequencing technology effects in the evaluation of a genome assembly described at https://github.com/arangrhie/T2T-Polish + + **What does it produce?** + + Bed format results are output, containing each continuous segment of at least *minwin* base pairs above a cut point, or below another cut point. + These can be viewed as features on the reference genome using a genome browser tool like JBrowse2. + Three kinds of bed files can be created depending on the values included. + Both high and low regions in one bed output is the default. This can be displayed in JBrowse2 with colour indicating the high or low status, + one less track and a little easier to understand. High and low features can be output as separate bed files. + + **How is it controlled?** + + The cut points are calculated using a user supplied quantile, from each chromosome's bigwig value distribution. + The defaults are 0.99 and 0.01 and the default *minwin* is 10. + The probability of 10 values at or below the 1st percentile purely by chance is about 0.01**10, so false positives should be + rare, even in a 3GB genome. + This data driven and non-parametric method is preferred for the asymmetrical distributions found in typical bigwigs, such as depth of coverage + for genome sequencing reads. Coverage values are truncated at zero, and regions with very high values often form a long sparse right tail. + + **How do I choose the input data?** + + One or more bigwigs and can be selected as inputs. + Multiple bigwigs will be combined in bed files, so must share the reference genome to display + using JBrowse2. + + .. class:: warningmark + + **Lower quantile may not behave as expected in bigwigs with large fractions of zero values** + + The lower cut point may be problematic for integer values like coverage if many values are zero. For example, if 5% of bases have zero coverage, the 1st percentile is also zero, + but that cut point will include the entire 5% *at or below 0* + ]]></help> <citations>
--- a/bigwigtobed.python.txt Mon Jul 01 05:02:05 2024 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,131 +0,0 @@ -#raw -""" -Ross Lazarus June 2024 for VGP -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 only display will rely on one reference so others will not be shown... -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
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bigwig_sample_31953 31953 +Merlin 63949 63959 bigwig_sample_32338 32338 +Merlin 63969 63979 bigwig_sample_32167 32167 +Merlin 64359 64369 bigwig_sample_32186 32186 +Merlin 65999 66009 bigwig_sample_32167 32167 +Merlin 66219 66229 bigwig_sample_32661 32661 +Merlin 66519 66529 bigwig_sample_32731 32731 +Merlin 66859 66869 bigwig_sample_32552 32552 +Merlin 67249 67259 bigwig_sample_32335 32335 +Merlin 67699 67709 bigwig_sample_32697 32697 +Merlin 68649 68659 bigwig_sample_32302 32302 +Merlin 68769 68789 bigwig_sample_32429 32429 +Merlin 68989 68999 bigwig_sample_31961 31961 +Merlin 69259 69269 bigwig_sample_32057 32057 +Merlin 69579 69589 bigwig_sample_32098 32098 +Merlin 69819 69829 bigwig_sample_32047 32047 +Merlin 69859 69869 bigwig_sample_32663 32663 +Merlin 69889 69899 bigwig_sample_31994 31994 +Merlin 70049 180929 bigwig_sample_0 0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/bedoutlo2_sample Tue Jul 23 23:12:23 2024 +0000 @@ -0,0 +1,110 @@ +Merlin 0 9 bigwig_sample_0 0 +Merlin 70049 180929 bigwig_sample_0 0 +chr21 0 9411190 1.bigwig_0 0 +chr21 9411785 9411790 1.bigwig_0 0 +chr21 9411800 9411815 1.bigwig_0 0 +chr21 9411860 9411865 1.bigwig_0 0 +chr21 9411900 9411905 1.bigwig_0 0 +chr21 9412005 9412010 1.bigwig_0 0 +chr21 9412050 9412055 1.bigwig_0 0 +chr21 9412065 9412070 1.bigwig_0 0 +chr21 9412080 9412085 1.bigwig_0 0 +chr21 9412100 9412105 1.bigwig_0 0 +chr21 9412120 9412125 1.bigwig_0 0 +chr21 9412130 9412135 1.bigwig_0 0 +chr21 9412140 9412145 1.bigwig_0 0 +chr21 9412180 9412185 1.bigwig_0 0 +chr21 9412200 9412210 1.bigwig_0 0 +chr21 9412225 9412230 1.bigwig_0 0 +chr21 9412250 9412260 1.bigwig_0 0 +chr21 9412305 9412310 1.bigwig_0 0 +chr21 9412360 9412370 1.bigwig_0 0 +chr21 9412385 9412390 1.bigwig_0 0 +chr21 9412400 9412415 1.bigwig_0 0 +chr21 9412440 9412455 1.bigwig_0 0 +chr21 9412460 9412465 1.bigwig_0 0 +chr21 9412470 9412480 1.bigwig_0 0 +chr21 9412485 9412490 1.bigwig_0 0 +chr21 9412510 9412515 1.bigwig_0 0 +chr21 9412565 9412570 1.bigwig_0 0 +chr21 9412590 9412595 1.bigwig_0 0 +chr21 9412640 9412650 1.bigwig_0 0 +chr21 9412670 9412675 1.bigwig_0 0 +chr21 9412690 9412700 1.bigwig_0 0 +chr21 9412770 9412775 1.bigwig_0 0 +chr21 9412815 9412820 1.bigwig_0 0 +chr21 9412835 9412840 1.bigwig_0 0 +chr21 9412845 9412850 1.bigwig_0 0 +chr21 9412900 9412905 1.bigwig_0 0 +chr21 9412970 9412975 1.bigwig_0 0 +chr21 9412990 9412995 1.bigwig_0 0 +chr21 9413040 9413045 1.bigwig_0 0 +chr21 9413055 9413065 1.bigwig_0 0 +chr21 9413095 9413100 1.bigwig_0 0 +chr21 9413130 9413135 1.bigwig_0 0 +chr21 9413155 9413160 1.bigwig_0 0 +chr21 9413170 9413180 1.bigwig_0 0 +chr21 9413205 9413210 1.bigwig_0 0 +chr21 9413250 9413255 1.bigwig_0 0 +chr21 9413280 9413285 1.bigwig_0 0 +chr21 9413310 9413315 1.bigwig_0 0 +chr21 9413345 9413350 1.bigwig_0 0 +chr21 9413400 9413405 1.bigwig_0 0 +chr21 9413510 9413515 1.bigwig_0 0 +chr21 9413665 9413670 1.bigwig_0 0 +chr21 9414040 9414045 1.bigwig_0 0 +chr21 9414055 9414060 1.bigwig_0 0 +chr21 9414100 9414105 1.bigwig_0 0 +chr21 9414150 9414160 1.bigwig_0 0 +chr21 9414175 9414180 1.bigwig_0 0 +chr21 9414215 9414225 1.bigwig_0 0 +chr21 9414255 9414260 1.bigwig_0 0 +chr21 9414265 9414270 1.bigwig_0 0 +chr21 9414280 9414285 1.bigwig_0 0 +chr21 9414305 9414310 1.bigwig_0 0 +chr21 9414435 9414440 1.bigwig_0 0 +chr21 9414525 9414530 1.bigwig_0 0 +chr21 9414585 9414590 1.bigwig_0 0 +chr21 9414595 9414600 1.bigwig_0 0 +chr21 9414655 9414665 1.bigwig_0 0 +chr21 9414680 9414690 1.bigwig_0 0 +chr21 9414695 9414700 1.bigwig_0 0 +chr21 9414705 9414710 