Mercurial > repos > jjohnson > defuse
diff defuse_trinity_analysis.py @ 11:b22f8634ff84 draft
planemo upload for repository https://github.com/jj-umn/galaxytools/tree/master/defuse commit 23b94b5747c6956360cd2eca0a07a669929ea141-dirty
| author | jjohnson |
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| date | Sun, 17 Jan 2016 14:11:06 -0500 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/defuse_trinity_analysis.py Sun Jan 17 14:11:06 2016 -0500 @@ -0,0 +1,466 @@ +#!/usr/bin/env python +""" +# +#------------------------------------------------------------------------------ +# University of Minnesota +# Copyright 2014, Regents of the University of Minnesota +#------------------------------------------------------------------------------ +# Author: +# +# James E Johnson +# +#------------------------------------------------------------------------------ +""" + + +""" +This tool takes the defuse results.tsv tab-delimited file, trinity +and creates a tabular report + +Would it be possible to create 2 additional files from the deFuse-Trinity comparison program. +One containing all the Trinity records matched to deFuse records (with the deFuse ID number), +and the other with the ORFs records matching back to the Trinity records in the first files? + +M045_Report.csv +"","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" +"1",1,"Rps6","Dennd4c",7,0.814853504,"4","coding","4","coding","TIC " + + + +OS03_Matched_Rev.csv +"count","gene1","gene2","breakpoint","fusion","Trinity_transcript_ID","Trinity_transcript","ID1","protein" + +"","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" + +""" + +import sys,re,os.path,math +import textwrap +import optparse +from optparse import OptionParser + +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]) + +codon_map = {"UUU":"F", "UUC":"F", "UUA":"L", "UUG":"L", + "UCU":"S", "UCC":"S", "UCA":"S", "UCG":"S", + "UAU":"Y", "UAC":"Y", "UAA":"*", "UAG":"*", + "UGU":"C", "UGC":"C", "UGA":"*", "UGG":"W", + "CUU":"L", "CUC":"L", "CUA":"L", "CUG":"L", + "CCU":"P", "CCC":"P", "CCA":"P", "CCG":"P", + "CAU":"H", "CAC":"H", "CAA":"Q", "CAG":"Q", + "CGU":"R", "CGC":"R", "CGA":"R", "CGG":"R", + "AUU":"I", "AUC":"I", "AUA":"I", "AUG":"M", + "ACU":"T", "ACC":"T", "ACA":"T", "ACG":"T", + "AAU":"N", "AAC":"N", "AAA":"K", "AAG":"K", + "AGU":"S", "AGC":"S", "AGA":"R", "AGG":"R", + "GUU":"V", "GUC":"V", "GUA":"V", "GUG":"V", + "GCU":"A", "GCC":"A", "GCA":"A", "GCG":"A", + "GAU":"D", "GAC":"D", "GAA":"E", "GAG":"E", + "GGU":"G", "GGC":"G", "GGA":"G", "GGG":"G",} + +def translate(seq) : + rna = seq.upper().replace('T','U') + aa = [] + for i in range(0,len(rna) - 2, 3): + codon = rna[i:i+3] + aa.append(codon_map[codon] if codon in codon_map else 'X') + return ''.join(aa) + +def get_stop_codons(seq) : + rna = seq.upper().replace('T','U') + stop_codons = [] + for i in range(0,len(rna) - 2, 3): + codon = rna[i:i+3] + aa = codon_map[codon] if codon in codon_map else 'X' + if aa == '*': + stop_codons.append(codon) + return stop_codons + +def read_fasta(fp): + name, seq = None, [] + for line in fp: + line = line.rstrip() + if line.startswith(">"): + if name: yield (name, ''.join(seq)) + name, seq = line, [] + else: + seq.append(line) + if name: yield (name, ''.join(seq)) + + +def test_rcomplement(seq, target): + try: + comp = revcompl(seq) + return