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comparison defuse_trinity_analysis.py @ 36:4353f776dfa3

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Add defuse_trinity_analysis
author Jim Johnson <jj@umn.edu>
date Tue, 10 Feb 2015 19:35:52 -0600
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children 90127ee1eae5
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35:a004033614d4 36:4353f776dfa3
1 #!/usr/bin/env python
2 """
3 #
4 #------------------------------------------------------------------------------
5 # University of Minnesota
6 # Copyright 2014, Regents of the University of Minnesota
7 #------------------------------------------------------------------------------
8 # Author:
9 #
10 # James E Johnson
11 #
12 #------------------------------------------------------------------------------
13 """
14
15
16 """
17 This tool takes the defuse results.tsv tab-delimited file, trinity
18 and creates a tabular report
19 """
20
21 import sys,re,os.path
22 import optparse
23 from optparse import OptionParser
24
25 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])
26
27 def read_fasta(fp):
28 name, seq = None, []
29 for line in fp:
30 line = line.rstrip()
31 if line.startswith(">"):
32 if name: yield (name, ''.join(seq))
33 name, seq = line, []
34 else:
35 seq.append(line)
36 if name: yield (name, ''.join(seq))
37
38
39 def test_rcomplement(seq, target):
40 try:
41 comp = revcompl(seq)
42 return comp in target
43 except:
44 pass
45 return False
46
47 def test_reverse(seq,target):
48 return options.test_reverse and seq and seq[::-1] in target
49
50 def cmp_alphanumeric(s1,s2):
51 if s1 == s2:
52 return 0
53 a1 = re.findall("\d+|[a-zA-Z]+",s1)
54 a2 = re.findall("\d+|[a-zA-Z]+",s2)
55 for i in range(min(len(a1),len(a2))):
56 if a1[i] == a2[i]:
57 continue
58 if a1[i].isdigit() and a2[i].isdigit():
59 return int(a1[i]) - int(a2[i])
60 return 1 if a1[i] > a2[i] else -1
61 return len(a1) - len(a2)
62
63
64 def parse_defuse_results(inputFile):
65 columns = []
66 defuse_results = []
67 # {cluster_id : { field : value})
68 try:
69 for linenum,line in enumerate(inputFile):
70 ## print >> sys.stderr, "%d: %s\n" % (linenum,line)
71 fields = line.strip().split('\t')
72 if line.startswith('cluster_id'):
73 columns = fields
74 ## print >> sys.stderr, "columns: %s\n" % columns
75 continue
76 cluster_dict = dict()
77 cluster_id = fields[columns.index('cluster_id')]
78 cluster_dict['cluster_id'] = fields[columns.index('cluster_id')]
79 cluster_dict['gene_chromosome1'] = fields[columns.index('gene_chromosome1')]
80 cluster_dict['gene_chromosome2'] = fields[columns.index('gene_chromosome2')]
81 cluster_dict['genomic_strand1'] = fields[columns.index('genomic_strand1')]
82 cluster_dict['genomic_strand2'] = fields[columns.index('genomic_strand2')]
83 cluster_dict['gene1'] = fields[columns.index('gene1')]
84 cluster_dict['gene2'] = fields[columns.index('gene2')]
85 cluster_dict['gene_name1'] = fields[columns.index('gene_name1')]
86 cluster_dict['gene_name2'] = fields[columns.index('gene_name2')]
87 cluster_dict['gene_location1'] = fields[columns.index('gene_location1')]
88 cluster_dict['gene_location2'] = fields[columns.index('gene_location2')]
89 cluster_dict['expression1'] = int(fields[columns.index('expression1')])
90 cluster_dict['expression2'] = int(fields[columns.index('expression2')])
91 cluster_dict['genomic_break_pos1'] = int(fields[columns.index('genomic_break_pos1')])
92 cluster_dict['genomic_break_pos2'] = int(fields[columns.index('genomic_break_pos2')])
93 cluster_dict['breakpoint_homology'] = int(fields[columns.index('breakpoint_homology')])
94 cluster_dict['orf'] = fields[columns.index('orf')] == 'Y'
95 cluster_dict['exonboundaries'] = fields[columns.index('exonboundaries')] == 'Y'
