1 | #!/usr/bin/env python |
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2 | |
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3 | import os, sys, math, tempfile, zipfile, re |
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4 | from rpy import * |
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5 | |
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6 | assert sys.version_info[:2] >= ( 2, 4 ) |
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7 | |
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8 | def stop_err( msg ): |
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9 | sys.stderr.write( "%s\n" % msg ) |
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10 | sys.exit() |
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11 | |
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12 | def unzip( filename ): |
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13 | zip_file = zipfile.ZipFile( filename, 'r' ) |
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14 | tmpfilename = tempfile.NamedTemporaryFile().name |
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15 | for name in zip_file.namelist(): |
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16 | file( tmpfilename, 'a' ).write( zip_file.read( name ) ) |
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17 | zip_file.close() |
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18 | return tmpfilename |
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19 | |
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20 | def __main__(): |
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21 | infile_score_name = sys.argv[1].strip() |
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22 | outfile_R_name = sys.argv[2].strip() |
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23 | |
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24 | try: |
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25 | score_threshold = int( sys.argv[3].strip() ) |
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26 | except: |
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27 | stop_err( 'Threshold for quality score must be numerical.' ) |
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28 | |
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29 | infile_is_zipped = False |
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30 | if zipfile.is_zipfile( infile_score_name ): |
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31 | infile_is_zipped = True |
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32 | infile_name = unzip( infile_score_name ) |
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33 | else: |
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34 | infile_name = infile_score_name |
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35 | |
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36 | # detect whether it's tabular or fasta format |
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37 | seq_method = None |
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38 | data_type = None |
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39 | for i, line in enumerate( file( infile_name ) ): |
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40 | line = line.rstrip( '\r\n' ) |
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41 | if not line or line.startswith( '#' ): |
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42 | continue |
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43 | if data_type == None: |
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44 | if line.startswith( '>' ): |
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45 | data_type = 'fasta' |
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46 | continue |
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47 | elif len( line.split( '\t' ) ) > 0: |
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48 | fields = line.split() |
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49 | for score in fields: |
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50 | try: |
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51 | int( score ) |
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52 | data_type = 'tabular' |
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53 | seq_method = 'solexa' |
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54 | break |
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55 | except: |
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56 | break |
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57 | elif data_type == 'fasta': |
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58 | fields = line.split() |
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59 | for score in fields: |
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60 | try: |
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61 | int( score ) |
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62 | seq_method = '454' |
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63 | break |
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64 | except: |
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65 | break |
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66 | if i == 100: |
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67 | break |
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68 | |
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69 | if data_type is None: |
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70 | stop_err( 'This tool can only use fasta data or tabular data.' ) |
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71 | if seq_method is None: |
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72 | stop_err( 'Invalid data for fasta format.') |
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73 | |
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74 | cont_high_quality = [] |
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75 | invalid_lines = 0 |
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76 | invalid_scores = 0 |
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77 | if seq_method == 'solexa': |
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78 | for i, line in enumerate( open( infile_name ) ): |
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79 | line = line.rstrip( '\r\n' ) |
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80 | if not line or line.startswith( '#' ): |
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81 | continue |
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82 | locs = line.split( '\t' ) |
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83 | for j, base in enumerate( locs ): |
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84 | nuc_errors = base.split() |
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85 | try: |
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86 | nuc_errors[0] = int( nuc_errors[0] ) |
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87 | nuc_errors[1] = int( nuc_errors[1] ) |
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88 | nuc_errors[2] = int( nuc_errors[2] ) |
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89 | nuc_errors[3] = int( nuc_errors[3] ) |
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90 | big = max( nuc_errors ) |
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91 | except: |
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92 | invalid_scores += 1 |
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93 | big = 0 |
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94 | if j == 0: |
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95 | cont_high_quality.append(1) |
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96 | else: |
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97 | if big >= score_threshold: |
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98 | cont_high_quality[ len( cont_high_quality ) - 1 ] += 1 |
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99 | else: |
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100 | cont_high_quality.append(1) |
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101 | else: # seq_method == '454' |
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102 | tmp_score = '' |
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103 | for i, line in enumerate( open( infile_name ) ): |
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104 | line = line.rstrip( '\r\n' ) |
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105 | if not line or line.startswith( '#' ): |
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106 | continue |
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107 | if line.startswith( '>' ): |
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108 | if len( tmp_score ) > 0: |
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109 | locs = tmp_score.split() |
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110 | for j, base in enumerate( locs ): |
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111 | try: |
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112 | base = int( base ) |
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113 | except: |
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114 | invalid_scores += 1 |
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115 | base = 0 |
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116 | if j == 0: |
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117 | cont_high_quality.append(1) |
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118 | else: |
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119 | if base >= score_threshold: |
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120 | cont_high_quality[ len( cont_high_quality ) - 1 ] += 1 |
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121 | else: |
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122 | cont_high_quality.append(1) |
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123 | tmp_score = '' |
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124 | else: |
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125 | tmp_score = "%s %s" % ( tmp_score, line ) |
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126 | if len( tmp_score ) > 0: |
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127 | locs = tmp_score.split() |
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128 | for j, base in enumerate( locs ): |
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129 | try: |
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130 | base = int( base ) |
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131 | except: |
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132 | invalid_scores += 1 |
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133 | base = 0 |
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134 | if j == 0: |
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135 | cont_high_quality.append(1) |
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136 | else: |
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137 | if base >= score_threshold: |
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138 | cont_high_quality[ len( cont_high_quality ) - 1 ] += 1 |
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139 | else: |
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140 | cont_high_quality.append(1) |
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141 | |
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142 | # generate pdf figures |
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143 | cont_high_quality = array ( cont_high_quality ) |
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144 | outfile_R_pdf = outfile_R_name |
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145 | r.pdf( outfile_R_pdf ) |
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146 | title = "Histogram of continuous high quality scores" |
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147 | xlim_range = [ 1, max( cont_high_quality ) ] |
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148 | nclass = max( cont_high_quality ) |
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149 | if nclass > 100: |
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150 | nclass = 100 |
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151 | r.hist( cont_high_quality, probability=True, xlab="Continuous High Quality Score length (bp)", ylab="Frequency (%)", xlim=xlim_range, main=title, nclass=nclass) |
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152 | r.dev_off() |
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153 | |
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154 | if infile_is_zipped and os.path.exists( infile_name ): |
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155 | # Need to delete temporary file created when we unzipped the infile archive |
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156 | os.remove( infile_name ) |
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157 | |
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158 | if invalid_lines > 0: |
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159 | print 'Skipped %d invalid lines. ' % invalid_lines |
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160 | if invalid_scores > 0: |
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161 | print 'Skipped %d invalid scores. ' % invalid_scores |
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162 | |
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163 | r.quit( save="no" ) |
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164 | |
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165 | if __name__=="__main__":__main__() |
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