def detectBp(range1, range2, blockSize, assembly='hg19'): # process coordinate range1 = mygenome.locus(range1) range2 = mygenome.locus(range2) # fetch sequence seq1 = range1.nibFrag('/data1/Sequence/ucsc_%s' % assembly, blockSize,0) seq2 = range2.nibFrag('/data1/Sequence/ucsc_%s' % assembly, 0,blockSize) # generate block combination outFile = open('/EQL2/RNASeq_LymphNK/bpTemplate.fa','w') for i in range(len(seq1)-blockSize+1): for j in range(len(seq2)-blockSize+1): outFile.write('>seq1:%s-%s|seq2:%s-%s\n%s%s\n' % (i,i+blockSize,j,j+blockSize, seq1[i:i+blockSize], seq2[j:j+blockSize])) outFile.close() # run bowtie print 'building bowtie index' os.system('bowtie-build -q -f /EQL2/RNASeq_LymphNK/bpTemplate.fa /data1/Sequence/bowtie/bpTemplate')
def process_bp(inFileName,outFileName,regionL): result = mygsnap.gsnapFile(inFileName,True) outFile = open(outFileName, 'w') outFile.write('browser full knownGene\n') outFile.write('track name="%s" visibility=2\n' % inFileName) for rL in result: if not (rL[0].nLoci==1 and rL[1].nLoci==1 and rL[0].pairRel=='concordant'): raise Exception locL = [mygenome.locus(rL[0].matchL()[0].segL[0][2]), mygenome.locus(rL[1].matchL()[0].segL[0][2])] flag = False for loc in locL: for region in regionL: if loc.overlap(region) > 0: flag = True if flag: print '^%s.*%s$\n' % (rL[0].seq(),mybasic.rc(rL[1].seq())), for loc in locL: outFile.write('%s\t%s\t%s\n' % (loc.chrom,loc.chrSta,loc.chrEnd))
def process_bed(inFileName, outFileName, coordH): result = mygsnap.gsnapFile(inFileName, True) outFile = open(outFileName, 'w') count_all = 0 count_strand = 0 outFile.write('browser full knownGene\n') outFile.write('track name="targeted" visibility=2\n') for rL in result: if not (rL[0].nLoci == 1 and rL[1].nLoci == 1 and rL[0].pairRel == 'unpaired'): raise Exception locL = [ mygenome.locus(rL[0].matchL()[0].segL[0][2]), mygenome.locus(rL[1].matchL()[0].segL[0][2]) ] for loc in locL: loc.chrSta += coordH[loc.chrom][1] - 1 loc.chrEnd += coordH[loc.chrom][1] - 1 loc.chrom = coordH[loc.chrom][0] for loc in locL: outFile.write('%s\t%s\t%s\n' % (loc.chrom, loc.chrSta, loc.chrEnd))
def process_bed(inFileName,outFileName,coordH): result = mygsnap.gsnapFile(inFileName,True) outFile = open(outFileName, 'w') count_all = 0 count_strand = 0 outFile.write('browser full knownGene\n') outFile.write('track name="targeted" visibility=2\n') for rL in result: if not (rL[0].nLoci==1 and rL[1].nLoci==1 and rL[0].pairRel=='unpaired'): raise Exception locL = [mygenome.locus(rL[0].matchL()[0].segL[0][2]), mygenome.locus(rL[1].matchL()[0].segL[0][2])] for loc in locL: loc.chrSta += coordH[loc.chrom][1] -1 loc.chrEnd += coordH[loc.chrom][1] -1 loc.chrom = coordH[loc.chrom][0] for loc in locL: outFile.write('%s\t%s\t%s\n' % (loc.chrom,loc.chrSta,loc.chrEnd))
