1 | #!/usr/bin/env python |
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2 | """ |
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3 | trim reads based on the quality scores |
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4 | input: read file and quality score file |
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5 | output: trimmed read file |
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6 | """ |
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7 | |
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8 | import os, sys, math, tempfile, re |
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9 | |
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10 | assert sys.version_info[:2] >= ( 2, 4 ) |
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11 | |
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12 | def stop_err( msg ): |
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13 | sys.stderr.write( "%s\n" % msg ) |
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14 | sys.exit() |
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15 | |
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16 | def append_to_outfile( outfile_name, seq_title, segments ): |
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17 | segments = segments.split( ',' ) |
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18 | if len( segments ) > 1: |
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19 | outfile = open( outfile_name, 'a' ) |
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20 | for i in range( len( segments ) ): |
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21 | outfile.write( "%s_%d\n%s\n" % ( seq_title, i, segments[i] ) ) |
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22 | outfile.close() |
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23 | elif segments[0]: |
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24 | outfile = open( outfile_name, 'a' ) |
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25 | outfile.write( "%s\n%s\n" % ( seq_title, segments[0] ) ) |
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26 | outfile.close() |
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27 | |
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28 | def trim_seq( seq, score, arg, trim_score, threshold ): |
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29 | seq_method = '454' |
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30 | trim_pos = 0 |
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31 | # trim after a certain position |
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32 | if arg.isdigit(): |
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33 | keep_homopolymers = False |
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34 | trim_pos = int( arg ) |
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35 | if trim_pos > 0 and trim_pos < len( seq ): |
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36 | seq = seq[0:trim_pos] |
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37 | else: |
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38 | keep_homopolymers = arg=='yes' |
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39 | |
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40 | new_trim_seq = '' |
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41 | max_segment = 0 |
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42 | |
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43 | for i in range( len( seq ) ): |
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44 | if i >= len( score ): |
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45 | score.append(-1) |
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46 | if int( score[i] ) >= trim_score: |
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47 | pass_nuc = seq[ i:( i + 1 ) ] |
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48 | else: |
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49 | if keep_homopolymers and ( (i == 0 ) or ( seq[ i:( i + 1 ) ].lower() == seq[ ( i - 1 ):i ].lower() ) ): |
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50 | pass_nuc = seq[ i:( i + 1 ) ] |
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51 | else: |
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52 | pass_nuc = ' ' |
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53 | new_trim_seq = '%s%s' % ( new_trim_seq, pass_nuc ) |
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54 | # find the max substrings |
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55 | segments = new_trim_seq.split() |
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56 | max_segment = '' |
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57 | len_max_segment = 0 |
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58 | if threshold == 0: |
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59 | for seg in segments: |
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60 | if len_max_segment < len( seg ): |
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61 | max_segment = '%s,' % seg |
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62 | len_max_segment = len( seg ) |
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63 | elif len_max_segment == len( seg ): |
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64 | max_segment = '%s%s,' % ( max_segment, seg ) |
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65 | else: |
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66 | for seg in segments: |
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67 | if len( seg ) >= threshold: |
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68 | max_segment = '%s%s,' % ( max_segment, seg ) |
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69 | return max_segment[ 0:-1 ] |
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70 | |
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71 | def __main__(): |
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72 | |
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73 | try: |
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74 | threshold_trim = int( sys.argv[1].strip() ) |
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75 | except: |
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76 | stop_err( "Minimal quality score must be numeric." ) |
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77 | try: |
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78 | threshold_report = int( sys.argv[2].strip() ) |
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79 | except: |
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80 | stop_err( "Minimal length of trimmed reads must be numeric." ) |
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81 | outfile_seq_name = sys.argv[3].strip() |
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82 | infile_seq_name = sys.argv[4].strip() |
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83 | infile_score_name = sys.argv[5].strip() |
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84 | arg = sys.argv[6].strip() |
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85 | |
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86 | seq_infile_name = infile_seq_name |
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87 | score_infile_name = infile_score_name |
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88 | |
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89 | |
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90 | # Determine quailty score format: tabular or fasta format within the first 100 lines |
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91 | seq_method = None |
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92 | data_type = None |
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93 | for i, line in enumerate( file( score_infile_name ) ): |
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94 | line = line.rstrip( '\r\n' ) |
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95 | if not line or line.startswith( '#' ): |
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96 | continue |
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97 | if data_type == None: |
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98 | if line.startswith( '>' ): |
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99 | data_type = 'fasta' |
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100 | continue |
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101 | elif len( line.split( '\t' ) ) > 0: |
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102 | fields = line.split() |
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103 | for score in fields: |
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104 | try: |
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105 | int( score ) |
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106 | data_type = 'tabular' |
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107 | seq_method = 'solexa' |
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108 | break |
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109 | except: |
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110 | break |
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111 | elif data_type == 'fasta': |
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112 | fields = line.split() |
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113 | for score in fields: |
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114 | try: |
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115 | int( score ) |
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116 | seq_method = '454' |
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117 | break |
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118 | except: |
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119 | break |
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120 | if i == 100: |
