1 | #!/usr/bin/env python |
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2 | #Guruprasad Ananda |
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3 | """ |
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4 | Filter based on nucleotide quality (PHRED score). |
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5 | |
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6 | usage: %prog input out_file primary_species mask_species score mask_char mask_region mask_region_length |
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7 | """ |
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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("numpy") |
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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 | from bx.binned_array import BinnedArray, FileBinnedArray |
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25 | from bx.bitset import * |
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26 | from bx.bitset_builders import * |
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27 | from fpconst import isNaN |
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28 | from bx.cookbook import doc_optparse |
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29 | from galaxy.tools.exception_handling import * |
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30 | import bx.align.maf |
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31 | |
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32 | class FileBinnedArrayDir( DictMixin ): |
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33 | """ |
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34 | Adapter that makes a directory of FileBinnedArray files look like |
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35 | a regular dict of BinnedArray objects. |
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36 | """ |
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37 | def __init__( self, dir ): |
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38 | self.dir = dir |
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39 | self.cache = dict() |
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40 | def __getitem__( self, key ): |
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41 | value = None |
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42 | if key in self.cache: |
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43 | value = self.cache[key] |
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44 | else: |
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45 | fname = os.path.join( self.dir, "%s.qa.bqv" % key ) |
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46 | if os.path.exists( fname ): |
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47 | value = FileBinnedArray( open( fname ) ) |
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48 | self.cache[key] = value |
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49 | if value is None: |
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50 | raise KeyError( "File does not exist: " + fname ) |
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51 | return value |
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52 | |
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53 | def stop_err(msg): |
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54 | sys.stderr.write(msg) |
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55 | sys.exit() |
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56 | |
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57 | def load_scores_ba_dir( dir ): |
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58 | """ |
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59 | Return a dict-like object (keyed by chromosome) that returns |
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60 | FileBinnedArray objects created from "key.ba" files in `dir` |
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61 | """ |
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62 | return FileBinnedArrayDir( dir ) |
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63 | |
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64 | def bitwise_and ( string1, string2, maskch ): |
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65 | result=[] |
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66 | for i,ch in enumerate(string1): |
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67 | try: |
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68 | ch = int(ch) |
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69 | except: |
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70 | pass |
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71 | if string2[i] == '-': |
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72 | ch = 1 |
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73 | if ch and string2[i]: |
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74 | result.append(string2[i]) |
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75 | else: |
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76 | result.append(maskch) |
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77 | return ''.join(result) |
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78 | |
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79 | def main(): |
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80 | # Parsing Command Line here |
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81 | options, args = doc_optparse.parse( __doc__ ) |
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82 | |
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83 | try: |
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84 | #chr_col_1, start_col_1, end_col_1, strand_col_1 = parse_cols_arg( options.cols ) |
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85 | inp_file, out_file, pri_species, mask_species, qual_cutoff, mask_chr, mask_region, mask_length, loc_file = args |
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86 | qual_cutoff = int(qual_cutoff) |
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87 | mask_chr = int(mask_chr) |
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88 | mask_region = int(mask_region) |
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89 | if mask_region != 3: |
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90 | mask_length = int(mask_length) |
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91 | else: |
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92 | mask_length_r = int(mask_length.split(',')[0]) |
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93 | mask_length_l = int(mask_length.split(',')[1]) |
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94 | except: |
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95 | stop_err( "Data issue, click the pencil icon in the history item to correct the metadata attributes of the input dataset." ) |
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96 | |
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97 | if pri_species == 'None': |
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98 | stop_err( "No primary species selected, try again by selecting at least one primary species." ) |
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99 | if mask_species == 'None': |
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100 | stop_err( "No mask species selected, try again by selecting at least one species to mask." ) |
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101 | |
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102 | mask_chr_count = 0 |
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103 | mask_chr_dict = {0:'#', 1:'$', 2:'^', 3:'*', 4:'?', 5:'N'} |
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104 | mask_reg_dict = {0:'Current pos', 1:'Current+Downstream', 2:'Current+Upstream', 3:'Current+Both sides'} |
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105 | |
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106 | #ensure dbkey is present in the twobit loc file |
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107 | filepath = None |
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108 | try: |
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109 | pspecies_all = pri_species.split(',') |
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110 | pspecies_all2 = pri_species.split(',') |
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111 | pspecies = [] |
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112 | filepaths = [] |
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113 | for line in open(loc_file): |
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114 | if pspecies_all2 == []: |
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115 | break |
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116 | if line[0:1] == "#": |
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117 | continue |
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118 | fields = line.split('\t') |
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119 | try: |
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120 | build = fields[0] |
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121 | for i,dbkey in enumerate(pspecies_all2): |
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122 | if dbkey == build: |
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123 | pspecies.append(build) |
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124 | filepaths.append(fields[1]) |
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125 | del pspecies_all2[i] |
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126 | else: |
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127 | continue |
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128 | except: |
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129 | pass |
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130 | except Exception, exc: |
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131 | stop_err( 'Initialization errorL %s' % str( exc ) ) |
