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1 #######################################################################
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2 #######################################################################
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3 # CoNIFER: Copy Number Inference From Exome Reads
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4 # Developed by Niklas Krumm (C) 2012
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5 # nkrumm@gmail.com
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6 #
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7 # homepage: http://conifer.sf.net
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8 # This program is described in:
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9 # Krumm et al. 2012. Genome Research. doi:10.1101/gr.138115.112
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10 #
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11 # This file is part of CoNIFER.
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12 # CoNIFER is free software: you can redistribute it and/or modify
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13 # it under the terms of the GNU General Public License as published by
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14 # the Free Software Foundation, either version 3 of the License, or
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15 # (at your option) any later version.
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16 #
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17 # This program is distributed in the hope that it will be useful,
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18 # but WITHOUT ANY WARRANTY; without even the implied warranty of
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19 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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20 # GNU General Public License for more details.
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21 #
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22 # You should have received a copy of the GNU General Public License
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23 # along with this program. If not, see <http://www.gnu.org/licenses/>.
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24 #######################################################################
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25 #######################################################################
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26
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27 import argparse
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28 import os, sys, copy
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29 import glob
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30 import csv
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31 import conifer_functions as cf
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32 import operator
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33 from tables import *
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34 import numpy as np
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35
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36 def CF_analyze(args):
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37 # do path/file checks:
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38 try:
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39 # read probes table
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40 probe_fn = str(args.probes[0])
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41 probes = cf.loadProbeList(probe_fn)
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42 num_probes = len(probes)
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43 print '[INIT] Successfully read in %d probes from %s' % (num_probes, probe_fn)
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44 except IOError as e:
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45 print '[ERROR] Cannot read probes file: ', probe_fn
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46 sys.exit(0)
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47
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48 try:
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49 svd_outfile_fn = str(args.output)
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50 # h5file_out = openFile(svd_outfile_fn, mode='w')
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51 h5file_out = open_file(svd_outfile_fn, mode='w')
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52 # probe_group = h5file_out.createGroup("/","probes","probes")
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53 probe_group = h5file_out.create_group("/","probes","probes")
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54 except IOError as e:
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55 print '[ERROR] Cannot open SVD output file for writing: ', svd_outfile_fn
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56 sys.exit(0)
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57
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58 if args.write_svals != "":
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59 sval_f = open(args.write_svals,'w')
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60
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61 if args.plot_scree != "":
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62 try:
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63 import matplotlib
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64 matplotlib.use('Agg')
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65 import matplotlib.pyplot as plt
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66 import pylab as P
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67 from matplotlib.lines import Line2D
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68 from matplotlib.patches import Rectangle
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69 except:
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70 print "[ERROR] One or more of the required modules for plotting cannot be loaded! Are matplotlib and pylab installed?"
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71 sys.exit(0)
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72
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73 plt.gcf().clear()
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74 fig = plt.figure(figsize=(10,5))
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75 ax = fig.add_subplot(111)
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76
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77 rpkm_dir = str(args.rpkm_dir[0])
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78 rpkm_files = glob.glob(rpkm_dir + "/*")
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79 if len(rpkm_files) == 0:
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80 print '[ERROR] Cannot find any files in RPKM directory (or directory path is incorrect): ', rpkm_dir
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81 sys.exit(0)
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82 elif len(rpkm_files) == 1:
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83 print '[ERROR] Found only 1 RPKM file (sample). CoNIFER requires multiple samples (8 or more) to run. Exiting.'
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84 sys.exit(0)
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85 elif len(rpkm_files) < 8:
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86 print '[WARNING] Only found %d samples... this is less than the recommended minimum, and CoNIFER may not analyze this dataset correctly!' % len(rpkm_files)
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87 elif len(rpkm_files) <= int(args.svd):
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88 print '[ERROR] The number of SVD values specified (%d) must be less than the number of samples (%d). Either add more samples to the analysis or reduce the --svd parameter! Exiting.' % (len(rpkm_files), int(args.svd))
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89 sys.exit(0)
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90 else:
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91 print '[INIT] Found %d RPKM files in %s' % (len(rpkm_files), rpkm_dir)
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92
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93 # read in samples names and generate file list
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94 samples = {}
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95 for f in rpkm_files:
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96 s = '.'.join(f.split('/')[-1].split('.')[0:-1])
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97 print "[INIT] Mapping file to sampleID: %s --> %s" % (f, s)
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98 samples[s] = f
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99
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100 #check uniqueness and total # of samples
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101 if len(set(samples)) != len(set(rpkm_files)):
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102 print '[ERROR] Could not successfully derive sample names from RPKM filenames. There are probably non-unique sample names! Please rename files using <sampleID>.txt format!'