comp in target + except: + pass + return False + +def test_reverse(seq,target): + return options.test_reverse and seq and seq[::-1] in target + +def cmp_alphanumeric(s1,s2): + if s1 == s2: + return 0 + a1 = re.findall("\d+|[a-zA-Z]+",s1) + a2 = re.findall("\d+|[a-zA-Z]+",s2) + for i in range(min(len(a1),len(a2))): + if a1[i] == a2[i]: + continue + if a1[i].isdigit() and a2[i].isdigit(): + return int(a1[i]) - int(a2[i]) + return 1 if a1[i] > a2[i] else -1 + return len(a1) - len(a2) + +def parse_defuse_results(inputFile): + defuse_results = [] + columns = [] + 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'] + coltype_float = ['probability'] + coltype_yn = [ 'orf', 'exonboundaries', 'read_through', 'interchromosomal', 'adjacent', 'altsplice', 'deletion', 'eversion', 'inversion'] + try: + for linenum,line in enumerate(inputFile): + ## print >> sys.stderr, "%d: %s\n" % (linenum,line) + fields = line.strip().split('\t') + if line.startswith('cluster_id'): + columns = fields + ## print >> sys.stderr, "columns: %s\n" % columns + continue + elif fields and len(fields) == len(columns): + cluster_id = fields[columns.index('cluster_id')] + cluster = dict() + flags = [] + defuse_results.append(cluster) + for i,v in enumerate(columns): + if v in coltype_int: + cluster[v] = int(fields[i]) + elif v in coltype_float: + cluster[v] = float(fields[i]) + elif v in coltype_yn: + cluster[v] = fields[i] == 'Y' + if cluster[v]: + flags.append(columns[i]) + else: + cluster[v] = fields[i] + cluster['flags'] = ','.join(flags) + except Exception, e: + print >> sys.stderr, "failed to read cluster_dict: %s" % e + exit(1) + return defuse_results + +## deFuse params to the mapping application? + +def __main__(): + #Parse Command Line + parser = optparse.OptionParser() + # files + parser.add_option( '-i', '--input', dest='input', default=None, help='The input defuse results.tsv file (else read from stdin)' ) + parser.add_option( '-t', '--transcripts', dest='transcripts', default=None, help='Trinity transcripts' ) + parser.add_option( '-p', '--peptides', dest='peptides', default=None, help='Trinity ORFs' ) + parser.add_option( '-o', '--output', dest='output', default=None, help='The output report (else write to stdout)' ) + parser.add_option( '-m', '--matched', dest='matched', default=None, help='The output matched report' ) + parser.add_option( '-a', '--transcript_alignment', dest='transcript_alignment', default=None, help='The output alignment file' ) + parser.add_option( '-A', '--orf_alignment', dest='orf_alignment', default=None, help='The output ORF alignment file' ) + parser.add_option( '-N', '--nbases', dest='nbases', type='int', default=12, help='Number of bases on either side of the fusion to compare' ) + parser.add_option( '-L', '--min_pep_len', dest='min_pep_len', type='int', default=100, help='Minimum length of peptide to report' ) + parser.add_option( '-T', '--ticdist', dest='ticdist', type='int', default=1000000, help='Maximum intrachromosomal distance to be classified a Transcription-induced chimera (TIC)' ) + parser.add_option( '-P', '--prior_aa', dest='prior_aa', type='int', default=11, help='Number of protein AAs to show preceeding fusion point' ) + parser.add_option( '-I', '--incomplete_orfs', dest='incomplete_orfs', action='store_true', default=False, help='Count incomplete ORFs' ) + 