96 cluster_dict['read_through'] = fields[columns.index('read_through')] == 'Y'
97 cluster_dict['interchromosomal'] = fields[columns.index('interchromosomal')] == 'Y'
98 cluster_dict['adjacent'] = fields[columns.index('adjacent')] == 'Y'
99 cluster_dict['altsplice'] = fields[columns.index('altsplice')] == 'Y'
100 cluster_dict['deletion'] = fields[columns.index('deletion')] == 'Y'
101 cluster_dict['eversion'] = fields[columns.index('eversion')] == 'Y'
102 cluster_dict['inversion'] = fields[columns.index('inversion')] == 'Y'
103 cluster_dict['span_count'] = int(fields[columns.index('span_count')])
104 cluster_dict['splitr_count'] = int(fields[columns.index('splitr_count')])
105 cluster_dict['splice_score'] = int(fields[columns.index('splice_score')])
106 cluster_dict['probability'] = float(fields[columns.index('probability')] if columns.index('probability') else 'nan')
107 cluster_dict['splitr_sequence'] = fields[columns.index('splitr_sequence')]
108 defuse_results.append(cluster_dict)
109 except Exception, e:
110 print >> sys.stderr, "failed: %s" % e
111 sys.exit(1)
112 return defuse_results
113
114 ## deFuse params to the mapping application?
115
116 def __main__():
117 #Parse Command Line
118 parser = optparse.OptionParser()
119 # files
120 parser.add_option( '-i', '--input', dest='input', help='The input defuse results.tsv file (else read from stdin)' )
121 parser.add_option( '-t', '--transcripts', dest='transcripts', default=None, help='Trinity transcripts' )
122 parser.add_option( '-p', '--peptides', dest='peptides', default=None, help='Trinity ORFs' )
123 parser.add_option( '-o', '--output', dest='output', help='The output report (else write to stdout)' )
124 parser.add_option( '-a', '--transcript_alignment', dest='transcript_alignment', help='The output alignment file' )
125 parser.add_option( '-A', '--orf_alignment', dest='orf_alignment', help='The output alignment file' )
126 parser.add_option( '-N', '--nbases', dest='nbases', type='int', default=12, help='Number of bases on either side of the fusion to compare' )
127 parser.add_option( '-L', '--min_pep_len', dest='min_pep_len', type='int', default=100, help='Minimum length of peptide to report' )
128 parser.add_option( '-T', '--ticdist', dest='ticdist', type='int', default=1000000, help='Maximum intrachromosomal distance to be classified a Transcription-induced chimera (TIC)' )
129 parser.add_option( '-P', '--prior_aa', dest='prior_aa', type='int', default=11, help='Number of protein AAs to show preceeding fusion point' )
130 # min_orf_len
131 # split_na_len
132 # tic_len = 1000000
133 # prior
134 # deFuse direction reversed
135 # in frame ?
136 # contain known protein elements
137 # what protein change
138 # trinity provides full transctipt, defuse doesn't show full
139 #parser.add_option( '-r', '--reference', dest='reference', default=None, help='The genomic reference fasta' )
140 #parser.add_option( '-g', '--gtf', dest='gtf', default=None, help='The genomic reference gtf feature file')
141 (options, args) = parser.parse_args()
142
143 # results.tsv input
144 if options.input != None:
145 try:
146 inputPath = os.path.abspath(options.input)
147 inputFile = open(inputPath, 'r')
148 except Exception, e:
149 print >> sys.stderr, "failed: %s" % e
150 exit(2)
151 else:
152 inputFile = sys.stdin
153 # vcf output
154 if options.output != None:
155 try:
156 outputPath = os.path.abspath(options.output)
157 outputFile = open(outputPath, 'w')
158 except Exception, e:
159 print >> sys.stderr, "failed: %s" % e
160 exit(3)
161 else:
162 outputFile = sys.stdout
163
164 ## Read defuse results
165 fusions = parse_defuse_results(inputFile)
166 ## Create a field with the 12 nt before and after the fusion point.
167 ## Create a field with the reverse complement of the 24 nt fusion point field.
