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1 #!/usr/bin/env python
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2 """
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3 #
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4 #------------------------------------------------------------------------------
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5 # University of Minnesota
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6 # Copyright 2014, Regents of the University of Minnesota
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7 #------------------------------------------------------------------------------
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8 # Author:
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9 #
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10 # James E Johnson
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11 #
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12 #------------------------------------------------------------------------------
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13 """
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14
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15
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16 """
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17 This tool takes the defuse results.tsv tab-delimited file, trinity
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18 and creates a tabular report
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40
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19
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20 Would it be possible to create 2 additional files from the deFuse-Trinity comparison program.
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21 One containing all the Trinity records matched to deFuse records (with the deFuse ID number),
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22 and the other with the ORFs records matching back to the Trinity records in the first files?
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23
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24 M045_Report.csv
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25 "","deFuse_subset.count","deFuse.gene_name1","deFuse.gene_name2","deFuse.span_count","deFuse.probability","deFuse.gene_chromosome1","deFuse.gene_location1","deFuse.gene_chromosome2","deFuse.gene_location2","deFuse_subset.type"
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26 "1",1,"Rps6","Dennd4c",7,0.814853504,"4","coding","4","coding","TIC "
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27
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28
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29
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30 OS03_Matched_Rev.csv
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31 "count","gene1","gene2","breakpoint","fusion","Trinity_transcript_ID","Trinity_transcript","ID1","protein"
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32
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33 "","deFuse.splitr_sequence","deFuse.gene_chromosome1","deFuse.gene_chromosome2","deFuse.gene_location1","deFuse.gene_location2","deFuse.gene_name1","deFuse.gene_name2","deFuse.span_count","deFuse.probability","word1","word2","fusion_part_1","fusion_part_2","fusion_point","fusion_point_rc","count","transcript"
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34
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36
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35 """
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36
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40
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37 import sys,re,os.path,math
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38 import textwrap
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36
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39 import optparse
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40 from optparse import OptionParser
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41
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42 revcompl = lambda x: ''.join([{'A':'T','C':'G','G':'C','T':'A','a':'t','c':'g','g':'c','t':'a','N':'N','n':'n'}[B] for B in x][::-1])
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43
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40
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44 codon_map = {"UUU":"F", "UUC":"F", "UUA":"L", "UUG":"L",
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45 "UCU":"S", "UCC":"S", "UCA":"S", "UCG":"S",
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46 "UAU":"Y", "UAC":"Y", "UAA":"*", "UAG":"*",
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47 "UGU":"C", "UGC":"C", "UGA":"*", "UGG":"W",
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48 "CUU":"L", "CUC":"L", "CUA":"L", "CUG":"L",
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49 "CCU":"P", "CCC":"P", "CCA":"P", "CCG":"P",
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50 "CAU":"H", "CAC":"H", "CAA":"Q", "CAG":"Q",
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51 "CGU":"R", "CGC":"R", "CGA":"R", "CGG":"R",
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52 "AUU":"I", "AUC":"I", "AUA":"I", "AUG":"M",
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53 "ACU":"T", "ACC":"T", "ACA":"T", "ACG":"T",
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54 "AAU":"N", "AAC":"N", "AAA":"K", "AAG":"K",
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55 "AGU":"S", "AGC":"S", "AGA":"R", "AGG":"R",
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56 "GUU":"V", "GUC":"V", "GUA":"V", "GUG":"V",
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57 "GCU":"A", "GCC":"A", "GCA":"A", "GCG":"A",
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58 "GAU":"D", "GAC":"D", "GAA":"E", "GAG":"E",
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59 "GGU":"G", "GGC":"G", "GGA":"G", "GGG":"G",}
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60
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61 def translate(seq) :
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62 rna = seq.upper().replace('T','U')
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63 aa = []
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64 for i in range(0,len(rna) - 2, 3):
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65 codon = rna[i:i+3]
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66 aa.append(codon_map[codon] if codon in codon_map else 'X')
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67 return ''.join(aa)
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68
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69 def get_stop_codons(seq) :
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70 rna = seq.upper().replace('T','U')
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71 stop_codons = []
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72 for i in range(0,len(rna) - 2, 3):
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73 codon = rna[i:i+3]
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74 aa = codon_map[codon] if codon in codon_map else 'X'
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75 if aa == '*':
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76 stop_codons.append(codon)
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77 return stop_codons
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78
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36
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79 def read_fasta(fp):
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80 name, seq = None, []
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81 for line in fp:
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82 line = line.rstrip()
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83 if line.startswith(">"):
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84 if name: yield (name, ''.join(seq))
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85 name, seq = line, []
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86 else:
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87 seq.append(line)
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88 if name: yield (name, ''.join(seq))
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89
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90
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91 def test_rcomplement(seq, target):
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92 try:
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93 comp = revcompl(seq)