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' ) + parser.add_option( '-r', '--readthrough', dest='readthrough', type='int', default=3, help='Number of stop_codons to read through' ) + # min_orf_len + # split_na_len + # tic_len = 1000000 + # prior + # deFuse direction reversed + # in frame ? + # contain known protein elements + # what protein change + # trinity provides full transctipt, defuse doesn't show full + #parser.add_option( '-r', '--reference', dest='reference', default=None, help='The genomic reference fasta' ) + #parser.add_option( '-g', '--gtf', dest='gtf', default=None, help='The genomic reference gtf feature file') + (options, args) = parser.parse_args() + + # results.tsv input + if options.input != None: + try: + inputPath = os.path.abspath(options.input) + inputFile = open(inputPath, 'r') + except Exception, e: + print >> sys.stderr, "failed: %s" % e + exit(2) + else: + inputFile = sys.stdin + # vcf output + if options.output != None: + try: + outputPath = os.path.abspath(options.output) + outputFile = open(outputPath, 'w') + except Exception, e: + print >> sys.stderr, "failed: %s" % e + exit(3) + else: + outputFile = sys.stdout + outputTxFile = None + outputOrfFile = None + if options.transcript_alignment: + try: + outputTxFile = open(options.transcript_alignment,'w') + except Exception, e: + print >> sys.stderr, "failed: %s" % e + exit(3) + if options.orf_alignment: + try: + outputOrfFile = open(options.orf_alignment,'w') + except Exception, e: + print >> sys.stderr, "failed: %s" % e + exit(3) + # Add percent match after transcript + 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'] + 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'] + 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'} + + ## Read defuse results + fusions = parse_defuse_results(inputFile) + ## Create a field with the 12 nt before and after the fusion point. + ## Create a field with the reverse complement of the 24 nt fusion point field. + ## Add fusion type filed (INTER, INTRA, TIC) + for i,fusion in enumerate(fusions): + fusion['ordinal'] = i + 1 + fusion['genomic_bkpt1'] = "%s:%d" % (fusion['gene_chromosome1'], fusion['genomic_break_pos1']) + fusion['genomic_bkpt2'] = "%s:%d" % (fusion['gene_chromosome2'], fusion['genomic_break_pos2']) + fusion['alignments1'] = "%s%s%s" % (fusion['genomic_strand1'], fusion['gene_strand1'], fusion['gene_align_strand1']) + fusion['alignments2'] = "%s%s%s" % (fusion['genomic_strand2'], fusion['gene_strand2'], fusion['gene_align_strand2']) + split_seqs = fusion['splitr_sequence'].split('|') + fusion['split_seqs'] = split_seqs + fusion['split_seqs'] = split_seqs + fusion['split_seq_lens'] = [len(split_seqs[0]),len(split_seqs[1])] + fusion['split_max_lens'] = [len(split_seqs[0]),len(split_seqs[1])] + fwd_off = min(abs(options.nbases),len(split_seqs[0])) + rev_off = min(abs(options.nbases),len(split_seqs[1])) + fusion['fwd_off'] = fwd_off + fusion['rev_off'] = rev_off + fwd_seq = split_seqs[0][-fwd_off:] + split_seqs[1][:rev_off] + rev_seq = revcompl(fwd_seq) + fusion['fwd_seq'] = fwd_seq + fusion['rev_seq'] = rev_seq + 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' + fusion['fusion_type'] = fusion_type + fusion['transcripts'] = dict() + fusion['Transcript'] = 'No' + fusion['coverage'] = 0 + fusion['Protein'] = 'No' + # 