/usr/bin/guess-ploidy.py is in bcftools 1.7-2.
This file is owned by root:root, with mode 0o755.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 | #!/usr/bin/env python
#
# Plot the output of "bcftools +guess-ploidy -v"
#
# Copyright (C) 2016 Genome Research Ltd.
#
# Author: Petr Danecek <pd3@sanger.ac.uk>
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
# DEALINGS IN THE SOFTWARE.
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import random, math, sys
import csv
csv.register_dialect('tab', delimiter='\t', quoting=csv.QUOTE_NONE)
if len(sys.argv) != 3:
print >> sys.stderr, 'About: Plot output of "bcftools +guess-ploidy -v"'
print >> sys.stderr, 'Usage: guess-ploidy.py <guess-ploidy.out> <image-prefix>'
sys.exit()
prefix = sys.argv[2]
dpi = 150
def add_value(dat,key,x,y):
if key not in dat:
dat[key] = []
dat[key].append([x,y])
smpl2sex = {}
dat = {}
with open(sys.argv[1]) as f:
reader = csv.reader(f, 'tab')
for row in reader:
if row[0][0]=="#": continue
if row[0]=="SEX":
smpl = row[1]
sex = row[2]
phap = float(row[3])
pdip = float(row[4])
ndat = float(row[5])
score = float(row[6])
smpl2sex[smpl] = sex
add_value(dat,'score',smpl,score)
add_value(dat,'phap',smpl,phap)
add_value(dat,'pdip',smpl,pdip)
add_value(dat,'ndat',smpl,ndat)
def sort_by_val(arr):
for x in (sorted(arr, key=lambda x:x[1])):
id = len(smpl2id)
smpl2id[x[0]] = id
arr = sorted(arr, key=lambda x:smpl2id[x[0]])
return arr
def select_sex(arr,sex):
out = []
for x in arr:
if smpl2sex[x[0]]==sex: out.append(x)
return out
col = {}
col['blue'] = '#396ab1'
col['orange'] = '#da7c30'
col['green'] = '#3e9651'
col['red'] = '#cc2529'
col['grey'] = '#000000'
col['purple'] = '#6b4c9a'
col['yellow'] = '#ccc210'
if True:
fig,ax1 = plt.subplots(1,1,figsize=(6,4))
smpl2id = {}
dat['score'] = sort_by_val(dat['score'])
dat['scoreM'] = select_sex(dat['score'],'M')
dat['scoreF'] = select_sex(dat['score'],'F')
ax2 = ax1.twinx()
plots = ax2.plot([smpl2id[x[0]] for x in dat['ndat']],[x[1] for x in dat['ndat']],'v',color=col['grey'],ms=2,label='Number of sites')
plots += ax1.plot([smpl2id[x[0]] for x in dat['phap']],[x[1] for x in dat['phap']],'.',color=col['blue'],ms=3,label='log P(haploid)')
plots += ax1.plot([smpl2id[x[0]] for x in dat['pdip']],[x[1] for x in dat['pdip']],'.',color=col['yellow'],ms=3,label='log P(diploid)')
plots += ax1.plot([smpl2id[x[0]] for x in dat['scoreM']],[x[1] for x in dat['scoreM']],'.',color=col['green'],label='Total score: Males')
plots += ax1.plot([smpl2id[x[0]] for x in dat['scoreF']],[x[1] for x in dat['scoreF']],'.',color=col['red'],label='Total score: Females')
labels = [l.get_label() for l in plots]
ax1.legend(plots,labels,loc='best', frameon=False, numpoints=1, prop={'size':9})
ax1.set_zorder(ax2.get_zorder()+1)
ax1.patch.set_visible(False)
ax1.set_xlabel('Sample')
ax1.set_ylabel('Score')
ax2.set_ylabel('Number of sites')
ax2.set_yscale('log')
# ax1.set_yscale('log')
ax1.ticklabel_format(style='sci', scilimits=(-3,4), axis='x')
plt.subplots_adjust(left=0.13,right=0.89,bottom=0.13,top=0.9,hspace=0.1)
plt.savefig(prefix+'.png',dpi=dpi)
plt.close()
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