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103 sys.exit(0)
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104
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105 # LOAD RPKM DATA
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106 RPKM_data = np.zeros([num_probes,len(samples)], dtype=np.float)
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107 failed_samples = 0
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108
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109 for i,s in enumerate(samples.keys()):
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110 t = np.loadtxt(samples[s], dtype=np.float, delimiter="\t", skiprows=0, usecols=[2])
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111 if len(t) != num_probes:
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112 print "[WARNING] Number of RPKM values for %s in file %s does not match number of defined probes in %s. **This sample will be dropped from analysis**!" % (s, samples[s], probe_fn)
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113 _ = samples.pop(s)
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114 failed_samples += 1
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115 else:
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116 RPKM_data[:,i] = t
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117 print "[INIT] Successfully read RPKM data for sampleID: %s" % s
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118
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119 RPKM_data = RPKM_data[:,0:len(samples)]
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120 print "[INIT] Finished reading RPKM files. Total number of samples in experiment: %d (%d failed to read properly)" % (len(samples), failed_samples)
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121
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122 if len(samples) <= int(args.svd):
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123 print '[ERROR] The number of SVD values specified (%d) must be less than the number of samples (%d). Either add more samples to the analysis or reduce the --svd parameter! Exiting.' % (int(args.svd), len(samples))
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124 sys.exit(0)
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125
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126 # BEGIN
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127 chrs_to_process = set(map(operator.itemgetter("chr"),probes))
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128 chrs_to_process_str = ', '.join([cf.chrInt2Str(c) for c in chrs_to_process])
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129 print '[INIT] Attempting to process chromosomes: ', chrs_to_process_str
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130
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131
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132
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133 for chr in chrs_to_process:
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134 print "[RUNNING: chr%d] Now on: %s" %(chr, cf.chrInt2Str(chr))
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135 chr_group_name = "chr%d" % chr
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136 # chr_group = h5file_out.createGroup("/",chr_group_name,chr_group_name)
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137 chr_group = h5file_out.create_group("/",chr_group_name,chr_group_name)
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138
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139 chr_probes = filter(lambda i: i["chr"] == chr, probes)
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140 num_chr_probes = len(chr_probes)
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141 start_probeID = chr_probes[0]['probeID']
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142 stop_probeID = chr_probes[-1]['probeID']
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143 print "[RUNNING: chr%d] Found %d probes; probeID range is [%d-%d]" % (chr, len(chr_probes), start_probeID-1, stop_probeID) # probeID is 1-based and slicing is 0-based, hence the start_probeID-1 term
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144
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145 rpkm = RPKM_data[start_probeID:stop_probeID,:]
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146
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147 print "[RUNNING: chr%d] Calculating median RPKM" % chr
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148 median = np.median(rpkm,1)
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149 sd = np.std(rpkm,1)
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150 probe_mask = median >= float(args.min_rpkm)
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151 print "[RUNNING: chr%d] Masking %d probes with median RPKM < %f" % (chr, np.sum(probe_mask==False), float(args.min_rpkm))
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152
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153 rpkm = rpkm[probe_mask, :]
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154 num_chr_probes = np.sum(probe_mask)
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155
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156 if num_chr_probes <= len(samples):
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157 print "[ERROR] This chromosome has fewer informative probes than there are samples in the analysis! There are probably no mappings on this chromosome. Please remove these probes from the probes.txt file"
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158 sys.exit(0)
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159
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160 probeIDs = np.array(map(operator.itemgetter("probeID"),chr_probes))[probe_mask]
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161 probe_starts = np.array(map(operator.itemgetter("start"),chr_probes))[probe_mask]
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162 probe_stops = np.array(map(operator.itemgetter("stop"),chr_probes))[probe_mask]
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163 gene_names = np.array(map(operator.itemgetter("name"),chr_probes))[probe_mask]
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164
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165 dt = np.dtype([('probeID',np.uint32),('start',np.uint32),('stop',np.uint32), ('name', np.str_, 20)])
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166
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167 out_probes = np.empty(num_chr_probes,dtype=dt)
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168 out_probes['probeID'] = probeIDs
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169 out_probes['start'] = probe_starts
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170 out_probes['stop'] = probe_stops
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171 out_probes['name'] = gene_names
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172 # probe_table = h5file_out.createTable(probe_group,"probes_chr%d" % chr,cf.probe,"chr%d" % chr)
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173 probe_table = h5file_out.create_table(probe_group,"probes_chr%d" % chr,cf.probe,"chr%d" % chr)
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174 probe_table.append(out_probes)
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175
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176 print "[RUNNING: chr%d] Calculating ZRPKM scores..." % chr
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177 rpkm = np.apply_along_axis(cf.zrpkm, 0, rpkm, median[probe_mask], sd[probe_mask])
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178
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179 # svd transform
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180 print "[RUNNING: chr%d] SVD decomposition..." % chr
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181 components_removed = int(args.svd)
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182
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183 U, S, Vt = np.linalg.svd(rpkm,full_matrices=False)
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184 new_S = np.diag(np.hstack([np.zeros([components_removed]),S[components_removed:]]))
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185
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186 if args.write_svals != "":
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187 sval_f.write('chr' + str(chr) + '\t' + '\t'.join([str(_i) for _i in S]) + "\n")
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188
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189 if args.plot_scree != "":
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190 ax.plot(S, label='chr' + str(chr),lw=0.5)
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191
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192 # reconstruct data matrix
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193 rpkm = np.dot(U, np.dot(new_S, Vt))
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194
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195
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196 # save to HDF5 file
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197 print "[RUNNING: chr%d] Saving SVD-ZRPKM values" % chr
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198
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199 for i,s in enumerate(samples):
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200 out_data = np.empty(num_chr_probes,dtype='u4,f8')
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201 out_data['f0'] = probeIDs
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202 out_data['f1'] = rpkm[:,i]
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203 # sample_tbl = h5file_out.createTable(chr_group,"sample_" + str(s),cf.rpkm_value,"%s" % str(s))
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204 sample_tbl = h5file_out.create_table(chr_group,"sample_" + str(s),cf.rpkm_value,"%s" % str(s))
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205 sample_tbl.append(out_data)
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206
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207
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208 print "[RUNNING] Saving sampleIDs to file..."