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94 return comp in target
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95 except:
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96 pass
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97 return False
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98
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99 def test_reverse(seq,target):
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100 return options.test_reverse and seq and seq[::-1] in target
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101
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102 def cmp_alphanumeric(s1,s2):
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103 if s1 == s2:
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104 return 0
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105 a1 = re.findall("\d+|[a-zA-Z]+",s1)
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106 a2 = re.findall("\d+|[a-zA-Z]+",s2)
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107 for i in range(min(len(a1),len(a2))):
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108 if a1[i] == a2[i]:
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109 continue
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110 if a1[i].isdigit() and a2[i].isdigit():
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111 return int(a1[i]) - int(a2[i])
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112 return 1 if a1[i] > a2[i] else -1
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113 return len(a1) - len(a2)
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114
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115 def parse_defuse_results(inputFile):
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116 defuse_results = []
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117 columns = []
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118 coltype_int = ['expression1', 'expression2', 'gene_start1', 'gene_start2', 'gene_end1', 'gene_end2', 'genomic_break_pos1', 'genomic_break_pos2', 'breakpoint_homology', 'span_count', 'splitr_count', 'splice_score']
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119 coltype_float = ['probability']
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120 coltype_yn = [ 'orf', 'exonboundaries', 'read_through', 'interchromosomal', 'adjacent', 'altsplice', 'deletion', 'eversion', 'inversion']
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36
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121 try:
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122 for linenum,line in enumerate(inputFile):
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123 ## print >> sys.stderr, "%d: %s\n" % (linenum,line)
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124 fields = line.strip().split('\t')
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125 if line.startswith('cluster_id'):
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126 columns = fields
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127 ## print >> sys.stderr, "columns: %s\n" % columns
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128 continue
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40
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129 elif fields and len(fields) == len(columns):
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130 cluster_id = fields[columns.index('cluster_id')]
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131 cluster = dict()
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132 flags = []
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133 defuse_results.append(cluster)
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134 for i,v in enumerate(columns):
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135 if v in coltype_int:
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136 cluster[v] = int(fields[i])
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137 elif v in coltype_float:
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138 cluster[v] = float(fields[i])
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139 elif v in coltype_yn:
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140 cluster[v] = fields[i] == 'Y'
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141 if cluster[v]:
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142 flags.append(columns[i])
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143 else:
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144 cluster[v] = fields[i]
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145 cluster['flags'] = ','.join(flags)
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146 except Exception, e:
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147 print >> sys.stderr, "failed to read cluster_dict: %s" % e
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148 exit(1)
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36
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149 return defuse_results
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150
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151 ## deFuse params to the mapping application?
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152
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153 def __main__():
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154 #Parse Command Line
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155 parser = optparse.OptionParser()
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156 # files
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157 parser.add_option( '-i', '--input', dest='input', default=None, help='The input defuse results.tsv file (else read from stdin)' )
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158 parser.add_option( '-t', '--transcripts', dest='transcripts', default=None, help='Trinity transcripts' )
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159 parser.add_option( '-p', '--peptides', dest='peptides', default=None, help='Trinity ORFs' )
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160 parser.add_option( '-o', '--output', dest='output', default=None, help='The output report (else write to stdout)' )
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161 parser.add_option( '-m', '--matched', dest='matched', default=None, help='The output matched report' )
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162 parser.add_option( '-a', '--transcript_alignment', dest='transcript_alignment', default=None, help='The output alignment file' )
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163 parser.add_option( '-A', '--orf_alignment', dest='orf_alignment', default=None, help='The output ORF alignment file' )
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164 parser.add_option( '-N', '--nbases', dest='nbases', type='int', default=12, help='Number of bases on either side of the fusion to compare' )
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165 parser.add_option( '-L', '--min_pep_len', dest='min_pep_len', type='int', default=100, help='Minimum length of peptide to report' )
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166 parser.add_option( '-T', '--ticdist', dest='ticdist', type='int', default=1000000, help='Maximum intrachromosomal distance to be classified a Transcription-induced chimera (TIC)' )
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167 parser.add_option( '-P', '--prior_aa', dest='prior_aa', type='int', default=11, help='Number of protein AAs to show preceeding fusion point' )
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168 parser.add_option( '-I', '--incomplete_orfs', dest='incomplete_orfs', action='store_true', default=False, help='Count incomplete ORFs' )
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169 parser.add_option( '-O', '--orf_type', dest='orf_type', action='append', default=['complete','5prime_partial'], choices=['complete','5prime_partial','3prime_partial','internal'], help='ORF types to report' )
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170 parser.add_option( '-r', '--readthrough', dest='readthrough', type='int', default=3, help='Number of stop_codons to read through' )
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171 # min_orf_len
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172 # split_na_len
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173 # tic_len = 1000000
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174 # prior
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175 # deFuse direction reversed
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176 # in frame ?