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']) + inputFile.close() + + ## Process Trinity data and compare to deFuse + matched_transcripts = dict() + matched_orfs = dict() + transcript_orfs = dict() + fusions_with_transcripts = set() + fusions_with_orfs = set() + ## fusion['transcripts'][tx_id] { revcompl:?, bkpt:n, seq1: , seq2: , match1:n, match2:n} + n = 0 + if options.transcripts: + with open(options.transcripts) as fp: + for tx_full_id, seq in read_fasta(fp): + n += 1 + for i,fusion in enumerate(fusions): + if fusion['fwd_seq'] in seq or fusion['rev_seq'] in seq: + fusions_with_transcripts.add(i) + fusion['Transcript'] = 'Yes' + tx_id = tx_full_id.lstrip('>').split()[0] + matched_transcripts[tx_full_id] = seq + fusion['transcripts'][tx_id] = dict() + fusion['transcripts'][tx_id]['seq'] = seq + fusion['transcripts'][tx_id]['full_id'] = tx_full_id + pos = seq.find(fusion['fwd_seq']) + if pos >= 0: + tx_bkpt = pos + fusion['fwd_off'] + # fusion['transcripts'][tx_full_id] = tx_bkpt + if tx_bkpt > fusion['split_max_lens'][0]: + fusion['split_max_lens'][0] = tx_bkpt + len2 = len(seq) - tx_bkpt + if len2 > fusion['split_max_lens'][1]: + fusion['split_max_lens'][1] = len2 + fusion['transcripts'][tx_id]['bkpt'] = tx_bkpt + fusion['transcripts'][tx_id]['revcompl'] = False + fusion['transcripts'][tx_id]['seq1'] = seq[:tx_bkpt] + fusion['transcripts'][tx_id]['seq2'] = seq[tx_bkpt:] + else: + pos = seq.find(fusion['rev_seq']) + tx_bkpt = pos + fusion['rev_off'] + # fusion['transcripts'][tx_full_id] = -tx_bkpt + if tx_bkpt > fusion['split_max_lens'][1]: + fusion['split_max_lens'][1] = tx_bkpt + len2 = len(seq) - tx_bkpt + if len2 > fusion['split_max_lens'][0]: + fusion['split_max_lens'][0] = len2 + rseq = revcompl(seq) + pos = rseq.find(fusion['fwd_seq']) + tx_bkpt = pos + fusion['fwd_off'] + fusion['transcripts'][tx_id]['bkpt'] = tx_bkpt + fusion['transcripts'][tx_id]['revcompl'] = True + fusion['transcripts'][tx_id]['seq1'] = rseq[:tx_bkpt] + fusion['transcripts'][tx_id]['seq2'] = rseq[tx_bkpt:] + fseq = fusion['split_seqs'][0] + tseq = fusion['transcripts'][tx_id]['seq1'] + mlen = min(len(fseq),len(tseq)) + fusion['transcripts'][tx_id]['match1'] = mlen + for j in range(1,mlen+1): + if fseq[-j] != tseq[-j]: + fusion['transcripts'][tx_id]['match1'] = j - 1 + break + fseq = fusion['split_seqs'][1] + tseq = fusion['transcripts'][tx_id]['seq2'] + mlen = min(len(fseq),len(tseq)) + fusion['transcripts'][tx_id]['match2'] = mlen + for j in range(mlen): + if fseq[j] != tseq[j]: + fusion['transcripts'][tx_id]['match2'] = j + break + # coverage = math.floor(float(fusion['transcripts'][tx_id]['match1'] + fusion['transcripts'][tx_id]['match2']) * 100. / len(fusion['split_seqs'][0]+fusion['split_seqs'][1])) + coverage = int((fusion['transcripts'][tx_id]['match1'] + fusion['transcripts'][tx_id]['match2']) * 1000. / len(fusion['split_seqs'][0]+fusion['split_seqs'][1])) * .1 + # 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'])) + fusion['coverage'] = max(coverage,fusion['coverage']) + print >> sys.stdout, "fusions_with_transcripts: %d %s\n matched_transcripts: %d" % (len(fusions_with_transcripts),fusions_with_transcripts,len(matched_transcripts)) + ##for i,fusion in enumerate(fusions): + ## 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']) + ## Process ORFs and compare to matched deFuse and Trinity data. + ## Proteins must be at least 100 aa long, starting at the first "M" and must end with an "*". + if options.peptides: + with open(options.peptides) as fp: + for orf_full_id, seq in read_fasta(fp): + n += 1 + if len(seq) < options.min_pep_len: + continue + orf_type = re.match('^.