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209 # sample_group = h5file_out.createGroup("/","samples","samples")
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210 # sample_table = h5file_out.createTable(sample_group,"samples",cf.sample,"samples")
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211 sample_group = h5file_out.create_group("/","samples","samples")
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212 sample_table = h5file_out.create_table(sample_group,"samples",cf.sample,"samples")
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213 dt = np.dtype([('sampleID',np.str_,100)])
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214 out_samples = np.empty(len(samples.keys()),dtype=dt)
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215 out_samples['sampleID'] = np.array(samples.keys())
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216 sample_table.append(out_samples)
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217
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218
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219 if args.write_sd != "":
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220 print "[RUNNING] Calculating standard deviations for all samples (this can take a while)..."
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221
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222 sd_file = open(args.write_sd,'w')
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223
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224 for i,s in enumerate(samples):
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225 # collect all SVD-ZRPKM values
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226 count = 1
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227 for chr in chrs_to_process:
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228 if count == 1:
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229 sd_out = h5file_out.root._f_getChild("chr%d" % chr)._f_getChild("sample_%s" % s).read(field="rpkm").flatten()
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230 else:
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231 sd_out = np.hstack([sd_out,out.h5file_out.root._f_getChild("chr%d" % chr)._f_getChild("sample_%s" % s).read(field="rpkm").flatten()])
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232
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233 sd = np.std(sd_out)
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234 sd_file.write("%s\t%f\n" % (s,sd))
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235
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236 sd_file.close()
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237
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238 if args.plot_scree != "":
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239 plt.title("Scree plot")
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240 if len(samples) < 50:
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241 plt.xlim([0,len(samples)])
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242 plt.xlabel("S values")
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243 else:
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244 plt.xlim([0,50])
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245 plt.xlabel("S values (only first 50 plotted)")
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246 plt.ylabel("Relative contributed variance")
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247 plt.savefig(args.plot_scree)
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248
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249 print "[FINISHED]"
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250 h5file_out.close()
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251 sys.exit(0)
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252
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253 def CF_export(args):
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254 try:
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255 h5file_in_fn = str(args.input)
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256 # h5file_in = openFile(h5file_in_fn, mode='r')
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257 h5file_in = open_file(h5file_in_fn, mode='r')
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258 except IOError as e:
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259 print '[ERROR] Cannot open CoNIFER input file for reading: ', h5file_in_fn
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260 sys.exit(0)
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261
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262 # read probes
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263 probes = {}
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264 for probes_chr in h5file_in.root.probes:
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265 probes[probes_chr.title] = probes_chr.read()
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266
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267 if args.sample =='all':
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268 all_samples = list(h5file_in.root.samples.samples.read(field="sampleID"))
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269
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270 out_path = os.path.abspath(args.output)
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271
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272 print "[INIT] Preparing to export all samples (%d samples) to %s" % (len(all_samples), out_path)
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273 for sample in all_samples:
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274 try:
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275 outfile_fn = out_path + "/" + sample + ".bed"
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276 outfile_f = open(outfile_fn,'w')
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277 except IOError as e:
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278 print '[ERROR] Cannot open output file for writing: ', outfile_fn
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279 sys.exit(0)
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280 print "[RUNNING] Exporting %s" % sample
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281
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282 cf.export_sample(h5file_in,sample,probes,outfile_f)
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283 outfile_f.close()
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284
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285 elif len(args.sample) == 1:
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286 out_path = os.path.abspath(args.output)
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287 sample = args.sample[0]
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288 print "[INIT] Preparing to export sampleID %s to %s" % (args.sample[0], out_path)
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289 try:
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290 if os.path.isdir(out_path):
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291 outfile_fn = out_path + "/" + sample + ".bed"
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292 else:
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293 outfile_fn = out_path
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294 outfile_f = open(outfile_fn,'w')
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295 except IOError as e:
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296 print '[ERROR] Cannot open output file for writing: ', outfile_fn
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297 sys.exit(0)
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298 print "[RUNNING] Exporting %s to %s" % (sample, outfile_fn)
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299
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300 cf.export_sample(h5file_in,sample,probes,outfile_f)
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301 outfile_f.close()
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302
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303 else:
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304 out_path = os.path.abspath(args.output)
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305 print "[INIT] Preparing to export %d samples to %s" % (len(args.sample), out_path)