def process_bp(inFileName,outFileName,coordH,regionL): result = mygsnap.gsnapFile(inFileName,True) outFile = open(outFileName, 'w') outFile.write('browser full knownGene\n') outFile.write('track name="%s" visibility=2\n' % inFileName) for rL in result: if not (rL[0].nLoci==1 and rL[1].nLoci==1 and rL[0].pairRel=='unpaired'): raise Exception locL = [mygenome.locus(rL[0].matchL()[0].segL[0][2]), mygenome.locus(rL[1].matchL()[0].segL[0][2])] for loc in locL: loc.chrSta += coordH[loc.chrom][1] -1 loc.chrEnd += coordH[loc.chrom][1] -1 loc.chrom = coordH[loc.chrom][0] flag = False for loc in locL: for region in regionL: if loc.overlap(region) > 0: flag = True if flag: print '^%s.*%s$\n' % (rL[0].seq(),mybasic.rc(rL[1].seq())), for loc in locL: outFile.write('%s\t%s\t%s\n' % (loc.chrom,loc.chrSta,loc.chrEnd))
def detectBp(range1, range2, blockSize, assembly='hg19'): # process coordinate range1 = mygenome.locus(range1) range2 = mygenome.locus(range2) # fetch sequence seq1 = range1.nibFrag('/data1/Sequence/ucsc_%s' % assembly, blockSize, 0) seq2 = range2.nibFrag('/data1/Sequence/ucsc_%s' % assembly, 0, blockSize) # generate block combination outFile = open('/EQL2/RNASeq_LymphNK/bpTemplate.fa', 'w') for i in range(len(seq1) - blockSize + 1): for j in range(len(seq2) - blockSize + 1): outFile.write('>seq1:%s-%s|seq2:%s-%s\n%s%s\n' % (i, i + blockSize, j, j + blockSize, seq1[i:i + blockSize], seq2[j:j + blockSize])) outFile.close() # run bowtie print 'building bowtie index' os.system( 'bowtie-build -q -f /EQL2/RNASeq_LymphNK/bpTemplate.fa /data1/Sequence/bowtie/bpTemplate' )
def __init__(self,segL): # take newline- and tab-delimited list ''' __init__ ''' self.segL = segL self.locusL = [mygenome.locus(s[2]) for s in segL]
def main(inGsnapFileName,outReportFileName,sampN,geneNL=[],overlap=10): eiH, ei_keyH, juncInfoH, ei_cntH = loadAnnot(geneNL) print 'Finished loading refFlat' result = mygsnap.gsnapFile(inGsnapFileName,False) count = 0 for r in result: if r.nLoci != 1: continue match = r.matchL()[0] for seg in match.segL: loc = mygenome.locus(seg[2]) if loc.chrSta + overlap > loc.chrEnd - overlap: continue cnt_s = findCut(ei_cntH[loc.chrom], ei_keyH[loc.chrom], loc.chrSta + overlap - 1) cnt_e = findCut(ei_cntH[loc.chrom], ei_keyH[loc.chrom], loc.chrEnd - overlap) if cnt_e < 1: ## no junction overlaps continue elif cnt_s != cnt_e: # overlapping junction exists pos_min = bisect.bisect_right(ei_keyH[loc.chrom], loc.chrSta + overlap - 1) - 1 pos_max = bisect.bisect_right(ei_keyH[loc.chrom], loc.chrEnd - overlap) for pos in range(pos_min, pos_max): if loc.chrSta+overlap <= ei_keyH[loc.chrom][pos] <= loc.chrEnd-overlap: eiH[loc.chrom][ei_keyH[loc.chrom][pos]] += 1 # count += 1 # # if count % 10000 == 0: # print count outReportFile = open(outReportFileName,'w') for chrom in ei_keyH.keys(): for e in ei_keyH[chrom]: if eiH[chrom][e]==[]: continue outReportFile.write('%s\t%s\t%s\t%s\n' % (sampN, '%s:%s' % (chrom,e), ','.join(juncInfoH[chrom][e]), eiH[chrom][e]))