1.bigwig_0 0 +chr21 9414720 9414725 1.bigwig_0 0 +chr21 9414755 9414760 1.bigwig_0 0 +chr21 9414775 9414780 1.bigwig_0 0 +chr21 9414785 9414790 1.bigwig_0 0 +chr21 9414820 9414825 1.bigwig_0 0 +chr21 9414835 9414840 1.bigwig_0 0 +chr21 9414850 9414855 1.bigwig_0 0 +chr21 9414860 9414870 1.bigwig_0 0 +chr21 9414905 9414910 1.bigwig_0 0 +chr21 9414925 9414930 1.bigwig_0 0 +chr21 9414955 9414960 1.bigwig_0 0 +chr21 9414975 9414980 1.bigwig_0 0 +chr21 9414995 9415000 1.bigwig_0 0 +chr21 9415040 9415055 1.bigwig_0 0 +chr21 9415065 9415075 1.bigwig_0 0 +chr21 9415095 9415100 1.bigwig_0 0 +chr21 9415105 9415115 1.bigwig_0 0 +chr21 9415135 9415140 1.bigwig_0 0 +chr21 9415150 9415155 1.bigwig_0 0 +chr21 9415170 9415175 1.bigwig_0 0 +chr21 9415270 9415275 1.bigwig_0 0 +chr21 9415320 9415325 1.bigwig_0 0 +chr21 9415385 9415390 1.bigwig_0 0 +chr21 9415470 9415475 1.bigwig_0 0 +chr21 9415535 9415540 1.bigwig_0 0 +chr21 9415595 9415600 1.bigwig_0 0 +chr21 9415665 9415670 1.bigwig_0 0 +chr21 9415685 9415700 1.bigwig_0 0 +chr21 9415710 9415715 1.bigwig_0 0 +chr21 9415820 9415830 1.bigwig_0 0 +chr21 9415880 9415885 1.bigwig_0 0 +chr21 9416020 9416025 1.bigwig_0 0 +chr21 9416080 9416085 1.bigwig_0 0 +chr21 9416095 9416100 1.bigwig_0 0 +chr21 9416130 9416135 1.bigwig_0 0 +chr21 9416150 9416155 1.bigwig_0 0 +chr21 9416165 9416175 1.bigwig_0 0 +chr21 9416185 48129895 1.bigwig_0 0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/bedoutlo_sample Tue Jul 23 23:12:23 2024 +0000 @@ -0,0 +1,2 @@ +Merlin 0 9 bigwig_sample_0 0 +Merlin 70049 180929 bigwig_sample_0 0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/table2_sample Tue Jul 23 23:12:23 2024 +0000 @@ -0,0 +1,74 @@ +Descriptive measures +bigwig bigwig_sample +contig Merlin +n 180929 +mean 6354.313736 +std 9951.749936 +min 0.000000 +max 32767.000000 +qtop 24359.00 +qbot 0.00 +First/Last 10 value counts +Value Count +0.00 110889 +13.00 30 +22.00 10 +26.00 10 +29.00 10 +40.00 10 +43.00 10 +53.00 10 +57.00 10 +60.00 20 +32721.00 10 +32724.00 10 +32726.00 10 +32728.00 10 +32730.00 10 +32731.00 20 +32737.00 10 +32745.00 10 +32766.00 10 +32767.00 10 +Histogram of bigwig values +Merlin 1638.35 | 114,349 | ************************************************** +Merlin 3276.70 | 3,650 | * +Merlin 4915.05 | 3,620 | * +Merlin 6553.40 | 3,570 | * +Merlin 8191.75 | 3,570 | * +Merlin 9830.10 | 3,410 | * +Merlin 11468.45 | 3,610 | * +Merlin 13106.80 | 3,170 | * +Merlin 14745.15 | 3,310 | * +Merlin 16383.50 | 3,390 | * +Merlin 18021.85 | 3,270 | * +Merlin 19660.20 | 3,680 | * +Merlin 21298.55 | 3,560 | * +Merlin 22936.90 | 3,490 | * +Merlin 24575.25 | 3,530 | * +Merlin 26213.60 | 3,460 | * +Merlin 27851.95 | 3,470 | * +Merlin 29490.30 | 3,500 | * +Merlin 31128.65 | 3,920 | * +Merlin 32767.00 | 3,400 | * +Merlin ------------ |------------ | +Merlin N= | 180,929 | +Merlin ------------ |------------ | + +Descriptive measures +bigwig 1.bigwig +contig chr21 +n 48129895 +mean 0.003446 +std 0.400601 +min 0.000000 +max 100.000000 +qtop 0.00 +qbot 0.00 +chr21: 0.000000 occurs 48125565 times +chr21: 20.000000 occurs 1660 times +chr21: 40.000000 occurs 1610 times +chr21: 50.000000 occurs 5 times +chr21: 60.000000 occurs 840 times +chr21: 80.000000 occurs 195 times +chr21: 100.000000 occurs 20 times