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306 for sample in args.sample:
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307 try:
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308 if os.path.isdir(out_path):
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309 outfile_fn = out_path + "/" + sample + ".bed"
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310 else:
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311 outfile_fn = out_path
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312 outfile_f = open(outfile_fn,'w')
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313 except IOError as e:
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314 print '[ERROR] Cannot open output file for writing: ', outfile_fn
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315 sys.exit(0)
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316 print "[RUNNING] Exporting %s to %s" % (sample, outfile_fn)
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317
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318 cf.export_sample(h5file_in,sample,probes,outfile_f)
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319 outfile_f.close()
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320 sys.exit(0)
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321
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322 def CF_call(args):
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323 try:
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324 h5file_in_fn = str(args.input)
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325 # h5file_in = openFile(h5file_in_fn, mode='r')
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326 h5file_in = open_file(h5file_in_fn, mode='r')
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327 except IOError as e:
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328 print '[ERROR] Cannot open CoNIFER input file for reading: ', h5file_in_fn
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329 sys.exit(0)
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330
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331 try:
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332 callfile_fn = str(args.output)
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333 callfile_f = open(callfile_fn, mode='w')
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334 except IOError as e:
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335 print '[ERROR] Cannot open output file for writing: ', callfile_fn
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336 sys.exit(0)
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337
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338 chrs_to_process = []
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339 for chr in h5file_in.root:
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340 if chr._v_title not in ('probes','samples'):
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341 chrs_to_process.append(chr._v_title.replace("chr",""))
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342
|
|
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343 h5file_in.close()
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344
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|
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345 print '[INIT] Initializing caller at threshold = %f' % (args.threshold)
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346
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|
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347 r = cf.rpkm_reader(h5file_in_fn)
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|
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348
|
|
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349 all_calls = []
|
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350
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|
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351 for chr in chrs_to_process:
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|
352 print '[RUNNING] Now processing chr%s' % chr
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353 data = r.getExonValuesByRegion(chr)
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354
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355 #raw_data = copy.copy(data)
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356 _ = data.smooth()
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357
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|
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358 mean= np.mean(data.rpkm,axis=1)
|
|
|
359 sd = np.std(data.rpkm,axis=1)
|
|
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360
|
|
|
361 for sample in r.getSampleList():
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|
362 sample_data = data.getSample([sample]).flatten()
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|
|
363 #sample_raw_data = raw_data.getSample([sample]).flatten()
|
|
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364
|
|
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365 dup_mask = sample_data >= args.threshold
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|
366 del_mask = sample_data <= -1*args.threshold
|
|
|
367
|
|
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368 dup_bkpoints = cf.getbkpoints(dup_mask) #returns exon coordinates for this chromosome (numpy array coords)
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|
|
369 del_bkpoints = cf.getbkpoints(del_mask)
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|
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370
|
|
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371
|
|
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372 dups = []
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|
|
373 for start,stop in dup_bkpoints:
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|
374 try: new_start = np.max(np.where(sample_data[:start] < (mean[:start] + 3*sd[:start])))
|
|
|
375 except ValueError: new_start = 0
|
|
|
376 try: new_stop = stop + np.min(np.where(sample_data[stop:] < (mean[stop:] + 3*sd[stop:])))
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|
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377 except ValueError: new_stop = data.shape[1]-1
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|
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378 dups.append({"sampleID":sample,"chromosome": cf.chrInt2Str(chr), "start":data.exons[new_start]["start"], "stop": data.exons[new_stop]["stop"], "state": "dup"})
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|
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379
|
|
|
380 dels = []
|
|
|
381 for start,stop in del_bkpoints:
|
|
|
382 try: new_start = np.max(np.where(sample_data[:start] > (-1*mean[:start] - 3*sd[:start])))
|
|
|
383 except ValueError: new_start = 0
|
|
|
384 try: new_stop = stop + np.min(np.where(sample_data[stop:] > (-1*mean[stop:] - 3*sd[stop:])))
|
|
|
385 except ValueError: new_stop = data.shape[1]-1
|
|
|
386 dels.append({"sampleID":sample,"chromosome": cf.chrInt2Str(chr), "start":data.exons[new_start]["start"], "stop": data.exons[new_stop]["stop"], "state": "del"})
|
|
|
387
|
|
|
388 dels = cf.mergeCalls(dels) #merges overlapping calls
|
|
|
389 dups = cf.mergeCalls(dups)
|
|
|
390
|
|
|
391 #print sampleID, len(dels), len(dups)
|
|
|
392
|
|
|
393 all_calls.extend(list(dels))
|
|
|
394 all_calls.extend(list(dups))
|
|
|
395
|
|
|
396 # print calls to file
|
|
|
397 header = ['sampleID','chromosome','start','stop','state']
|
|
|
398
|
|
|
399 callfile_f.write('\t'.join(header) + "\n")
|
|
|
400 for call in all_calls:
|
|
|
401 print "%s\t%s\t%d\t%d\t%s" % (call["sampleID"], call["chromosome"], call["start"], call["stop"], call["state"])
|
|
|
402 callfile_f.write("%s\t%s\t%d\t%d\t%s\n" % (call["sampleID"], call["chromosome"], call["start"], call["stop"], call["state"]))
|
|
|
403
|
|
|
404 sys.exit(0)
|
|
|
405
|
|
|
406 def CF_plot(args):
|
|
|
407 try:
|
|
|
408 import locale
|
|
|
409 import matplotlib
|
|
|
410 matplotlib.use('Agg')
|
|
|
411 import matplotlib.pyplot as plt
|
|
|
412 import pylab as P
|
|
|
413 from matplotlib.lines import Line2D
|
|
|
414 from matplotlib.patches import Rectangle
|
|
|
415 _ = locale.setlocale(locale.LC_ALL, '')
|
|
|
416 except:
|
|
|
417 print "[ERROR] One or more of the required modules for plotting cannot be loaded! Are matplotlib and pylab installed?"
