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