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1 #!/usr/bin/env python
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2
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3 """
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4 count.py -- Take SAM files and output a table of counts with column
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5 names that are the filenames, and rowname that are the reference
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6 names.
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7
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8 Author: Vince Buffalo
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9 Email: vsbuffaloAAAAA@gmail.com (with poly-A tail removed)
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10 """
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11
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12 VERSION = 0.91
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13
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14 import sys
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15 import csv
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16 from os import path
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17 try:
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18 import pysam
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19 except ImportError:
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20 sys.exit("pysam not installed; please install it\n")
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21
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22 from optparse import OptionParser
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23
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24 def SAM_file_to_counts(filename, bam=False, extra=False, use_all_references=True):
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25 """
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26 Take SAM filename, and create a hash of mapped and unmapped reads;
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27 keys are reference sequences, values are the counts of occurences.
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28
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29 Also, a hash of qualities (either 0 or >0) of mapped reads
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30 is output, which is handy for diagnostics.
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31 """
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32 counts = dict()
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33 unique = dict()
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34 nonunique = dict()
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35 mode = 'r'
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36 if bam:
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37 mode = 'rb'
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38 sf = pysam.Samfile(filename, mode)
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39
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40 if use_all_references:
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41 # Make dictionary of all entries in header
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42 for sn in sf.header['SQ']:
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43 if extra:
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44 unique[sn['SN']] = 0
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45 nonunique[sn['SN']] = 0
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46 counts[sn['SN']] = 0
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47
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48 for read in sf:
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49 if not read.is_unmapped:
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50 id_name = sf.getrname(read.rname) if read.rname != -1 else 0
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51
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52 if not use_all_references and not counts.get(id_name, False):
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53 ## Only make keys based on aligning reads, make empty hash
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54 if extra:
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55 unique[id_name] = 0
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56 nonunique[id_name] = 0
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57 ## initiate entry; even if not mapped, record 0 count
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58 counts[id_name] = counts.get(id_name, 0)
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59
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60
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61 counts[id_name] = counts.get(id_name, 0) + 1
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62
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63 if extra:
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64 if read.mapq == 0:
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65 nonunique[id_name] = nonunique[id_name] + 1
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66 else:
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67 unique[id_name] = unique[id_name] + 1
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68
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69 if extra:
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70 return {'counts':counts, 'unique':unique, 'nonunique':nonunique}
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71
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72 return {'counts':counts}
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73
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74 def collapsed_nested_count_dict(counts_dict, all_ids, order=None):
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75 """
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76 Takes a nested dictionary `counts_dict` and `all_ids`, which is
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77 built with the `table_dict`. All files (first keys) in
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78 `counts_dict` are made into columns with order specified by
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79 `order`.
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80
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81 Output is a dictionary with keys that are the id's (genes or
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82 transcripts), with values that are ordered counts. A header will
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83 be created on the first row from the ordered columns (extracted
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84 from filenames).
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85 """
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86 if order is None:
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87 col_order = counts_dict.keys()
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88 else:
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89 col_order = order
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90
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91 collapsed_dict = dict()
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92 for i, filename in enumerate(col_order):
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93 for id_name in all_ids:
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94 if not collapsed_dict.get(id_name, False):
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95 collapsed_dict[id_name] = list()
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96
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97 # get counts and append
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98 c = counts_dict[filename].get(id_name, 0)
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99 collapsed_dict[id_name].append(c)
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100 return {'table':collapsed_dict, 'header':col_order}
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101
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102
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103 def counts_to_file(table_dict, outfilename, delimiter=',', labels=''):
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104 """
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105 A function for its side-effect of writing `table_dict` (which
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106 contains a table and header), to `outfilename` with the specified
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107 `delimiter`.