|
|
|
418 sys.exit(0)
|
|
|
419
|
|
|
420
|
|
|
421 chr, start, stop = cf.parseLocString(args.region)
|
|
|
422
|
|
|
423 r = cf.rpkm_reader(args.input)
|
|
|
424
|
|
|
425 data = r.getExonValuesByRegion(chr,start,stop)
|
|
|
426 _ = data.smooth()
|
|
|
427
|
|
|
428 plt.gcf().clear()
|
|
|
429 fig = plt.figure(figsize=(10,5))
|
|
|
430 ax = fig.add_subplot(111)
|
|
|
431
|
|
|
432
|
|
|
433 ax.plot(data.rpkm, linewidth = 0.3, c='k')
|
|
|
434
|
|
|
435
|
|
|
436 if args.sample != 'none':
|
|
|
437 cnt = 1
|
|
|
438 coloriter = iter(['r','b','g','y'])
|
|
|
439 for sample in args.sample:
|
|
|
440 try:
|
|
|
441 color, sampleID = sample.split(":")
|
|
|
442 except:
|
|
|
443 color =coloriter.next()
|
|
|
444 sampleID = sample
|
|
|
445
|
|
|
446 ax.plot(data.getSample([sampleID]), linewidth = 1, c=color, label = sampleID)
|
|
|
447
|
|
|
448 if cnt == 1:
|
|
|
449 cf.plotRawData(ax, r.getExonValuesByRegion(chr,start,stop,sampleList=[sampleID]).getSample([sampleID]),color=color)
|
|
|
450 cnt +=1
|
|
|
451 plt.legend(prop={'size':10},frameon=False)
|
|
|
452
|
|
|
453 cf.plotGenes(ax, data)
|
|
|
454 cf.plotGenomicCoords(plt,data)
|
|
|
455 plt.xlim(0,data.shape[1])
|
|
|
456 plt.ylim(-3,3)
|
|
|
457
|
|
|
458 plt.title("%s: %s - %s" % (cf.chrInt2Str(chr),locale.format("%d",start, grouping=True),locale.format("%d",stop, grouping=True)))
|
|
|
459 plt.xlabel("Position")
|
|
|
460 plt.ylabel("SVD-ZRPKM Values")
|
|
|
461
|
|
|
462 plt.savefig(args.output)
|
|
|
463
|
|
|
464 sys.exit(0)
|
|
|
465
|
|
|
466 def CF_plotcalls(args):
|
|
|
467 try:
|
|
|
468 import matplotlib
|
|
|
469 matplotlib.use('Agg')
|
|
|
470 import matplotlib.pyplot as plt
|
|
|
471 import pylab as P
|
|
|
472 from matplotlib.lines import Line2D
|
|
|
473 from matplotlib.patches import Rectangle
|
|
|
474 except:
|
|
|
475 print "[ERROR] One or more of the required modules for plotting cannot be loaded! Are matplotlib and pylab installed?"