168 ## Add fusion type filed (INTER, INTRA, TIC)
169 for i,fusion in enumerate(fusions):
170 fusion['ordinal'] = i + 1
171 split_seqs = fusion['splitr_sequence'].split('|')
172 fusion['split_seqs'] = split_seqs
173 fwd_seq = split_seqs[0][-(min(abs(options.nbases),len(split_seqs[0]))):] + split_seqs[1][:min(abs(options.nbases),len(split_seqs[1]))]
174 rev_seq = revcompl(fwd_seq)
175 fusion['fwd_seq'] = fwd_seq
176 fusion['rev_seq'] = rev_seq
177 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'
178 fusion['fusion_type'] = fusion_type
179 fusion['transcripts'] = []
180 fusion['Transcript'] = 'No'
181 fusion['Protein'] = 'No'
182 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'])
183 inputFile.close()
184
185 ## Process Trinity data and compare to deFuse
186 matched_transcripts = dict()
187 matched_orfs = dict()
188 fusions_with_transcripts = set()
189 fusions_with_orfs = set()
190 n = 0
191 if options.transcripts:
192 with open(options.transcripts) as fp:
193 for name, seq in read_fasta(fp):
194 n += 1
195 for i,fusion in enumerate(fusions):
196 if fusion['fwd_seq'] in seq or fusion['rev_seq'] in seq:
197 fusions_with_transcripts.add(i)
198 matched_transcripts[name] = seq
199 fusion['transcripts'].append(name)
200 fusion['Transcript'] = 'Yes'
201 print >> sys.stdout, "fusions_with_transcripts: %d %s\n matched_transcripts: %d" % (len(fusions_with_transcripts),fusions_with_transcripts,len(matched_transcripts))
202 for i,fusion in enumerate(fusions):
203 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'])
204 ## Process ORFs and compare to matched deFuse and Trinity data.
205 ## Proteins must be at least 100 aa long, starting at the first "M" and must end with an "*".
206 if options.peptides:
207 with open(options.peptides) as fp:
208 for name, seq in read_fasta(fp):
209 n += 1
210 if len(seq) < options.min_pep_len:
211 continue
212 for i,fusion in enumerate(fusions):
213 if len(fusion['transcripts']) > 0:
214 for id_string in fusion['transcripts']:
215 tx_id = id_string.lstrip('>').split()[0]
216 if tx_id in name:
217 pep_len = len(seq)
218 start = seq.find('M')
219 if pep_len - start < options.min_pep_len:
220 continue
221 fusions_with_orfs.add(i)
222 matched_orfs[name] = seq
223 fusion['Protein'] = 'Yes'
224 # fwd or reverse
225 tx_seq = matched_transcripts(tx_id)
226 pos = tx_seq.find(fusion['fwd_seq'])
227 if pos < 0:
228 pos = tx_seq.find(fusion['rev_seq'])
229 # locate fusion in transcript
230 # locate fusion in ORF
231 fusion['prior_pep_seq'] = ''
232 fusion['novel_pep_seq'] = ''
233 print >> sys.stdout, "fusions_with_orfs: %d %s\n matched_orfs: %d" % (len(fusions_with_orfs),fusions_with_orfs,len(matched_orfs))
234 ## Write reports
235 report_fields = ['gene_name1','gene_name2','span_count','probability','gene_chromosome1','gene_location1','gene_chromosome2','gene_location2','fusion_type','Transcript','Protein']
236 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','fusion_type':'Type','Transcript':'Transcript?','Protein':'Protein?' }
237 print >> outputFile,"%s\t%s" % ('#','\t'.join([report_colnames[x] for x in report_fields]))
238 for i,fusion in enumerate(fusions):
239 print >> outputFile,"%s\t%s" % (i + 1,'\t'.join([str(fusion[x]) for x in report_fields]))
240 # print >> outputFile, "%d\t%s\t%s\t%d\t%f\t%s\t%s\t%s\t%s\t%s\t%s\t%s" % (i,fusion['gene_name1'],fusion['gene_name2'],fusion['span_count'],fusion['probability'],fusion['gene_chromosome1'],fusion['gene_location1'],fusion['gene_chromosome2'],fusion['gene_location2'],fusion['fusion_type'],fusion['Transcript'],fusion['Protein'])
241
242 if __name__ == "__main__" : __main__()
243