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/table3_sample Tue Jul 23 23:12:23 2024 +0000 @@ -0,0 +1,57 @@ +Descriptive measures +bigwig bigwig_sample +contig Merlin +n 180929 +mean 6354.313736 +std 9951.749936 +min 0.000000 +max 32767.000000 +qtop 24359.00 +qbot 0.00 +First/Last 10 value counts +Value Count +0.00 110889 +13.00 30 +22.00 10 +26.00 10 +29.00 10 +40.00 10 +43.00 10 +53.00 10 +57.00 10 +60.00 20 +32721.00 10 +32724.00 10 +32726.00 10 +32728.00 10 +32730.00 10 +32731.00 20 +32737.00 10 +32745.00 10 +32766.00 10 +32767.00 10 +Histogram of bigwig values +Merlin 1638.35 | 114,349 | ************************************************** +Merlin 3276.70 | 3,650 | * +Merlin 4915.05 | 3,620 | * +Merlin 6553.40 | 3,570 | * +Merlin 8191.75 | 3,570 | * +Merlin 9830.10 | 3,410 | * +Merlin 11468.45 | 3,610 | * +Merlin 13106.80 | 3,170 | * +Merlin 14745.15 | 3,310 | * +Merlin 16383.50 | 3,390 | * +Merlin 18021.85 | 3,270 | * +Merlin 19660.20 | 3,680 | * +Merlin 21298.55 | 3,560 | * +Merlin 22936.90 | 3,490 | * +Merlin 24575.25 | 3,530 | * +Merlin 26213.60 | 3,460 | * +Merlin 27851.95 | 3,470 | * +Merlin 29490.30 | 3,500 | * +Merlin 31128.65 | 3,920 | * +Merlin 32767.00 | 3,400 | * +Merlin ------------ |------------ | +Merlin N= | 180,929 | +Merlin ------------ |------------ | +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/table_only_sample Tue Jul 23 23:12:23 2024 +0000 @@ -0,0 +1,74 @@ +Descriptive measures +bigwig bigwig_sample +contig Merlin +n 180929 +mean 6354.313736 +std 9951.749936 +min 0.000000 +max 32767.000000 +qtop noqhi +qbot noqlo +First/Last 10 value counts +Value Count +0.00 110889 +13.00 30 +22.00 10 +26.00 10 +29.00 10 +40.00 10 +43.00 10 +53.00 10 +57.00 10 +60.00 20 +32721.00 10 +32724.00 10 +32726.00 10 +32728.00 10 +32730.00 10 +32731.00 20 +32737.00 10 +32745.00 10 +32766.00 10 +32767.00 10 +Histogram of bigwig values +Merlin 1638.35 | 114,349 | ************************************************** +Merlin 3276.70 | 3,650 | * +Merlin 4915.05 | 3,620 | * +Merlin 6553.40 | 3,570 | * +Merlin 8191.75 | 3,570 | * +Merlin 9830.10 | 3,410 | * +Merlin 11468.45 | 3,610 | * +Merlin 13106.80 | 3,170 | * +Merlin 14745.15 | 3,310 | * +Merlin 16383.50 | 3,390 | * +Merlin 18021.85 | 3,270 | * +Merlin 19660.20 | 3,680 | * +Merlin 21298.55 | 3,560 | * +Merlin 22936.90 | 3,490 | * +Merlin 24575.25 | 3,530 | * +Merlin 26213.60 | 3,460 | * +Merlin 27851.95 | 3,470 | * +Merlin 29490.30 | 3,500 | * +Merlin 31128.65 | 3,920 | * +Merlin 32767.00 | 3,400 | * +Merlin ------------ |------------ | +Merlin N= | 180,929 | +Merlin ------------ |------------ | + +Descriptive measures +bigwig 1.bigwig +contig chr21 +n 48129895 +mean 0.003446 +std 0.400601 +min 0.000000 +max 100.000000 +qtop noqhi +qbot noqlo +chr21: 0.000000 occurs 48125565 times +chr21: 20.000000 occurs 1660 times +chr21: 40.000000 occurs 1610 times +chr21: 50.000000 occurs 5 times +chr21: 60.000000 occurs 840 times +chr21: 80.000000 occurs 195 times +chr21: 100.000000 occurs 20 times