|
|
|
476 sys.exit(0)
|
|
|
477
|
|
|
478 import locale
|
|
|
479 try:
|
|
|
480 _ = locale.setlocale(locale.LC_ALL, 'en_US')
|
|
|
481 except:
|
|
|
482 _ = locale.setlocale(locale.LC_ALL, '')
|
|
|
483
|
|
|
484 try:
|
|
|
485 callfile_fn = str(args.calls)
|
|
|
486 callfile_f = open(callfile_fn, mode='r')
|
|
|
487 except IOError as e:
|
|
|
488 print '[ERROR] Cannot open call file for reading: ', callfile_fn
|
|
|
489 sys.exit(0)
|
|
|
490
|
|
|
491 all_calls = []
|
|
|
492 header = callfile_f.readline()
|
|
|
493
|
|
|
494 for line in callfile_f:
|
|
|
495 sampleID, chr, start, stop, state = line.strip().split()
|
|
|
496 chr = cf.chrStr2Int(chr)
|
|
|
497 all_calls.append({"chromosome":int(chr), "start":int(start), "stop":int(stop), "sampleID":sampleID})
|
|
|
498
|
|
|
499 r = cf.rpkm_reader(args.input)
|
|
|
500
|
|
|
501 for call in all_calls:
|
|
|
502 chr = call["chromosome"]
|
|
|
503 start = call["start"]
|
|
|
504 stop = call["stop"]
|
|
|
505 sampleID = call["sampleID"]
|
|
|
506
|
|
|
507 exons = r.getExonIDs(chr,int(start),int(stop))
|
|
|
508
|
|
|
509
|
|
|
510 window_start = max(exons[0]-args.window,0)
|
|
|
511 window_stop = exons[-1]+args.window
|
|
|
512
|
|
|
513 data = r.getExonValuesByExons(chr,window_start, window_stop)
|
|
|
514 _ = data.smooth()
|
|
|
515
|
|
|
516 plt.gcf().clear()
|
|
|
517 fig = plt.figure(figsize=(10,5))
|
|
|
518 ax = fig.add_subplot(111)
|
|
|
519
|
|
|
520
|
|
|
521 ax.plot(data.rpkm, linewidth = 0.3, c='k')
|
|
|
522
|
|
|
523
|
|
|
524 ax.plot(data.getSample([sampleID]), linewidth = 1, c='r', label = sampleID)
|
|
|
525 cf.plotRawData(ax, r.getExonValuesByExons(chr,window_start, window_stop,sampleList=[sampleID]).getSample([sampleID]),color='r')
|
|
|
526
|
|
|
527 plt.legend(prop={'size':10},frameon=False)
|
|
|
528
|
|
|
529 cf.plotGenes(ax, data)
|
|
|
530 cf.plotGenomicCoords(plt,data)
|
|
|
531
|
|
|
532 exon_start = np.where(data.exons["start"] == start)[0][0]
|
|
|
533 exon_stop = np.where(data.exons["stop"] == stop)[0][0]
|
|
|
534 _ = ax.add_line(matplotlib.lines.Line2D([exon_start,exon_stop],[2,2],color='k',lw=6,linestyle='-',alpha=1,solid_capstyle='butt'))
|
|
|
535
|
|
|
536 _ = plt.xlim(0,data.shape[1])
|
|
|
537 _ = plt.ylim(-3,3)
|
|
|
538
|
|
|
539 plt.title("%s: %s - %s" % (cf.chrInt2Str(chr),locale.format("%d",start, grouping=True),locale.format("%d",stop, grouping=True)))
|
|
|
540 plt.xlabel("Position")
|
|
|
541 plt.ylabel("SVD-ZRPKM Values")
|
|
|
542 outfile = "%s_%d_%d_%s.png" % (cf.chrInt2Str(chr), start, stop, sampleID)
|
|
|
543 plt.savefig(args.outputdir + "/" + outfile)
|
|
|
544
|
|
|
545 def CF_bam2RPKM(args):
|
|
|
546 try:
|
|
|
547 import pysam
|
|
|
548 except:
|
|
|
549 print '[ERROR] Cannot load pysam module! Make sure it is insalled'
|
|
|
550 sys.exit(0)
|
|
|
551 try:
|
|
|
552 # read probes table
|
|
|
553 probe_fn = str(args.probes[0])
|
|
|
554 probes = cf.loadProbeList(probe_fn)
|
|
|
555 num_probes = len(probes)
|
|
|
556 print '[INIT] Successfully read in %d probes from %s' % (num_probes, probe_fn)
|
|
|
557 except IOError as e:
|
|
|
558 print '[ERROR] Cannot read probes file: ', probe_fn
|
|
|
559 sys.exit(0)
|
|
|
560
|
|
|
561 try:
|
|
|
562 rpkm_f = open(args.output[0],'w')
|
|
|
563 except IOError as e:
|
|
|
564 print '[ERROR] Cannot open rpkm file for writing: ', args.output
|
|
|
565 sys.exit(0)
|
|
|
566
|
|
|
567 print "[RUNNING] Counting total number of reads in bam file..."