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177 # contain known protein elements
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178 # what protein change
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179 # trinity provides full transctipt, defuse doesn't show full
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180 #parser.add_option( '-r', '--reference', dest='reference', default=None, help='The genomic reference fasta' )
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181 #parser.add_option( '-g', '--gtf', dest='gtf', default=None, help='The genomic reference gtf feature file')
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182 (options, args) = parser.parse_args()
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183
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184 # results.tsv input
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185 if options.input != None:
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186 try:
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187 inputPath = os.path.abspath(options.input)
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188 inputFile = open(inputPath, 'r')
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189 except Exception, e:
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190 print >> sys.stderr, "failed: %s" % e
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191 exit(2)
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192 else:
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193 inputFile = sys.stdin
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194 # vcf output
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195 if options.output != None:
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196 try:
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197 outputPath = os.path.abspath(options.output)
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198 outputFile = open(outputPath, 'w')
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199 except Exception, e:
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200 print >> sys.stderr, "failed: %s" % e
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201 exit(3)
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202 else:
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203 outputFile = sys.stdout
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40
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204 outputTxFile = None
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205 outputOrfFile = None
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206 if options.transcript_alignment:
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207 try:
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208 outputTxFile = open(options.transcript_alignment,'w')
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209 except Exception, e:
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210 print >> sys.stderr, "failed: %s" % e
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211 exit(3)
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212 if options.orf_alignment:
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213 try:
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214 outputOrfFile = open(options.orf_alignment,'w')
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215 except Exception, e:
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216 print >> sys.stderr, "failed: %s" % e
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217 exit(3)
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218 # Add percent match after transcript
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219 report_fields = ['gene_name1','gene_name2','span_count','probability','gene_chromosome1','gene_location1','gene_chromosome2','gene_location2','fusion_type','Transcript','coverage','Protein','flags','alignments1','alignments2']
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220 report_fields = ['cluster_id','gene_name1','gene_name2','span_count','probability','genomic_bkpt1','gene_location1','genomic_bkpt2','gene_location2','fusion_type','Transcript','coverage','Protein','flags','alignments1','alignments2']
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221 report_colnames = {'gene_name1':'Gene 1','gene_name2':'Gene 2','span_count':'Span cnt','probability':'Probability','gene_chromosome1':'From Chr','gene_location1':'Fusion point','gene_chromosome2':'To Chr','gene_location2':'Fusion point', 'cluster_id':'cluster_id', 'splitr_sequence':'splitr_sequence', 'splitr_count':'splitr_count', 'splitr_span_pvalue':'splitr_span_pvalue', 'splitr_pos_pvalue':'splitr_pos_pvalue', 'splitr_min_pvalue':'splitr_min_pvalue', 'adjacent':'adjacent', 'altsplice':'altsplice', 'break_adj_entropy1':'break_adj_entropy1', 'break_adj_entropy2':'break_adj_entropy2', 'break_adj_entropy_min':'break_adj_entropy_min', 'breakpoint_homology':'breakpoint_homology', 'breakseqs_estislands_percident':'breakseqs_estislands_percident', 'cdna_breakseqs_percident':'cdna_breakseqs_percident', 'deletion':'deletion', 'est_breakseqs_percident':'est_breakseqs_percident', 'eversion':'eversion', 'exonboundaries':'exonboundaries', 'expression1':'expression1', 'expression2':'expression2', 'gene1':'gene1', 'gene2':'gene2', 'gene_align_strand1':'gene_align_strand1', 'gene_align_strand2':'gene_align_strand2', 'gene_end1':'gene_end1', 'gene_end2':'gene_end2', 'gene_start1':'gene_start1', 'gene_start2':'gene_start2', 'gene_strand1':'gene_strand1', 'gene_strand2':'gene_strand2', 'genome_breakseqs_percident':'genome_breakseqs_percident', 'genomic_break_pos1':'genomic_break_pos1', 'genomic_break_pos2':'genomic_break_pos2', 'genomic_strand1':'genomic_strand1', 'genomic_strand2':'genomic_strand2', 'interchromosomal':'interchromosomal', 'interrupted_index1':'interrupted_index1', 'interrupted_index2':'interrupted_index2', 'inversion':'inversion', 'library_name':'library_name', 'max_map_count':'max_map_count', 'max_repeat_proportion':'max_repeat_proportion', 'mean_map_count':'mean_map_count', 'min_map_count':'min_map_count', 'num_multi_map':'num_multi_map', 'num_splice_variants':'num_splice_variants', 'orf':'orf', 'read_through':'read_through', 'repeat_proportion1':'repeat_proportion1', 'repeat_proportion2':'repeat_proportion2', 'span_coverage1':'span_coverage1', 'span_coverage2':'span_coverage2', 'span_coverage_max':'span_coverage_max', 'span_coverage_min':'span_coverage_min', 'splice_score':'splice_score', 'splicing_index1':'splicing_index1', 'splicing_index2':'splicing_index2', 'fusion_type':'Type', 'coverage':'fusion%','Transcript':'Transcript?','Protein':'Protein?','flags':'descriptions','fwd_seq':'fusion','alignments1':'alignments1','alignments2':'alignments2','genomic_bkpt1':'From Chr', 'genomic_bkpt2':'To Chr'}
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222
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223 ## Read defuse results
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224 fusions = parse_defuse_results(inputFile)
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225 ## Create a field with the 12 nt before and after the fusion point.
