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1 #!/usr/bin/env python
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2 # Greg Von Kuster
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3 """
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4 usage: %prog score_file interval_file chrom start stop [out_file] [options]
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5 -b, --binned: 'score_file' is actually a directory of binned array files
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6 -m, --mask=FILE: bed file containing regions not to consider valid
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7 -c, --chrom_buffer=INT: number of chromosomes (default is 3) to keep in memory when using a user supplied score file
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8 """
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9
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10 from __future__ import division
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11 from galaxy import eggs
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12 import pkg_resources
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13 pkg_resources.require( "bx-python" )
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14 pkg_resources.require( "lrucache" )
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15 try:
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16 pkg_resources.require( "python-lzo" )
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17 except:
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18 pass
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19
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20 import psyco_full
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21 import sys
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22 import os, os.path
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23 from UserDict import DictMixin
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24 import bx.wiggle
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25 from bx.binned_array import BinnedArray, FileBinnedArray
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26 from bx.bitset import *
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27 from bx.bitset_builders import *
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28 from fpconst import isNaN
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29 from bx.cookbook import doc_optparse
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30 from galaxy.tools.exception_handling import *
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31
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32 assert sys.version_info[:2] >= ( 2, 4 )
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33
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34 import tempfile, struct
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35 class PositionalScoresOnDisk:
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36 fmt = 'f'
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37 fmt_size = struct.calcsize( fmt )
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38 default_value = float( 'nan' )
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39
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40 def __init__( self ):
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41 self.file = tempfile.TemporaryFile( 'w+b' )
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42 self.length = 0
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43 def __getitem__( self, i ):
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44 if i < 0: i = self.length + i
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45 if i < 0 or i >= self.length: return self.default_value
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46 try:
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47 self.file.seek( i * self.fmt_size )
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48 return struct.unpack( self.fmt, self.file.read( self.fmt_size ) )[0]
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49 except Exception, e:
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50 raise IndexError, e
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51 def __setitem__( self, i, value ):
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52 if i < 0: i = self.length + i
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53 if i < 0: raise IndexError, 'Negative assignment index out of range'
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54 if i >= self.length:
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55 self.file.seek( self.length * self.fmt_size )
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56 self.file.write( struct.pack( self.fmt, self.default_value ) * ( i - self.length ) )
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57 self.length = i + 1
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58 self.file.seek( i * self.fmt_size )
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59 self.file.write( struct.pack( self.fmt, value ) )
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60 def __len__( self ):
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61 return self.length
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62 def __repr__( self ):
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63 i = 0
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64 repr = "[ "
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65 for i in xrange( self.length ):
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66 repr = "%s %s," % ( repr, self[i] )
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67 return "%s ]" % ( repr )
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68
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69 class FileBinnedArrayDir( DictMixin ):
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70 """
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71 Adapter that makes a directory of FileBinnedArray files look like
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72 a regular dict of BinnedArray objects.
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73 """
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74 def __init__( self, dir ):
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75 self.dir = dir
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76 self.cache = dict()
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77 def __getitem__( self, key ):
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78 value = None
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79 if key in self.cache:
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80 value = self.cache[key]
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81 else:
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82 fname = os.path.join( self.dir, "%s.ba" % key )
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83 if os.path.exists( fname ):
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84 value = FileBinnedArray( open( fname ) )
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85 self.cache[key] = value
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86 if value is None:
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87 raise KeyError( "File does not exist: " + fname )
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88 return value
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89
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90 def stop_err(msg):
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91 sys.stderr.write(msg)
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92 sys.exit()
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93
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94 def load_scores_wiggle( fname, chrom_buffer_size = 3 ):
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95 """
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96 Read a wiggle file and return a dict of BinnedArray objects keyed
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97 by chromosome.
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98 """
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99 scores_by_chrom = dict()
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100 try:
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101 for chrom, pos, val in bx.wiggle.Reader( UCSCOutWrapper( open( fname ) ) ):
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102 if chrom not in scores_by_chrom:
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103 if chrom_buffer_size:
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104 scores_by_chrom[chrom] = BinnedArray()
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105 chrom_buffer_size -= 1
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106 else:
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107 scores_by_chrom[chrom] = PositionalScoresOnDisk()
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108 scores_by_chrom[chrom][pos] = val
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109 except UCSCLimitException:
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110 # Wiggle data was truncated, at the very least need to warn the user.
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111 print 'Encountered message from UCSC: "Reached output limit of 100000 data values", so be aware your data was truncated.'