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121 | break |
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122 | |
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123 | if data_type is None: |
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124 | stop_err( 'This tool can only use fasta data or tabular data.' ) |
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125 | if seq_method is None: |
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126 | stop_err( 'Invalid data for fasta format.') |
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127 | |
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128 | if os.path.exists( seq_infile_name ) and os.path.exists( score_infile_name ): |
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129 | seq = None |
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130 | score = None |
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131 | score_found = False |
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132 | |
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133 | score_file = open( score_infile_name, 'r' ) |
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134 | |
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135 | for i, line in enumerate( open( seq_infile_name ) ): |
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136 | line = line.rstrip( '\r\n' ) |
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137 | if not line or line.startswith( '#' ): |
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138 | continue |
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139 | if line.startswith( '>' ): |
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140 | if seq: |
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141 | scores = [] |
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142 | if data_type == 'fasta': |
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143 | score = None |
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144 | score_found = False |
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145 | score_line = 'start' |
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146 | while not score_found and score_line: |
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147 | score_line = score_file.readline().rstrip( '\r\n' ) |
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148 | if not score_line or score_line.startswith( '#' ): |
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149 | continue |
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150 | if score_line.startswith( '>' ): |
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151 | if score: |
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152 | scores = score.split() |
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153 | score_found = True |
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154 | score = None |
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155 | else: |
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156 | for val in score_line.split(): |
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157 | try: |
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158 | int( val ) |
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159 | except: |
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160 | score_file.close() |
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161 | stop_err( "Non-numerical value '%s' in score file." % val ) |
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162 | if not score: |
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163 | score = score_line |
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164 | else: |
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165 | score = '%s %s' % ( score, score_line ) |
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166 | elif data_type == 'tabular': |
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167 | score = score_file.readline().rstrip('\r\n') |
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168 | loc = score.split( '\t' ) |
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169 | for base in loc: |
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170 | nuc_error = base.split() |
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171 | try: |
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172 | nuc_error[0] = int( nuc_error[0] ) |
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173 | nuc_error[1] = int( nuc_error[1] ) |
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174 | nuc_error[2] = int( nuc_error[2] ) |
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175 | nuc_error[3] = int( nuc_error[3] ) |
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176 | big = max( nuc_error ) |
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177 | except: |
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178 | score_file.close() |
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179 | stop_err( "Invalid characters in line %d: '%s'" % ( i, line ) ) |
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180 | scores.append( big ) |
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181 | if scores: |
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182 | new_trim_seq_segments = trim_seq( seq, scores, arg, threshold_trim, threshold_report ) |
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183 | append_to_outfile( outfile_seq_name, seq_title, new_trim_seq_segments ) |
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184 | |
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185 | seq_title = line |
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186 | seq = None |
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187 | else: |
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188 | if not seq: |
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189 | seq = line |
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190 | else: |
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191 | seq = "%s%s" % ( seq, line ) |
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192 | if seq: |
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193 | scores = [] |
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194 | if data_type == 'fasta': |
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195 | score = None |
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196 | while score_line: |
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197 | score_line = score_file.readline().rstrip( '\r\n' ) |
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198 | if not score_line or score_line.startswith( '#' ) or score_line.startswith( '>' ): |
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199 | continue |
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200 | for val in score_line.split(): |
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201 | try: |
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202 | int( val ) |
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203 | except: |
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204 | score_file.close() |
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205 | stop_err( "Non-numerical value '%s' in score file." % val ) |
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206 | if not score: |
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207 | score = score_line |
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208 | else: |
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209 | score = "%s %s" % ( score, score_line ) |
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210 | if score: |
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211 | scores = score.split() |
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212 | elif data_type == 'tabular': |
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213 | score = score_file.readline().rstrip('\r\n') |
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214 | loc = score.split( '\t' ) |
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215 | for base in loc: |
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216 | nuc_error = base.split() |
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217 | try: |
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218 | nuc_error[0] = int( nuc_error[0] ) |
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219 | nuc_error[1] = int( nuc_error[1] ) |
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220 | nuc_error[2] = int( nuc_error[2] ) |
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221 | nuc_error[3] = int( nuc_error[3] ) |
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222 | big = max( nuc_error ) |
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223 | except: |
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224 | score_file.close() |
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225 | stop_err( "Invalid characters in line %d: '%s'" % ( i, line ) ) |
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226 | scores.append( big ) |
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227 | if scores: |
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228 | new_trim_seq_segments = trim_seq( seq, scores, arg, threshold_trim, threshold_report ) |
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229 | append_to_outfile( outfile_seq_name, seq_title, new_trim_seq_segments ) |
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230 | score_file.close() |
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231 | else: |
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232 | stop_err( "Cannot locate sequence file '%s'or score file '%s'." % ( seq_infile_name, score_infile_name ) ) |
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233 | |
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234 | if __name__ == "__main__": __main__() |
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