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226 ## Create a field with the reverse complement of the 24 nt fusion point field.
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227 ## Add fusion type filed (INTER, INTRA, TIC)
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228 for i,fusion in enumerate(fusions):
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229 fusion['ordinal'] = i + 1
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230 fusion['genomic_bkpt1'] = "%s:%d" % (fusion['gene_chromosome1'], fusion['genomic_break_pos1'])
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231 fusion['genomic_bkpt2'] = "%s:%d" % (fusion['gene_chromosome2'], fusion['genomic_break_pos2'])
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232 fusion['alignments1'] = "%s%s%s" % (fusion['genomic_strand1'], fusion['gene_strand1'], fusion['gene_align_strand1'])
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233 fusion['alignments2'] = "%s%s%s" % (fusion['genomic_strand2'], fusion['gene_strand2'], fusion['gene_align_strand2'])
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234 split_seqs = fusion['splitr_sequence'].split('|')
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235 fusion['split_seqs'] = split_seqs
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40
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236 fusion['split_seqs'] = split_seqs
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237 fusion['split_seq_lens'] = [len(split_seqs[0]),len(split_seqs[1])]
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238 fusion['split_max_lens'] = [len(split_seqs[0]),len(split_seqs[1])]
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239 fwd_off = min(abs(options.nbases),len(split_seqs[0]))
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240 rev_off = min(abs(options.nbases),len(split_seqs[1]))
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241 fusion['fwd_off'] = fwd_off
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242 fusion['rev_off'] = rev_off
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243 fwd_seq = split_seqs[0][-fwd_off:] + split_seqs[1][:rev_off]
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244 rev_seq = revcompl(fwd_seq)
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245 fusion['fwd_seq'] = fwd_seq
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246 fusion['rev_seq'] = rev_seq
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247 fusion_type = 'inter' if fusion['gene_chromosome1'] != fusion['gene_chromosome2'] else 'intra' if abs(fusion['genomic_break_pos1'] - fusion['genomic_break_pos2']) > options.ticdist else 'TIC'
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248 fusion['fusion_type'] = fusion_type
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40
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249 fusion['transcripts'] = dict()
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250 fusion['Transcript'] = 'No'
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40
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251 fusion['coverage'] = 0
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252 fusion['Protein'] = 'No'
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40
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253 # print >> sys.stdout, "%4d\t%6s\t%s\t%s\t%s\t%s\t%s" % (i,fusion['cluster_id'],fwd_seq,rev_seq,fusion_type,fusion['gene_name1'],fusion['gene_name2'])
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36
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254 inputFile.close()
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255
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256 ## Process Trinity data and compare to deFuse
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257 matched_transcripts = dict()
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258 matched_orfs = dict()
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259 transcript_orfs = dict()
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260 fusions_with_transcripts = set()
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261 fusions_with_orfs = set()
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40
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262 ## fusion['transcripts'][tx_id] { revcompl:?, bkpt:n, seq1: , seq2: , match1:n, match2:n}
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36
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263 n = 0
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264 if options.transcripts:
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265 with open(options.transcripts) as fp:
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40
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266 for tx_full_id, seq in read_fasta(fp):
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36
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267 n += 1
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268 for i,fusion in enumerate(fusions):
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269 if fusion['fwd_seq'] in seq or fusion['rev_seq'] in seq:
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270 fusions_with_transcripts.add(i)
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271 fusion['Transcript'] = 'Yes'
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40
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272 tx_id = tx_full_id.lstrip('>').split()[0]
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273 matched_transcripts[tx_full_id] = seq
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274 fusion['transcripts'][tx_id] = dict()
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275 fusion['transcripts'][tx_id]['seq'] = seq
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276 fusion['transcripts'][tx_id]['full_id'] = tx_full_id