* type:(\S+) .*$',orf_full_id).groups()[0] + ## if not seq[-1] == '*' and not options.incomplete_orfs: + ## if not orf_type 'complete' and not options.incomplete_orfs: + if orf_type not in options.orf_type: + continue + for i,fusion in enumerate(fusions): + if len(fusion['transcripts']) > 0: + for tx_id in fusion['transcripts']: + ## >m.196252 g.196252 ORF g.196252 m.196252 type:complete len:237 (+) comp100000_c5_seq2:315-1025(+) + ## >m.134565 g.134565 ORF g.134565 m.134565 type:5prime_partial len:126 (-) comp98702_c1_seq21:52-429(-) + if tx_id+':' not in orf_full_id: + continue + m = re.match("^.*%s:(\d+)-(\d+)[(]([+-])[)].*" % re.sub('([|.{}()$?^])','[\\1]',tx_id),orf_full_id) + if m: + if not m.groups() or len(m.groups()) < 3 or m.groups()[0] == None: + print >> sys.stderr, "Error:\n%s\n%s\n" % (tx_id,orf_full_id) + orf_id = orf_full_id.lstrip('>').split()[0] + if not tx_id in transcript_orfs: + transcript_orfs[tx_id] = [] + 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']) + # 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) + start = seq.find('M') + pep_len = len(seq) + if pep_len - start < options.min_pep_len: + continue + orf_dict = dict() + transcript_orfs[tx_id].append(orf_dict) + fusions_with_orfs.add(i) + matched_orfs[orf_full_id] = seq + fusion['Protein'] = 'Yes' + tx_start = int(m.groups()[0]) + tx_end = int(m.groups()[1]) + tx_strand = m.groups()[2] + tx_bkpt = fusion['transcripts'][tx_id]['bkpt'] + orf_dict['orf_id'] = orf_id + orf_dict['tx_start'] = tx_start + orf_dict['tx_end'] = tx_end + orf_dict['tx_strand'] = tx_strand + orf_dict['tx_bkpt'] = tx_bkpt + orf_dict['seq'] = seq[:start].lower() + seq[start:] if start > 0 else seq + ## >m.208656 g.208656 ORF g.208656 m.208656 type:5prime_partial len:303 (+) comp100185_c2_seq9:2-910(+) + ## translate(tx34[1:910]) + ## translate(tx34[1:2048]) + ## comp99273_c1_seq1 len=3146 (-2772) + ## >m.158338 g.158338 ORF g.158338 m.158338 type:complete len:785 (-) comp99273_c1_seq1:404-2758(-) + ## translate(tx[-2758:-403]) + ## comp100185_c2_seq9 len=2048 (904) + ## novel protein sequence + ## find first novel AA + ## get prior n AAs + ## get novel AA seq thru n stop codons + ### tx_seq = matched_transcripts[tx_full_id] if tx_bkpt >= 0 else revcompl(tx_seq) + tx_seq = fusion['transcripts'][tx_id]['seq'] + orf_dict['tx_seq'] = tx_seq + novel_tx_seq = tx_seq[tx_start - 1:] if tx_strand == '+' else revcompl(tx_seq[:tx_end]) + read_thru_pep = translate(novel_tx_seq) + # fusion['transcripts'][tx_id]['revcompl'] = True + # tx_bkpt = fusion['transcripts'][tx_id]['bkpt'] + # bkpt_aa_pos = tx_bkpt - tx_start - 1 + # bkpt_aa_pos = (tx_bkpt - tx_start - 1) / 3 if tx_strand == '+' else tx_end + # print >> sys.stdout, "%s\n%s" % (seq,read_thru_pep) + stop_codons = get_stop_codons(novel_tx_seq) + if options.readthrough: + readthrough = options.readthrough + 1 + read_thru_pep = '*'.join(read_thru_pep.split('*')[:readthrough]) + stop_codons = stop_codons[:readthrough] + orf_dict['read_thru_pep'] = read_thru_pep + orf_dict['stop_codons'] = ','.join(stop_codons) + print >> sys.stdout, "fusions_with_orfs: %d %s\n matched_orfs: %d" % (len(fusions_with_orfs),fusions_with_orfs,len(matched_orfs)) + ## Alignments 3 columns, seq columns padded out to longest seq, UPPERCASE_match diffs lowercase + ### defuse_id pre_split_seq post_split_seq + ### trinity_id pre_split_seq post_split_seq + ## Transcripts alignment output + ## Peptide alignment output + ## Write reports + ## OS03_Matched_Rev.csv + ## "count","gene1","gene2","breakpoint","fusion","Trinity_transcript_ID","Trinity_transcript","ID1","protein" + if options.transcripts and options.matched: + #match_fields = ['ordinal','gene_name1','gene_name2','fwd_seq'] + outputMatchFile = open(options.matched,'w') + #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"]) + 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"]) + for i,fusion in enumerate(fusions): + if len(fusion['transcripts']) > 0: + for tx_id in fusion['transcripts'].keys(): + if tx_id in transcript_orfs: + for orf_dict in transcript_orfs[tx_id]: + if 'tx_seq' not in orf_dict: + print >> sys.stderr, "orf_dict %s" % orf_dict + #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']] + 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']] + print >> outputMatchFile, '\t'.join(fields) + outputMatchFile.close() + if options.transcripts and options.transcript_alignment: + if outputTxFile: + id_fields = ['gene_name1','alignments1','gene_name2','alignments2','span_count','probability','gene_chromosome1','gene_location1','gene_chromosome2','gene_location2','fusion_type','Transcript','Protein','flags'] + fa_width = 80 + for i,fusion in enumerate(fusions): + if len(fusion['transcripts']) > 0: + alignments1 = "%s%s%s" % (fusion['genomic_strand1'], fusion['gene_strand1'], fusion['gene_align_strand1']) + alignments2 = "%s%s%s" % (fusion['genomic_strand2'], fusion['gene_strand2'], fusion['gene_align_strand2']) + 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']) + fusion_id = "%s (%s) %s" % (i + 1,alignments,' '.join([str(fusion[x]) for x in report_fields])) + for tx_id in fusion['transcripts'].keys(): + m1 = fusion['transcripts'][tx_id]['match1'] + f_seq1 = fusion['split_seqs'][0][:-m1].lower() + fusion['split_seqs'][0][-m1:] + t_seq1 = fusion['transcripts'][tx_id]['seq1'][:-m1].lower() + fusion['transcripts'][tx_id]['seq1'][-m1:] + if len(f_seq1) > len(t_seq1): + t_seq1 = t_seq1.rjust(len(f_seq1),'.') + elif len(f_seq1) < len(t_seq1): + f_seq1 = f_seq1.rjust(len(t_seq1),'.') + m2 = fusion['transcripts'][tx_id]['match2'] + f_seq2 = fusion['split_seqs'][1][:m2] + fusion['split_seqs'][1][m2:].lower() + t_seq2 = fusion['transcripts'][tx_id]['seq2'][:m2] + fusion['transcripts'][tx_id]['seq2'][m2:].lower() + if len(f_seq2) > len(t_seq2): + t_seq2 = t_seq2.ljust(len(f_seq2),'.') + elif len(f_seq2) < len(t_seq2): + f_seq2 = f_seq2.ljust(len(t_seq2),'.') + 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))) + 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))) + """ + if options.peptides and options.orf_alignment: + pass + """ + print >> outputFile,"%s\t%s" % ('#','\t'.join([report_colnames[x] for x in report_fields])) + for i,fusion in enumerate(fusions): + print >> outputFile,"%s\t%s" % (i + 1,'\t'.join([str(fusion[x]) for x in report_fields])) + +if __name__ == "__main__" : __main__() +