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132 | |
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133 | if len(pspecies) == 0: |
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134 | stop_err( "Quality scores are not available for the following genome builds: %s" % ( pspecies_all2 ) ) |
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135 | if len(pspecies) < len(pspecies_all): |
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136 | print "Quality scores are not available for the following genome builds: %s" %(pspecies_all2) |
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137 | |
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138 | scores_by_chrom = [] |
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139 | #Get scores for all the primary species |
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140 | for file in filepaths: |
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141 | scores_by_chrom.append(load_scores_ba_dir( file.strip() )) |
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142 | |
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143 | try: |
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144 | maf_reader = bx.align.maf.Reader( open(inp_file, 'r') ) |
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145 | maf_writer = bx.align.maf.Writer( open(out_file,'w') ) |
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146 | except Exception, e: |
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147 | stop_err( "Your MAF file appears to be malformed: %s" % str( e ) ) |
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148 | |
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149 | maf_count = 0 |
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150 | for block in maf_reader: |
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151 | status_strings = [] |
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152 | for seq in range (len(block.components)): |
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153 | src = block.components[seq].src |
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154 | dbkey = src.split('.')[0] |
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155 | chr = src.split('.')[1] |
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156 | if not (dbkey in pspecies): |
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157 | continue |
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158 | else: #enter if the species is a primary species |
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159 | index = pspecies.index(dbkey) |
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160 | sequence = block.components[seq].text |
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161 | s_start = block.components[seq].start |
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162 | size = len(sequence) #this includes the gaps too |
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163 | status_str = '1'*size |
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164 | status_list = list(status_str) |
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165 | if status_strings == []: |
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166 | status_strings.append(status_str) |
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167 | ind = 0 |
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168 | s_end = block.components[seq].end |
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169 | #Get scores for the entire sequence |
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170 | try: |
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171 | scores = scores_by_chrom[index][chr][s_start:s_end] |
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172 | except: |
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173 | continue |
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174 | pos = 0 |
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175 | while pos < (s_end-s_start): |
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176 | if sequence[ind] == '-': #No score for GAPS |
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177 | ind += 1 |
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178 | continue |
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179 | score = scores[pos] |
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180 | if score < qual_cutoff: |
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181 | score = 0 |
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182 | |
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183 | if not(score): |
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184 | if mask_region == 0: #Mask Corresponding position only |
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185 | status_list[ind] = '0' |
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186 | ind += 1 |
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187 | pos += 1 |
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188 | elif mask_region == 1: #Mask Corresponding position + downstream neighbors |
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189 | for n in range(mask_length+1): |
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190 | try: |
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191 | status_list[ind+n] = '0' |
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192 | except: |
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193 | pass |
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194 | ind = ind + mask_length + 1 |
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195 | pos = pos + mask_length + 1 |
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196 | elif mask_region == 2: #Mask Corresponding position + upstream neighbors |
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197 | for n in range(mask_length+1): |
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198 | try: |
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199 | status_list[ind-n] = '0' |
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200 | except: |
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201 | pass |
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202 | ind += 1 |
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203 | pos += 1 |
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204 | elif mask_region == 3: #Mask Corresponding position + neighbors on both sides |
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205 | for n in range(-mask_length_l,mask_length_r+1): |
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206 | try: |
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207 | status_list[ind+n] = '0' |
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208 | except: |
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209 | pass |
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210 | ind = ind + mask_length_r + 1 |
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211 | pos = pos + mask_length_r + 1 |
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212 | else: |
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213 | pos += 1 |
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214 | ind += 1 |
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215 | |
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216 | status_strings.append(''.join(status_list)) |
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217 | |
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218 | if status_strings == []: #this block has no primary species |
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219 | continue |
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220 | output_status_str = status_strings[0] |
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221 | for stat in status_strings[1:]: |
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222 | try: |
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223 | output_status_str = bitwise_and (status_strings[0], stat, '0') |
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224 | except Exception, e: |
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225 | break |
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226 | |
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227 | for seq in range (len(block.components)): |
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228 | src = block.components[seq].src |
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229 | dbkey = src.split('.')[0] |
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230 | if dbkey not in mask_species.split(','): |
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231 | continue |
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232 | sequence = block.components[seq].text |
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233 | sequence = bitwise_and (output_status_str, sequence, mask_chr_dict[mask_chr]) |
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234 | block.components[seq].text = sequence |
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235 | mask_chr_count += output_status_str.count('0') |
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236 | maf_writer.write(block) |
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237 | maf_count += 1 |
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238 | |
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239 | maf_reader.close() |
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240 | maf_writer.close() |
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241 | print "No. of blocks = %d; No. of masked nucleotides = %s; Mask character = %s; Mask region = %s; Cutoff used = %d" %(maf_count, mask_chr_count, mask_chr_dict[mask_chr], mask_reg_dict[mask_region], qual_cutoff) |
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242 | |
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243 | |
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244 | if __name__ == "__main__": |
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245 | main() |
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