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277 pos = seq.find(fusion['fwd_seq'])
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278 if pos >= 0:
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279 tx_bkpt = pos + fusion['fwd_off']
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280 # fusion['transcripts'][tx_full_id] = tx_bkpt
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281 if tx_bkpt > fusion['split_max_lens'][0]:
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282 fusion['split_max_lens'][0] = tx_bkpt
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283 len2 = len(seq) - tx_bkpt
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284 if len2 > fusion['split_max_lens'][1]:
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285 fusion['split_max_lens'][1] = len2
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286 fusion['transcripts'][tx_id]['bkpt'] = tx_bkpt
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287 fusion['transcripts'][tx_id]['revcompl'] = False
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288 fusion['transcripts'][tx_id]['seq1'] = seq[:tx_bkpt]
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289 fusion['transcripts'][tx_id]['seq2'] = seq[tx_bkpt:]
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290 else:
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291 pos = seq.find(fusion['rev_seq'])
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292 tx_bkpt = pos + fusion['rev_off']
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293 # fusion['transcripts'][tx_full_id] = -tx_bkpt
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294 if tx_bkpt > fusion['split_max_lens'][1]:
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295 fusion['split_max_lens'][1] = tx_bkpt
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296 len2 = len(seq) - tx_bkpt
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297 if len2 > fusion['split_max_lens'][0]:
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298 fusion['split_max_lens'][0] = len2
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299 rseq = revcompl(seq)
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300 pos = rseq.find(fusion['fwd_seq'])
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301 tx_bkpt = pos + fusion['fwd_off']
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302 fusion['transcripts'][tx_id]['bkpt'] = tx_bkpt
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303 fusion['transcripts'][tx_id]['revcompl'] = True
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304 fusion['transcripts'][tx_id]['seq1'] = rseq[:tx_bkpt]
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305 fusion['transcripts'][tx_id]['seq2'] = rseq[tx_bkpt:]
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306 fseq = fusion['split_seqs'][0]
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307 tseq = fusion['transcripts'][tx_id]['seq1']
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308 mlen = min(len(fseq),len(tseq))
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309 fusion['transcripts'][tx_id]['match1'] = mlen
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310 for j in range(1,mlen+1):
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311 if fseq[-j] != tseq[-j]:
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312 fusion['transcripts'][tx_id]['match1'] = j - 1
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313 break
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314 fseq = fusion['split_seqs'][1]
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315 tseq = fusion['transcripts'][tx_id]['seq2']
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316 mlen = min(len(fseq),len(tseq))
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317 fusion['transcripts'][tx_id]['match2'] = mlen
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318 for j in range(mlen):
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319 if fseq[j] != tseq[j]:
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320 fusion['transcripts'][tx_id]['match2'] = j
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321 break
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322 # coverage = math.floor(float(fusion['transcripts'][tx_id]['match1'] + fusion['transcripts'][tx_id]['match2']) * 100. / len(fusion['split_seqs'][0]+fusion['split_seqs'][1]))
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323 coverage = int((fusion['transcripts'][tx_id]['match1'] + fusion['transcripts'][tx_id]['match2']) * 1000. / len(fusion['split_seqs'][0]+fusion['split_seqs'][1])) * .1
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324 # print >> sys.stderr, "%s\t%d\t%d\t%d\%s\t\t%d\t%d\t%d\t%d" % (tx_id,fusion['transcripts'][tx_id]['match1'],fusion['transcripts'][tx_id]['match2'],len(fusion['split_seqs'][0]+fusion['split_seqs'][1]),coverage,len( fusion['split_seqs'][0]),len(fusion['transcripts'][tx_id]['seq1']),len(fusion['split_seqs'][1]),len(fusion['transcripts'][tx_id]['seq2']))
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325 fusion['coverage'] = max(coverage,fusion['coverage'])
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326 print >> sys.stdout, "fusions_with_transcripts: %d %s\n matched_transcripts: %d" % (len(fusions_with_transcripts),fusions_with_transcripts,len(matched_transcripts))
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327 ##for i,fusion in enumerate(fusions):
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328 ## print >> sys.stdout, "%4d\t%6s\t%s\t%s\t%s\t%s\t%s\t%s" % (i,fusion['cluster_id'],fusion['fwd_seq'],fusion['rev_seq'],fusion['fusion_type'],fusion['gene_name1'],fusion['gene_name2'], fusion['transcripts'])
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36
|
329 ## Process ORFs and compare to matched deFuse and Trinity data.