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/table_qlo_notset_sample Tue Jul 23 23:12:23 2024 +0000 @@ -0,0 +1,57 @@ +Descriptive measures +bigwig bigwig_sample +contig Merlin +n 180929 +mean 6354.313736 +std 9951.749936 +min 0.000000 +max 32767.000000 +qtop 31906.72 +qbot noqlo +First/Last 10 value counts +Value Count +0.00 110889 +13.00 30 +22.00 10 +26.00 10 +29.00 10 +40.00 10 +43.00 10 +53.00 10 +57.00 10 +60.00 20 +32721.00 10 +32724.00 10 +32726.00 10 +32728.00 10 +32730.00 10 +32731.00 20 +32737.00 10 +32745.00 10 +32766.00 10 +32767.00 10 +Histogram of bigwig values +Merlin 1638.35 | 114,349 | ************************************************** +Merlin 3276.70 | 3,650 | * +Merlin 4915.05 | 3,620 | * +Merlin 6553.40 | 3,570 | * +Merlin 8191.75 | 3,570 | * +Merlin 9830.10 | 3,410 | * +Merlin 11468.45 | 3,610 | * +Merlin 13106.80 | 3,170 | * +Merlin 14745.15 | 3,310 | * +Merlin 16383.50 | 3,390 | * +Merlin 18021.85 | 3,270 | * +Merlin 19660.20 | 3,680 | * +Merlin 21298.55 | 3,560 | * +Merlin 22936.90 | 3,490 | * +Merlin 24575.25 | 3,530 | * +Merlin 26213.60 | 3,460 | * +Merlin 27851.95 | 3,470 | * +Merlin 29490.30 | 3,500 | * +Merlin 31128.65 | 3,920 | * +Merlin 32767.00 | 3,400 | * +Merlin ------------ |------------ | +Merlin N= | 180,929 | +Merlin ------------ |------------ | +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/table_sample Tue Jul 23 23:12:23 2024 +0000 @@ -0,0 +1,57 @@ +Descriptive measures +bigwig bigwig_sample +contig Merlin +n 180929 +mean 6354.313736 +std 9951.749936 +min 0.000000 +max 32767.000000 +qtop 31906.72 +qbot 0.00 +First/Last 10 value counts +Value Count +0.00 110889 +13.00 30 +22.00 10 +26.00 10 +29.00 10 +40.00 10 +43.00 10 +53.00 10 +57.00 10 +60.00 20 +32721.00 10 +32724.00 10 +32726.00 10 +32728.00 10 +32730.00 10 +32731.00 20 +32737.00 10 +32745.00 10 +32766.00 10 +32767.00 10 +Histogram of bigwig values +Merlin 1638.35 | 114,349 | ************************************************** +Merlin 3276.70 | 3,650 | * +Merlin 4915.05 | 3,620 | * +Merlin 6553.40 | 3,570 | * +Merlin 8191.75 | 3,570 | * +Merlin 9830.10 | 3,410 | * +Merlin 11468.45 | 3,610 | * +Merlin 13106.80 | 3,170 | * +Merlin 14745.15 | 3,310 | * +Merlin 16383.50 | 3,390 | * +Merlin 18021.85 | 3,270 | * +Merlin 19660.20 | 3,680 | * +Merlin 21298.55 | 3,560 | * +Merlin 22936.90 | 3,490 | * +Merlin 24575.25 | 3,530 | * +Merlin 26213.60 | 3,460 | * +Merlin 27851.95 | 3,470 | * +Merlin 29490.30 | 3,500 | * +Merlin 31128.65 | 3,920 | * +Merlin 32767.00 | 3,400 | * +Merlin ------------ |------------ | +Merlin N= | 180,929 | +Merlin ------------ |------------ | +