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108 """
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109 writer = csv.writer(open(outfilename, 'w'), delimiter=delimiter)
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110 table = table_dict['table']
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111 if labels:
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112 header = labels.split(',')
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113 else:
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114 header = table_dict['header']
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115
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116 header_row = True
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117 for id_name, fields in table.items():
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118 if header_row:
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119 row = ['id'] + header
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120 writer.writerow(row)
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121 header_row = False
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122
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123 if id_name == 0:
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124 continue
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125 row = [id_name]
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126 row.extend(fields)
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127 writer.writerow(row)
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128
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129 if __name__ == '__main__':
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130 parser = OptionParser()
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131 parser.add_option("-d", "--delimiter", dest="delimiter",
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132 help="the delimiter (default: tab)", default='\t')
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133 parser.add_option("-o", "--out-file", dest="out_file",
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134 help="output filename (default: counts.txt)",
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135 default='counts.txt', action="store", type="string")
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136 parser.add_option("-u", "--extra-output", dest="extra_out",
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137 help="output extra information on non-unique and unique mappers (default: False)",
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138 default=False, action="store_true")
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139 parser.add_option("-b", "--bam", dest="bam",
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140 help="all input files are BAM (default: False)",
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141 default=False, action="store_true")
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142 parser.add_option("-r", "--use-all-references", dest="use_all_references",
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143 help="Use all the references from the SAM header (default: True)",
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144 default=True, action="store_false")
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145 parser.add_option("-f", "--extra-out-files", dest="extra_out_files",
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146 help="comma-delimited filenames of unique and non-unique output "
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147 "(default: unique.txt,nonunique.txt)",
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148 default='unique.txt,nonunique.txt', action="store", type="string")
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149 parser.add_option("-v", "--verbose", dest="verbose",
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150 help="enable verbose output")
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151 parser.add_option("-l", "--columns-labels", dest="col_labels", help="comma-delimited label names for samples", action="store", type="string")
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152
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153 (options, args) = parser.parse_args()
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154
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155 if len(args) < 1:
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156 parser.error("one or more SAM files as arguments required")
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157
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158 file_counts = dict()
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159 file_unique_counts = dict()
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160 file_nonunique_counts = dict()
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161 all_ids = list()
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162 files = [path.basename(f) for f in args]
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163
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164 if options.col_labels and len(files) != len(options.col_labels.split(',')):
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165 parser.error("Number of sample names does not equal number of files")
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166
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167 if len(set(files)) != len(set(args)):
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168 parser.error("file args must have unique base names (i.e. no foo/bar joo/bar)")
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169
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170 ## do a pre-run check that all files exist
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171 for full_filename in args:
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172 if not path.exists(full_filename):
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173 parser.error("file '%s' does not exist" % full_filename)
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174
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175 for full_filename in args:
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176 filename = path.basename(full_filename)
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177 ## read in SAM file, extract counts, and unpack counts
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178 tmp = SAM_file_to_counts(full_filename, bam=options.bam, extra=options.extra_out,
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179 use_all_references=options.use_all_references)
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180
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181 if options.extra_out:
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182 counts, unique, nonunique = tmp['counts'], tmp['unique'], tmp['nonunique']
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183 else:
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184 counts = tmp['counts']
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185
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186 ## save counts, and unique/non-unique counts
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187 file_counts[filename] = counts
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188
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189 if options.extra_out:
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190 file_unique_counts[filename] = unique
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191 file_nonunique_counts[filename] = nonunique
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192
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193 ## add all ids encountered in this in this file
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194 all_ids.extend(file_counts[filename].keys())
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195
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196 ## Uniquify all_ids, and then take the nested file_counts
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197 ## dictionary, collapse, and write to file.
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198 all_ids = set(all_ids)
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199 table_dict = collapsed_nested_count_dict(file_counts, all_ids, order=files)
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200 counts_to_file(table_dict, options.out_file, delimiter=options.delimiter, labels=options.col_labels)
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201
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202 if options.extra_out:
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203 unique_fn, nonunique_fn = options.extra_out_files.split(',')
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204 unique_table_dict = collapsed_nested_count_dict(file_unique_counts, all_ids, order=files)
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205 nonunique_table_dict = collapsed_nested_count_dict(file_nonunique_counts, all_ids, order=files)
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206
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207 counts_to_file(unique_table_dict, unique_fn, delimiter=options.delimiter)
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208 counts_to_file(nonunique_table_dict, nonunique_fn, delimiter=options.delimiter)
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209
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