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112 except IndexError:
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113 stop_err('Data error: one or more column data values is missing in "%s"' %fname)
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114 except ValueError:
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115 stop_err('Data error: invalid data type for one or more values in "%s".' %fname)
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116 return scores_by_chrom
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117
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118 def load_scores_ba_dir( dir ):
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119 """
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120 Return a dict-like object (keyed by chromosome) that returns
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121 FileBinnedArray objects created from "key.ba" files in `dir`
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122 """
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123 return FileBinnedArrayDir( dir )
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124
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125 def main():
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126
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127 # Parse command line
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128 options, args = doc_optparse.parse( __doc__ )
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129
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130 try:
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131 score_fname = args[0]
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132 interval_fname = args[1]
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133 chrom_col = args[2]
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134 start_col = args[3]
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135 stop_col = args[4]
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136 if len( args ) > 5:
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137 out_file = open( args[5], 'w' )
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138 else:
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139 out_file = sys.stdout
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140 binned = bool( options.binned )
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141 mask_fname = options.mask
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142 except:
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143 doc_optparse.exit()
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144
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145 if score_fname == 'None':
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146 stop_err( 'This tool works with data from genome builds hg16, hg17 or hg18. Click the pencil icon in your history item to set the genome build if appropriate.' )
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147
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148 try:
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149 chrom_col = int(chrom_col) - 1
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150 start_col = int(start_col) - 1
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151 stop_col = int(stop_col) - 1
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152 except:
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153 stop_err( 'Chrom, start & end column not properly set, click the pencil icon in your history item to set these values.' )
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154
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155 if chrom_col < 0 or start_col < 0 or stop_col < 0:
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156 stop_err( 'Chrom, start & end column not properly set, click the pencil icon in your history item to set these values.' )
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157
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158 if binned:
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159 scores_by_chrom = load_scores_ba_dir( score_fname )
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160 else:
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161 try:
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162 chrom_buffer = int( options.chrom_buffer )
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163 except:
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164 chrom_buffer = 3
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165 scores_by_chrom = load_scores_wiggle( score_fname, chrom_buffer )
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166
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167 if mask_fname:
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168 masks = binned_bitsets_from_file( open( mask_fname ) )
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169 else:
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170 masks = None
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171
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172 skipped_lines = 0
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173 first_invalid_line = 0
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174 invalid_line = ''
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175
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176 for i, line in enumerate( open( interval_fname )):
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177 valid = True
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178 line = line.rstrip('\r\n')
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179 if line and not line.startswith( '#' ):
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180 fields = line.split()
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181
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182 try:
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183 chrom, start, stop = fields[chrom_col], int( fields[start_col] ), int( fields[stop_col] )
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184 except:
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185 valid = False
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186 skipped_lines += 1
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187 if not invalid_line:
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188 first_invalid_line = i + 1
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189 invalid_line = line
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190 if valid:
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191 total = 0
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192 count = 0
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193 min_score = 100000000
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194 max_score = -100000000
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195 for j in range( start, stop ):
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196 if chrom in scores_by_chrom:
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197 try:
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198 # Skip if base is masked
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199 if masks and chrom in masks:
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200 if masks[chrom][j]:
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201 continue
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202 # Get the score, only count if not 'nan'
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203 score = scores_by_chrom[chrom][j]
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204 if not isNaN( score ):
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205 total += score
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206 count += 1
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207 max_score = max( score, max_score )
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208 min_score = min( score, min_score )
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209 except:
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210 continue
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211 if count > 0:
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212 avg = total/count
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213 else:
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214 avg = "nan"
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215 min_score = "nan"
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216 max_score = "nan"
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217
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218 # Build the resulting line of data
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219 out_line = []
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220 for k in range(0, len(fields)):
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221 out_line.append(fields[k])
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222 out_line.append(avg)
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223 out_line.append(min_score)
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224 out_line.append(max_score)
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225
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226 print >> out_file, "\t".join( map( str, out_line ) )
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227 else:
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228 skipped_lines += 1
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229 if not invalid_line:
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230 first_invalid_line = i + 1
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231 invalid_line = line
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232 elif line.startswith( '#' ):
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233 # We'll save the original comments
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234 print >> out_file, line
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235
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236 out_file.close()
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237
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238 if skipped_lines > 0:
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239 print 'Data issue: skipped %d invalid lines starting at line #%d which is "%s"' % ( skipped_lines, first_invalid_line, invalid_line )
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240 if skipped_lines == i:
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241 print 'Consider changing the metadata for the input dataset by clicking on the pencil icon in the history item.'
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242
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243 if __name__ == "__main__": main()
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