def process_bp(inFileName,outFileName,regionL): result = mygsnap.gsnapFile(inFileName,True) outFile = open(outFileName, 'w') outFile.write('browser full knownGene\n') outFile.write('track name="%s" visibility=2\n' % inFileName) for rL in result: if not (rL[0].nLoci==1 and rL[1].nLoci==1 and rL[0].pairRel=='concordant'): raise Exception if int(rL[0].pairInfo()[0]) < 76: continue locL = [mygenome.locus(rL[0].matchL()[0].segL[0][2]), mygenome.locus(rL[1].matchL()[0].segL[0][2])] flag = False for loc in locL: for region in regionL: if loc.overlap(region) > 0: flag = True if flag: # print '^%s.*%s$\n' % (rL[0].seq(),mybasic.rc(rL[1].seq())), # for loc in locL: # outFile.write('%s\t%s\t%s\n' % (loc.chrom,loc.chrSta,loc.chrEnd)) if locL[0].chrEnd < locL[1].chrSta: outFile.write('%s\t%s\t%s\n' % (loc.chrom,locL[0].chrEnd,locL[1].chrSta)) else: outFile.write('%s\t%s\t%s\n' % (loc.chrom,locL[1].chrEnd,locL[0].chrSta))
def main(inGsnapFileName,outReportFileName,sampN,geneNL=[],overlap=10): eiH, ei_keyH, juncInfoH = loadAnnot(geneNL) print 'Finished loading refFlat' result = mygsnap.gsnapFile(inGsnapFileName,False) count = 0 for r in result: if r.nLoci != 1: continue match = r.matchL()[0] for seg in match.segL: loc = mygenome.locus(seg[2]) cursor.execute('select 1 from temp_table where chrom="%s" and pos>=%s and pos<=%s' % (loc.chrom,loc.chrSta+overlap,loc.chrEnd-overlap)) if cursor.fetchone(): eiH[loc.chrom][pos] += 1 count += 1 if count % 10000 == 0: print count outReportFile = open(outReportFileName,'w') for chrom in ei_keyH.keys(): for e in ei_keyH[chrom]: if eiH[chrom][e]==[]: continue outReportFile.write('%s\t%s\t%s\t%s\n' % (sampN, '%s:%s' % (chrom,e), ','.join(juncInfoH[chrom][e]), eiH[chrom][e]))
def genKgCompositeModel(outTextFileName, outFaFileName): kgH = mygenome.loadKgByChr() outTextFile = open(outTextFileName, 'w') outFaFile = open(outFaFileName, 'w') for chrNum in range(1, 23) + ['X', 'Y', 'M']: #for chrNum in [1]: chrom = 'chr%s' % chrNum txnLocusL_combined = [] for strand in ['+', '-']: txnLocusL = [ mygenome.locus( '%s:%s-%s%s' % (chrom, h['txnSta'], h['txnEnd'], strand), h['kgId']) for h in filter(lambda x: x['strand'] == strand, kgH[chrom]) ] n_before = len(txnLocusL) txnLocusL = mygenome.mergeLoci(txnLocusL) n_after = len(txnLocusL) #print chrom, strand, n_before, n_after txnLocusL_combined += txnLocusL txnLocusL_combined.sort(lambda x, y: cmp(x.chrEnd, y.chrEnd)) txnLocusL_combined.sort(lambda x, y: cmp(x.chrSta, y.chrSta)) for txnLoc in txnLocusL_combined: exnLocusL = [] for h in filter(lambda x: x['kgId'] in txnLoc.id, kgH[chrom]): for (exnSta, exnEnd) in h['exnList']: exnLocusL.append( mygenome.locus('%s:%s-%s%s' % (chrom, exnSta, exnEnd, h['strand']))) exnLocusL.sort(lambda x, y: cmp(x.chrEnd, y.chrEnd)) exnLocusL.sort(lambda x, y: cmp(x.chrSta, y.chrSta)) exnLocusL = mygenome.mergeLoci(exnLocusL) exnStaL = [str(exnLoc.chrSta) for exnLoc in exnLocusL] exnEndL = [str(exnLoc.chrEnd) for