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330 ## Proteins must be at least 100 aa long, starting at the first "M" and must end with an "*".
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331 if options.peptides:
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332 with open(options.peptides) as fp:
|
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40
|
333 for orf_full_id, seq in read_fasta(fp):
|
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36
|
334 n += 1
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|
335 if len(seq) < options.min_pep_len:
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|
336 continue
|
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40
|
337 orf_type = re.match('^.* type:(\S+) .*$',orf_full_id).groups()[0]
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338 ## if not seq[-1] == '*' and not options.incomplete_orfs:
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339 ## if not orf_type 'complete' and not options.incomplete_orfs:
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340 if orf_type not in options.orf_type:
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341 continue
|
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36
|
342 for i,fusion in enumerate(fusions):
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343 if len(fusion['transcripts']) > 0:
|
|
40
|
344 for tx_id in fusion['transcripts']:
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345 ## >m.196252 g.196252 ORF g.196252 m.196252 type:complete len:237 (+) comp100000_c5_seq2:315-1025(+)
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346 ## >m.134565 g.134565 ORF g.134565 m.134565 type:5prime_partial len:126 (-) comp98702_c1_seq21:52-429(-)
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347 if tx_id+':' not in orf_full_id:
|
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348 continue
|
|
|
349 m = re.match("^.*%s:(\d+)-(\d+)[(]([+-])[)].*" % re.sub('([|.{}()$?^])','[\\1]',tx_id),orf_full_id)
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350 if m:
|
|
|
351 if not m.groups() or len(m.groups()) < 3 or m.groups()[0] == None:
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|
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352 print >> sys.stderr, "Error:\n%s\n%s\n" % (tx_id,orf_full_id)
|
|
|
353 orf_id = orf_full_id.lstrip('>').split()[0]
|
|
|
354 if not tx_id in transcript_orfs:
|
|
|
355 transcript_orfs[tx_id] = []
|
|
|
356 alignments = "%s%s%s %s%s%s" % (fusion['genomic_strand1'], fusion['gene_strand1'], fusion['gene_align_strand1'], fusion['genomic_strand2'], fusion['gene_strand2'], fusion['gene_align_strand2'])
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|
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357 # print >> sys.stdout, "%d %s bkpt:%d %s rc:%s (%s) %s" % (fusion['ordinal'], tx_id, int(fusion['transcripts'][tx_id]['bkpt']), str(m.groups()), str(fusion['transcripts'][tx_id]['revcompl']), alignments, orf_full_id)
|
|
|
358 start = seq.find('M')
|
|
36
|
359 pep_len = len(seq)
|
|
|
360 if pep_len - start < options.min_pep_len:
|
|
|
361 continue
|
|
40
|
362 orf_dict = dict()
|
|
|
363 transcript_orfs[tx_id].append(orf_dict)
|
|
36
|
364 fusions_with_orfs.add(i)
|
|
40
|
365 matched_orfs[orf_full_id] = seq
|
|
36
|
366 fusion['Protein'] = 'Yes'
|
|
40
|
367 tx_start = int(m.groups()[0])
|
|
|
368 tx_end = int(m.groups()[1])
|
|
|
369 tx_strand = m.groups()[2]
|
|
|
370 tx_bkpt = fusion['transcripts'][tx_id]['bkpt']