|
|
|
568 total_reads = float(pysam.view("-c", args.input[0])[0].strip("\n"))
|
|
|
569 print "[RUNNING] Found %d reads" % total_reads
|
|
|
570
|
|
|
571 f = pysam.Samfile(args.input[0], "rb" )
|
|
|
572
|
|
|
573 # if not f._hasIndex():
|
|
|
574 if not f.has_index():
|
|
|
575 print "[ERROR] No index found for bam file (%s)!\n[ERROR] You must first index the bam file and include the .bai file in the same directory as the bam file!" % args.input[0]
|
|
|
576 sys.exit(0)
|
|
|
577
|
|
|
578 # will be storing values in these arrays
|
|
|
579 readcount = np.zeros(num_probes)
|
|
|
580 exon_bp = np.zeros(num_probes)
|
|
|
581 probeIDs = np.zeros(num_probes)
|
|
|
582 counter = 0
|
|
|
583
|
|
|
584 # detect contig naming scheme here # TODO, add an optional "contigs.txt" file or automatically handle contig naming
|
|
|
585 bam_contigs = f.references
|
|
|
586 probes_contigs = [str(p) for p in set(map(operator.itemgetter("chr"),probes))]
|
|
|
587
|
|
|
588 probes2contigmap = {}
|
|
|
589
|
|
|
590 for probes_contig in probes_contigs:
|
|
|
591 if probes_contig in bam_contigs:
|
|
|
592 probes2contigmap[probes_contig] = probes_contig
|
|
|
593 elif cf.chrInt2Str(probes_contig) in bam_contigs:
|
|
|
594 probes2contigmap[probes_contig] = cf.chrInt2Str(probes_contig)
|
|
|
595 elif cf.chrInt2Str(probes_contig).replace("chr","") in bam_contigs:
|
|
|
596 probes2contigmap[probes_contig] = cf.chrInt2Str(probes_contig).replace("chr","")
|
|
|
597 else:
|
|
|
598 print "[ERROR] Could not find contig '%s' from %s in bam file! \n[ERROR] Perhaps the contig names for the probes are incompatible with the bam file ('chr1' vs. '1'), or unsupported contig naming is used?" % (probes_contig, probe_fn)
|
|
|
599 sys.exit(0)
|
|
|
600
|
|
|
601 print "[RUNNING] Calculating RPKM values..."
|
|
|
602
|
|
|
603 # loop through each probe
|
|
|
604 for p in probes:
|
|
|
605
|
|
|
606 # f.fetch is a pysam method and returns an iterator for reads overlapping interval
|
|
|
607
|
|
|
608 p_chr = probes2contigmap[str(p["chr"])]
|
|
|
609
|
|
|
610 p_start = p["start"]
|
|
|
611 p_stop = p["stop"]
|
|
|
612 try:
|
|
|
613 iter = f.fetch(p_chr,p_start,p_stop)
|
|
|
614 except:
|
|
|
615 print "[ERROR] Could not retrieve mappings for region %s:%d-%d. Check that contigs are named correctly and the bam file is properly indexed" % (p_chr,p_start,p_stop)
|
|
|
616 sys.exit(0)
|
|
|
617
|
|
|
618 for i in iter:
|
|
|
619 if i.pos+1 >= p_start: #this checks to make sure a read actually starts in an interval
|
|
|
620 readcount[counter] += 1
|
|
|
621
|
|
|
622 exon_bp[counter] = p_stop-p_start
|
|
|
623 probeIDs[counter] = counter +1 #probeIDs are 1-based
|
|
|
624 counter +=1
|
|
|
625
|
|
|
626 #calcualte RPKM values for all probes
|
|
|
627 rpkm = (10**9*(readcount)/(exon_bp))/(total_reads)
|
|
|
628
|
|
|
629 out = np.vstack([probeIDs,readcount,rpkm])
|
|
|
630
|
|
|
631 np.savetxt(rpkm_f,out.transpose(),delimiter='\t',fmt=['%d','%d','%f'])
|
|
|
632
|
|
|
633 rpkm_f.close()
|
|
|
634
|
|
|
635
|
|
|
636
|
|
|
637 VERSION = "0.2.2"
|
|
|
638 parser = argparse.ArgumentParser(prog="CoNIFER", description="This is CoNIFER %s (Copy Number Inference From Exome Reads), designed to detect and genotype CNVs and CNPs from exome sequence read-depth data. See Krumm et al., Genome Research (2012) doi:10.1101/gr.138115.112 \nNiklas Krumm, 2012\n nkrumm@uw.edu" % VERSION)
|
|
|
639 parser.add_argument('--version', action='version', version='%(prog)s ' + VERSION)
|
|
|
640 subparsers = parser.add_subparsers(help='Command to be run.')
|
|
|
641
|
|
|
642 # rpkm command
|
|
|
643 rpkm_parser= subparsers.add_parser('rpkm', help='Create an RPKM file from a BAM file')
|
|
|
644 rpkm_parser.add_argument('--probes',action='store', required=True, metavar='/path/to/probes_file.txt', nargs=1,help="Probe definition file")
|
|
|
645 rpkm_parser.add_argument('--input',action='store', required=True, metavar='sample.bam',nargs=1, help="Aligned BAM file")
|
|
|
646 rpkm_parser.add_argument('--output',action='store', required=True, metavar='sample.rpkm.txt',nargs=1, help="RPKM file to write")
|
|
|
647 rpkm_parser.set_defaults(func=CF_bam2RPKM)
|
|
|
648
|
|
|
649 # analyze command
|
|
|
650 analyze_parser= subparsers.add_parser('analyze', help='Basic CoNIFER analysis. Reads a directory of RPKM files and a probe list and outputs a HDF5 file containing SVD-ZRPKM values.')
