annotate bigwig_outlier_bed.py @ 2:a7d26bca0a3b draft

planemo upload for repository https://github.com/jackh726/bigtools commit ce6b9f638ebcebcad5a5b10219f252962f30e5cc-dirty
author fubar
date Mon, 01 Jul 2024 03:05:55 +0000
parents c71db540eb38
children eb17eb8a3658
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1 """
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2 Ross Lazarus June 2024 for VGP
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4 Bigwigs are great, but hard to reliably "see" small low coverage or small very high coverage regions.
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5 Colouring in JB2 tracks will need a new plugin, so this code will find bigwig regions above and below a chosen percentile point.
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6 0.99 and 0.01 work well in testing with a minimum span of 10 bp.
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8 Multiple bigwigs **with the same reference** can be combined - bed segments will be named appropriately
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9 Combining multiple references works but is silly because only display will rely on one reference so others will not be shown...
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11 Tricksy numpy method from http://gregoryzynda.com/python/numpy/contiguous/interval/2019/11/29/contiguous-regions.html
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12 takes about 95 seconds for a 17MB test wiggle
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14 JBrowse2 bed normally displays ignore the score, so could provide separate low/high bed file outputs as an option.
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16 Update june 30 2024: wrote a 'no-build' plugin for beds to display red/blue if >0/<0 so those are used for scores
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17 Bed interval naming must be short for JB2 but needs input bigwig name and (lo or hi).
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19 """
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22 import argparse
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23 import numpy as np
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24 import pybigtools
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25 import sys
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28 from pathlib import Path
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30 class findOut():
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32 def __init__(self, args):
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33 self.bwnames=args.bigwig
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34 self.bwlabels=args.bigwiglabels
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35 self.bedwin=args.minwin
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36 self.qlo=args.qlo
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37 self.qhi=args.qhi
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38 self.bedouthilo=args.bedouthilo
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39 self.bedouthi=args.bedouthi
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40 self.bedoutlo=args.bedoutlo
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41 self.tableout = args.tableout
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42 self.bedwin = args.minwin
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43 self.qhi = args.qhi
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44 self.qlo = args.qlo
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45 self.makeBed()
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46
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47 def processVals(self, bw, isTop):
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48 # http://gregoryzynda.com/python/numpy/contiguous/interval/2019/11/29/contiguous-regions.html
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49 if isTop:
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50 bwex = np.r_[False, bw >= self.bwtop, False] # extend with 0s
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51 else:
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52 bwex = np.r_[False, bw <= self.bwbot, False]
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53 bwexd = np.diff(bwex)
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54 bwexdnz = bwexd.nonzero()[0]
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55 bwregions = np.reshape(bwexdnz, (-1,2))
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56 return bwregions
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57
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58 def writeBed(self, bed, bedfname):
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59 """
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60 potentially multiple
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61 """
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62 bed.sort()
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63 beds = ['%s\t%d\t%d\t%s\t%d' % x for x in bed]
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64 with open(bedfname, "w") as bedf:
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65 bedf.write('\n'.join(beds))
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66 bedf.write('\n')
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67 print('Wrote %d bed regions to %s' % (len(bed), bedfname))
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68
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69 def makeBed(self):
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70 bedhi = []
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71 bedlo = []
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72 bwlabels = self.bwlabels
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73 bwnames = self.bwnames
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74 print('bwnames=', bwnames, "bwlabs=", bwlabels)
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75 for i, bwname in enumerate(bwnames):
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76 bwlabel = bwlabels[i].replace(" ",'')
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77 p = Path('in.bw')
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78 p.symlink_to( bwname ) # required by pybigtools (!)
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79 bwf = pybigtools.open('in.bw')
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80 chrlist = bwf.chroms()
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81 chrs = list(chrlist.keys())
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82 chrs.sort()
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83 restab = ["contig\tn\tmean\tstd\tmin\tmax\tqtop\tqbot"]
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84 for chr in chrs:
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85 bw = bwf.values(chr)
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86 bw = bw[~np.isnan(bw)] # some have NaN if parts of a contig not covered
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87 if self.qhi is not None:
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88 self.bwtop = np.quantile(bw, self.qhi)
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89 bwhi = self.processVals(bw, isTop=True)
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90 for i, seg in enumerate(bwhi):
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91 if seg[1] - seg[0] >= self.bedwin:
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92 bedhi.append((chr, seg[0], seg[1], '%s_hi' % (bwlabel), 1))
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93 if self.qlo is not None:
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94 self.bwbot = np.quantile(bw, self.qlo)
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95 bwlo = self.processVals(bw, isTop=False)
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96 for i, seg in enumerate(bwlo):
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97 if seg[1] - seg[0] >= self.bedwin:
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98 bedlo.append((chr, seg[0], seg[1], '%s_lo' % (bwlabel), -1))
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99 bwmean = np.mean(bw)
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100 bwstd = np.std(bw)
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101 bwmax = np.max(bw)
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102 nrow = np.size(bw)
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103 bwmin = np.min(bw)
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104 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))
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105 print('\n'.join(restab), '\n')
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106 if self.tableout:
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107 with open(self.tableout) as t:
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108 t.write('\n'.join(restab))
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109 t.write('\n')
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110 if self.bedoutlo:
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111 if self.qlo:
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112 self.writeBed(bedlo, self.bedoutlo)
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113 if self.bedouthi:
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114 if self.qhi:
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115 self.writeBed(bedhi, self.bedouthi)
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116 if self.bedouthilo:
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117 allbed = bedlo + bedhi
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118 self.writeBed(allbed, self.bedouthilo)
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119 return restab
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120
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121
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122 if __name__ == "__main__":
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123 parser = argparse.ArgumentParser()
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124 a = parser.add_argument
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125 a('-m', '--minwin',default=10, type=int)
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126 a('-l', '--qlo',default=None, type=float)
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127 a('-i', '--qhi',default=None, type=float)
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128 a('-w', '--bigwig', nargs='+')
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129 a('-n', '--bigwiglabels', nargs='+')
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130 a('-o', '--bedouthilo', default=None, help="optional high and low combined bed")
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131 a('-u', '--bedouthi', default=None, help="optional high only bed")
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132 a('-b', '--bedoutlo', default=None, help="optional low only bed")
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133 a('-t', '--tableout', default=None)
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134 args = parser.parse_args()
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135 print('args=', args)
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136 if not (args.bedouthilo or args.bedouthi or args.bedoutlo):
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137 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")
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138 sys.exit(2)
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139 if not (args.qlo or args.qhi):
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140 sys.stderr.write("bigwig_outlier_bed.py cannot usefully run - need one or both of quantile cutpoints qhi and qlo")
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141 sys.exit(2)
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142 restab = findOut(args)
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143 if args.tableout:
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144 with open(args.tableout, 'w') as tout:
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145 tout.write('\n'.join(restab))
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146 tout.write('\n')
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147
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148