|
|
|
371 orf_dict['orf_id'] = orf_id
|
|
|
372 orf_dict['tx_start'] = tx_start
|
|
|
373 orf_dict['tx_end'] = tx_end
|
|
|
374 orf_dict['tx_strand'] = tx_strand
|
|
|
375 orf_dict['tx_bkpt'] = tx_bkpt
|
|
|
376 orf_dict['seq'] = seq[:start].lower() + seq[start:] if start > 0 else seq
|
|
|
377 ## >m.208656 g.208656 ORF g.208656 m.208656 type:5prime_partial len:303 (+) comp100185_c2_seq9:2-910(+)
|
|
|
378 ## translate(tx34[1:910])
|
|
|
379 ## translate(tx34[1:2048])
|
|
|
380 ## comp99273_c1_seq1 len=3146 (-2772)
|
|
|
381 ## >m.158338 g.158338 ORF g.158338 m.158338 type:complete len:785 (-) comp99273_c1_seq1:404-2758(-)
|
|
|
382 ## translate(tx[-2758:-403])
|
|
|
383 ## comp100185_c2_seq9 len=2048 (904)
|
|
|
384 ## novel protein sequence
|
|
|
385 ## find first novel AA
|
|
|
386 ## get prior n AAs
|
|
|
387 ## get novel AA seq thru n stop codons
|
|
|
388 ### tx_seq = matched_transcripts[tx_full_id] if tx_bkpt >= 0 else revcompl(tx_seq)
|
|
|
389 tx_seq = fusion['transcripts'][tx_id]['seq']
|
|
|
390 orf_dict['tx_seq'] = tx_seq
|
|
|
391 novel_tx_seq = tx_seq[tx_start - 1:] if tx_strand == '+' else revcompl(tx_seq[:tx_end])
|
|
|
392 read_thru_pep = translate(novel_tx_seq)
|
|
|
393 # fusion['transcripts'][tx_id]['revcompl'] = True
|
|
|
394 # tx_bkpt = fusion['transcripts'][tx_id]['bkpt']
|
|
|
395 # bkpt_aa_pos = tx_bkpt - tx_start - 1
|
|
|
396 # bkpt_aa_pos = (tx_bkpt - tx_start - 1) / 3 if tx_strand == '+' else tx_end
|
|
|
397 # print >> sys.stdout, "%s\n%s" % (seq,read_thru_pep)
|
|
|
398 stop_codons = get_stop_codons(novel_tx_seq)
|
|
|
399 if options.readthrough:
|
|
|
400 readthrough = options.readthrough + 1
|
|
|
401 read_thru_pep = '*'.join(read_thru_pep.split('*')[:readthrough])
|
|
|
402 stop_codons = stop_codons[:readthrough]
|
|
|
403 orf_dict['read_thru_pep'] = read_thru_pep
|
|
|
404 orf_dict['stop_codons'] = ','.join(stop_codons)
|
|
|
405 print >> sys.stdout, "fusions_with_orfs: %d %s\n matched_orfs: %d" % (len(fusions_with_orfs),fusions_with_orfs,len(matched_orfs))
|
|
|
406 ## Alignments 3 columns, seq columns padded out to longest seq, UPPERCASE_match diffs lowercase
|
|
|
407 ### defuse_id pre_split_seq post_split_seq
|
|
|
408 ### trinity_id pre_split_seq post_split_seq
|
|
|
409 ## Transcripts alignment output
|
|
|
410 ## Peptide alignment output
|
|
36
|
411 ## Write reports
|
|
40
|
412 ## OS03_Matched_Rev.csv
|
|
|
413 ## "count","gene1","gene2","breakpoint","fusion","Trinity_transcript_ID","Trinity_transcript","ID1","protein"
|
|
|
414 if options.transcripts and options.matched:
|
|
|
415 #match_fields = ['ordinal','gene_name1','gene_name2','fwd_seq']
|
|
|
416 outputMatchFile = open(options.matched,'w')
|
|
|
417 #print >> outputMatchFile, '\t'.join(["#fusion_id","cluster_id","gene1","gene2","breakpoint","fusion","Trinity_transcript_ID","Trinity_transcript","Trinity_ORF_Transcript","Trinity_ORF_ID","protein","read_through","stop_codons"])
|
|
|
418 print >> outputMatchFile, '\t'.join(["#fusion_id","cluster_id","gene1","gene2","breakpoint","fusion","Trinity_transcript_ID","Trinity_transcript","Trinity_ORF_Transcript","Trinity_ORF_ID","protein","stop_codons"])
|
|
|
419 for i,fusion in enumerate(fusions):
|
|
|
420 if len(fusion['transcripts']) > 0:
|
|
|
421 for tx_id in fusion['transcripts'].keys():
|
|
|
422 if tx_id in transcript_orfs:
|
|
|
423 for orf_dict in transcript_orfs[tx_id]:
|
|
|
424 if 'tx_seq' not in orf_dict:
|
|
|
425 print >> sys.stderr, "orf_dict %s" % orf_dict
|
|
|