|
|
|
651 analyze_parser.add_argument('--probes',action='store', required=True, metavar='/path/to/probes_file.txt', nargs=1,help="Probe definition file")
|
|
|
652 analyze_parser.add_argument('--rpkm_dir',action='store', required=True, metavar='/path/to/folder/containing/rpkm_files/',nargs=1, help="Location of folder containing RPKM files. Folder should contain ONLY contain RPKM files, and all readable RPKM files will used in analysis.")
|
|
|
653 analyze_parser.add_argument('--output','-o', required=True, metavar='/path/to/output_file.hdf5', type=str, help="Output location of HDF5 file to contain SVD-ZRPKM values")
|
|
|
654 analyze_parser.add_argument('--svd', metavar='12', type=int, nargs='?', default = 12,help="Number of components to remove")
|
|
|
655 analyze_parser.add_argument('--min_rpkm', metavar='1.00', type=float, nargs="?", default = 1.00,help="Minimum population median RPKM per probe.")
|
|
|
656 analyze_parser.add_argument('--write_svals', metavar='SingularValues.txt', type=str, default= "", help="Optional file to write singular values (S-values). Used for Scree Plot.")
|
|
|
657 analyze_parser.add_argument('--plot_scree', metavar='ScreePlot.png', type=str, default= "", help="Optional graphical scree plot. Requires matplotlib.")
|
|
|
658 analyze_parser.add_argument('--write_sd', metavar='StandardDeviations.txt', type=str, default= "", help="Optional file with sample SVD-ZRPKM standard deviations. Used to filter noisy samples.")
|
|
|
659 analyze_parser.set_defaults(func=CF_analyze)
|
|
|
660
|
|
|
661 # export command
|
|
|
662 export_parser= subparsers.add_parser('export', help='Export SVD-ZRPKM values from a HDF5 file to bed or vcf format.')
|
|
|
663 export_parser.add_argument('--input','-i',action='store', required=True, metavar='CoNIFER_SVD.hdf5',help="HDF5 file from CoNIFER 'analyze' step")
|
|
|
664 export_parser.add_argument('--output','-o',action='store', required=False, default='.', metavar='output.bed',help="Location of output file[s]. When exporting multiple samples, top-level directory of this path will be used.")
|
|
|
665 export_parser.add_argument('--sample','-s',action='store', required=False, metavar='sampleID', default='all', nargs="+",help="SampleID or comma-separated list of sampleIDs to export. Default: export all samples")
|
|
|
666 export_parser.set_defaults(func=CF_export)
|
|
|
667
|
|
|
668 # plot command
|
|
|
669 plot_parser= subparsers.add_parser('plot', help='Plot SVD-ZRPKM values using matplotlib')
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670 plot_parser.add_argument('--input','-i',action='store', required=True, metavar='CoNIFER_SVD.hdf5',help="HDF5 file from CoNIFER 'analyze' step")
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671 plot_parser.add_argument('--region',action='store', required=True, metavar='chr#:start-stop',help="Region to plot")
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672 plot_parser.add_argument('--output',action='store', required=True, metavar='image.png',help="Output path and filetype. PDF, PNG, PS, EPS, and SVG are supported.")
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673 plot_parser.add_argument('--sample',action='store', required=False, metavar='sampleID',nargs="+",default='none',help="Sample[s] to highlight. The following optional color spec can be used: <color>:<sampleID>. Available colors are r,b,g,y,c,m,y,k. The unsmoothed SVD-ZRPKM values for the first sample in this list will be drawn. Default: No samples highlighted.")
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674 plot_parser.set_defaults(func=CF_plot)
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675
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676 # make calls command
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677 call_parser= subparsers.add_parser('call', help='Very rudimentary caller for CNVs using SVD-ZRPKM thresholding.')
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678 call_parser.add_argument('--input','-i',action='store', required=True, metavar='CoNIFER_SVD.hdf5',help="HDF5 file from CoNIFER 'analyze' step")
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679 call_parser.add_argument('--output',action='store', required=True, metavar='calls.txt',help="Output file for calls")
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680 call_parser.add_argument('--threshold', metavar='1.50', type=float, nargs='?', required=False, default = 1.50,help="+/- Threshold for calling (minimum SVD-ZRPKM)")
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681 call_parser.set_defaults(func=CF_call)
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682
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683 # plotcalls command
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684 plotcalls_parser= subparsers.add_parser('plotcalls', help='Make basic plots from call file from "call" command.')
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685 plotcalls_parser.add_argument('--input','-i',action='store', required=True, metavar='CoNIFER_SVD.hdf5',help="HDF5 file from CoNIFER 'analyze' step")
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686 plotcalls_parser.add_argument('--calls',action='store', required=True, metavar='calls.txt',help="File with calls from 'call' command.")
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687 plotcalls_parser.add_argument('--outputdir',action='store', required=True, metavar='/path/to/directory',help="Output directory for plots")
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688 plotcalls_parser.add_argument('--window',action='store', required=False, metavar='50',default=50,help="In exons, the amount of padding to plot around each call")
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689 plotcalls_parser.set_defaults(func=CF_plotcalls)
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690
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691 args = parser.parse_args()
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692 args.func(args)
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