426 #fields = [str(fusion['ordinal']),str(fusion['cluster_id']),fusion['gene_name1'],fusion['gene_name2'],fusion['fwd_seq'],fusion['splitr_sequence'],tx_id, fusion['transcripts'][tx_id]['seq1']+'|'+fusion['transcripts'][tx_id]['seq2'],orf_dict['tx_seq'],orf_dict['orf_id'],orf_dict['seq'],orf_dict['read_thru_pep'],orf_dict['stop_codons']]
|
|
|
427 fields = [str(fusion['ordinal']),str(fusion['cluster_id']),fusion['gene_name1'],fusion['gene_name2'],fusion['fwd_seq'],fusion['splitr_sequence'],tx_id, fusion['transcripts'][tx_id]['seq1']+'|'+fusion['transcripts'][tx_id]['seq2'],orf_dict['tx_seq'],orf_dict['orf_id'],orf_dict['read_thru_pep'],orf_dict['stop_codons']]
|
|
|
428 print >> outputMatchFile, '\t'.join(fields)
|
|
|
429 outputMatchFile.close()
|
|
|
430 if options.transcripts and options.transcript_alignment:
|
|
|
431 if outputTxFile:
|
|
|
432 id_fields = ['gene_name1','alignments1','gene_name2','alignments2','span_count','probability','gene_chromosome1','gene_location1','gene_chromosome2','gene_location2','fusion_type','Transcript','Protein','flags']
|
|
|
433 fa_width = 80
|
|
|
434 for i,fusion in enumerate(fusions):
|
|
|
435 if len(fusion['transcripts']) > 0:
|
|
|
436 alignments1 = "%s%s%s" % (fusion['genomic_strand1'], fusion['gene_strand1'], fusion['gene_align_strand1'])
|
|
|
437 alignments2 = "%s%s%s" % (fusion['genomic_strand2'], fusion['gene_strand2'], fusion['gene_align_strand2'])
|
|
|
438 alignments = "%s%s%s %s%s%s" % (fusion['genomic_strand1'], fusion['gene_strand1'], fusion['gene_align_strand1'], fusion['genomic_strand2'], fusion['gene_strand2'], fusion['gene_align_strand2'])
|
|
|
439 fusion_id = "%s (%s) %s" % (i + 1,alignments,' '.join([str(fusion[x]) for x in report_fields]))
|
|
|
440 for tx_id in fusion['transcripts'].keys():
|
|
|
441 m1 = fusion['transcripts'][tx_id]['match1']
|
|
|
442 f_seq1 = fusion['split_seqs'][0][:-m1].lower() + fusion['split_seqs'][0][-m1:]
|
|
|
443 t_seq1 = fusion['transcripts'][tx_id]['seq1'][:-m1].lower() + fusion['transcripts'][tx_id]['seq1'][-m1:]
|
|
|
444 if len(f_seq1) > len(t_seq1):
|
|
|
445 t_seq1 = t_seq1.rjust(len(f_seq1),'.')
|
|
|
446 elif len(f_seq1) < len(t_seq1):
|
|
|
447 f_seq1 = f_seq1.rjust(len(t_seq1),'.')
|
|
|
448 m2 = fusion['transcripts'][tx_id]['match2']
|
|
|
449 f_seq2 = fusion['split_seqs'][1][:m2] + fusion['split_seqs'][1][m2:].lower()
|
|
|
450 t_seq2 = fusion['transcripts'][tx_id]['seq2'][:m2] + fusion['transcripts'][tx_id]['seq2'][m2:].lower()
|
|
|
451 if len(f_seq2) > len(t_seq2):
|
|
|
452 t_seq2 = t_seq2.ljust(len(f_seq2),'.')
|
|
|
453 elif len(f_seq2) < len(t_seq2):
|
|
|
454 f_seq2 = f_seq2.ljust(len(t_seq2),'.')
|
|
|
455 print >> outputTxFile, ">%s\n%s\n%s" % (fusion_id,'\n'.join(textwrap.wrap(f_seq1,fa_width)),'\n'.join(textwrap.wrap(f_seq2,fa_width)))
|
|
|
456 print >> outputTxFile, "%s bkpt:%d rev_compl:%s\n%s\n%s" % (fusion['transcripts'][tx_id]['full_id'],fusion['transcripts'][tx_id]['bkpt'],str(fusion['transcripts'][tx_id]['revcompl']),'\n'.join(textwrap.wrap(t_seq1,fa_width)),'\n'.join(textwrap.wrap(t_seq2,fa_width)))
|
|
|
457 """
|
|
|
458 if options.peptides and options.orf_alignment:
|
|
|
459 pass
|
|
|
460 """
|
|
36
|
461 print >> outputFile,"%s\t%s" % ('#','\t'.join([report_colnames[x] for x in report_fields]))
|
|
|
462 for i,fusion in enumerate(fusions):
|
|
|
463 print >> outputFile,"%s\t%s" % (i + 1,'\t'.join([str(fusion[x]) for x in report_fields]))
|
|
|
464
|
|
|
465 if __name__ == "__main__" : __main__()
|
|
|
466
|