exnLoc in exnLocusL] outTextFile.write('%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\n' % (txnLoc.id, txnLoc.chrom, txnLoc.strand, txnLoc.chrSta, txnLoc.chrEnd, len(exnLocusL), ','.join(exnStaL), ','.join(exnEndL))) outFaFile.write('>%s|%s|%s|%s|%s\n' % (txnLoc.id, txnLoc.chrom, txnLoc.strand, txnLoc.chrSta, txnLoc.chrEnd)) # for exnLoc in exnLocusL: # outFaFile.write(exnLoc.nibFrag()) txnLocCopy = copy.deepcopy( txnLoc) # print whole txn sequence in positive strand txnLocCopy.strand = '+' outFaFile.write(txnLocCopy.nibFrag()) outFaFile.write('\n') outTextFile.close() outFaFile.close()
def exonSkip_proc(inGsnapFileName, outGsnapFileName, outReportFileName, sampN): geneNameH = mygenome.geneNameH() geneSetH = mygenome.geneSetH() geneInfoH = mygenome.geneInfoH(geneNameH, geneSetH) refFlatH = mygenome.loadRefFlatByChr() result = mygsnap.gsnapFile(inGsnapFileName, False) juncHH = {} for r in result: match = r.matchL()[0] if not '(transloc)' in r.pairRel: raise Exception if len(match.segL) != 2: raise Exception splice_type = re.search('splice_type:([^,\t]*)', match.segL[0][3]).group(1) direction = re.search('dir:([^,\t]*)', match.segL[0][3]).group(1) offset = int(re.search('\.\.([0-9]*)', match.segL[0][1]).group(1)) transcript1 = re.search('label_[12]:([^,\t]*)', match.segL[0][3]) gene1 = set() if transcript1: transcript1 = tuple( [x.split('.exon')[0] for x in transcript1.group(1).split('|')]) for t in transcript1: g = mygenome.gene(t, geneNameH, geneSetH, geneInfoH) if g.geneName: gene1.add(g.geneName) else: transcript1 = () transcript2 = re.search('label_[12]:([^,\t]*)', match.segL[1][3]) gene2 = set() if transcript2: transcript2 = tuple( [x.split('.exon')[0] for x in transcript2.group(1).split('|')]) for t in transcript2: g = mygenome.gene(t, geneNameH, geneSetH, geneInfoH) if g.geneName: gene2.add(g.geneName) else: transcript2 = () s1 = match.segL[0][2] s2 = match.segL[1][2] bp1 = re.match('([+-])([^:]+):[0-9]+..([0-9]+)', s1) bp2 = re.match('([+-])([^:]+):([0-9]+)..[0-9]+', s2) if (bp1.group(1), direction) in (('+', 'sense'), ('-', 'antisense')): trans_strand1 = '+' elif (bp1.group(1), direction) in (('+', 'antisense'), ('-', 'sense')): trans_strand1 = '-' else: raise Exception if (bp2.group(1), direction) in (('+', 'sense'), ('-', 'antisense')): trans_strand2 = '+' elif (bp2.group(1), direction) in (('+', 'antisense'), ('-', 'sense')): trans_strand2 = '-' else: raise Exception bp_gene1 = mygenome.locus( '%s:%s-%s%s' % (bp1.group(2), int(bp1.group(3)) - 1, bp1.group(3), trans_strand1)).overlappingGeneL( refFlatH=refFlatH, strand_sensitive=True) bp_gene2 = mygenome.locus( '%s:%s-%s%s' % (bp2.group(2), int(bp2.group(3)) - 1, bp2.group(3), trans_strand2)).overlappingGeneL( refFlatH=refFlatH, strand_sensitive=True) if direction == 'sense': key = (bp1.groups()[1:], bp2.groups()[1:]) transcript = (transcript1, transcript2) gene = (tuple(gene1), tuple(gene2)) bp_gene = (bp_gene1, bp_gene2) elif direction == 'antisense': key = (bp2.groups()[1:], bp1.groups()[1:]) transcript = (transcript2, transcript1) gene = (tuple(gene2), tuple(gene1)) bp_gene = (bp_gene2, bp_gene1) else: raise Exception if key in juncHH: juncHH[key]['match'].append(r) juncHH[key]['seq'].append(r.seq()) juncHH[key]['reg'].append((direction, offset)) else: juncHH[key] = { 'match': [r], 'splice_type': splice_type, 'seq': [r.seq()], 'reg': [(direction, offset)], 'transcript': transcript, 'gene': gene, 'bp_gene': bp_gene } juncKH = juncHH.items() juncKH.sort(lambda x, y: cmp(len(set(y[1]['reg'])), len(set(x[1]['reg'])))) outGsnapFile = open(outGsnapFileName, 'w') outReportFile = open(outReportFileName, 'w') for (key, juncH) in juncKH: if key[0][0] == key[1][0]: type = 'intra' else: type = 'inter' geneInfo1 = [] censusInfo1 = [] for geneName in juncH['gene'][0]: gene = mygenome.gene(geneName, geneNameH, geneSetH, geneInfoH) geneInfo1.append( '%s:%s:%s' % (geneName, gene.getAttr('desc'), gene.getAttr('summary'))) censusInfo1.append('%s:%s:%s:%s' % (gene.getAttr('census_somatic'), gene.getAttr('census_germline'), gene.getAttr('census_mutType'), gene.getAttr('census_translocPartners'))) geneInfo2 = [] censusInfo2 = [] for geneName in juncH['gene'][1]: gene = mygenome.gene(geneName, geneNameH, geneSetH, geneInfoH) geneInfo2.append( '%s:%s:%s' % (geneName, gene.getAttr('desc'), gene.getAttr('summary'))) censusInfo2.append('%s:%s:%s:%s' % (gene.getAttr('census_somatic'), gene.getAttr('census_germline'), gene.getAttr('census_mutType'), gene.getAttr('census_translocPartners'))) outReportFile.write('%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\n' % \ (type, juncH['splice_type'], sampN, ':'.join(key[0]), ':'.join(key[1]), \ ';'.join(juncH['transcript'][0]), ';'.join(juncH['transcript'][1]), ';'.join(juncH['gene'][0]), ';'.join(juncH['gene'][1]), ';'.join(geneInfo1), ';'.join(geneInfo2), \ ';'.join(censusInfo1), ';'.join(censusInfo2), ','.join(juncH['bp_gene'][0]), ','.join(juncH['bp_gene'][1]), \ len(juncH['match']) ,len(set(juncH['seq'])), len(set(juncH['reg'])))) for m in juncH['match']: outGsnapFile.write(m.rawText() + '\n')
def genCompositeModel(outTextFileName,outFaFileName,intronSize=100): geneNameH = mygenome.geneNameH() geneSetH = mygenome.geneSetH() geneInfoH = mygenome.geneInfoH(geneNameH,geneSetH) geneH = mygenome.loadKgByChr() #geneH = mygenome.loadLincByChr(h=geneH) outTextFile = open(outTextFileName, 'w') outFaFile = open(outFaFileName, 'w') for chrNum in range(1,23)+['X','Y','M']: #for chrNum in [1]: chrom = 'chr%s' % chrNum geneH_byChr = filter(lambda x: mygenome.gene(x['geneId'],geneNameH,geneSetH,geneInfoH).geneName in mygenome.TK, geneH[chrom]) txnLocusL_combined = [] for strand in ['+','-']: txnLocusL = [mygenome.locus('%s:%s-%s%s' % (chrom,h['txnSta'],h['txnEnd'],strand),h['geneId']) for h in filter(lambda x: x['strand']==strand, geneH_byChr)] n_before = len(txnLocusL) txnLocusL = mygenome.mergeLoci(txnLocusL) n_after = len(txnLocusL) #print chrom, strand, n_before, n_after txnLocusL_combined += txnLocusL txnLocusL_combined.sort(lambda x,y: cmp(x.chrEnd,y.chrEnd)) txnLocusL_combined.sort(lambda x,y: cmp(x.chrSta,y.chrSta)) for txnLoc in txnLocusL_combined: exnLocusL = [] for h in filter(lambda x: x['geneId'] in txnLoc.id, geneH_byChr): for (exnSta,exnEnd) in h['exnList']: exnLocusL.append(mygenome.locus('%s:%s-%s%s' % (chrom, exnSta, exnEnd, h['strand']))) exnLocusL.sort(lambda x,y: cmp(x.chrEnd,y.chrEnd)) exnLocusL.sort(lambda x,y: cmp(x.chrSta,y.chrSta)) exnLocusL = mygenome.mergeLoci(exnLocusL) exnStaL = [str(exnLoc.chrSta) for exnLoc in exnLocusL] exnEndL = [str(exnLoc.chrEnd) for exnLoc in exnLocusL] outTextFile.write('%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\n' % (txnLoc.id,txnLoc.chrom,txnLoc.strand,txnLoc.chrSta,txnLoc.chrEnd,len(exnLocusL),','.join(exnStaL),','.join(exnEndL))) outFaFile.write('>%s|%s|%s|%s|%s\n' % (txnLoc.id,txnLoc.chrom,txnLoc.strand,txnLoc.chrSta,txnLoc.chrEnd)) for i in range(len(exnLocusL)): exnLocCopy = copy.deepcopy(exnLocusL[i]) exnLocCopy.strand = '+' if i > 0: exnLocCopy.chrSta -= min(intronSize, int((exnLocusL[i].chrSta - exnLocusL[i-1].chrEnd)/2)) if i < len(exnLocusL)-1: exnLocCopy.chrEnd += min(intronSize, int((exnLocusL[i+1].chrSta - exnLocusL[i].chrEnd)/2)) outFaFile.write(exnLocCopy.nibFrag()) outFaFile.write('\n') outTextFile.close() outFaFile.close()
def gsnap_process_junction(inGsnapFileName,outGsnapFileName,outReportFileName,sampN): geneNameH = mygenome.geneNameH() geneSetH = mygenome.geneSetH() geneInfoH = mygenome.geneInfoH(geneNameH,geneSetH) refFlatH = mygenome.loadRefFlatByChr() result = mygsnap.gsnapFile(inGsnapFileName,False) juncHH = {} for r in result: match = r.matchL()[0] if not '(transloc)' in r.pairRel: raise Exception if len(match.segL) != 2: raise Exception splice_type = re.search('splice_type:([^,\t]*)', match.segL[0][3]).group(1) direction = re.search('dir:([^,\t]*)', match.segL[0][3]).group(1) offset = int(re.search('\.\.([0-9]*)', match.segL[0][1]).group(1)) rm = re.search('label_[12]:([^,\t]*)', match.segL[0][3]) gene1 = set() if rm: trans_exon1 = rm.group(1).split('|') for t in trans_exon1: g = mygenome.gene(t.split('.exon')[0],geneNameH,geneSetH,geneInfoH) if g.geneName: gene1.add(g.geneName) else: trans_exon1 = () rm = re.search('label_[12]:([^,\t]*)', match.segL[0][3]) gene2 = set() if rm: trans_exon2 = rm.group(1).split('|') for t in trans_exon2: g = mygenome.gene(t.split('.exon')[0],geneNameH,geneSetH,geneInfoH) if g.geneName: gene2.add(g.geneName) else: trans_exon2 = () s1 = match.segL[0][2] s2 = match.segL[1][2] bp1 = re.match('([+-])([^:]+):[0-9]+..([0-9]+)',s1) bp2 = re.match('([+-])([^:]+):([0-9]+)..[0-9]+',s2) if (bp1.group(1),direction) in (('+','sense'),('-','antisense')): trans_strand1 = '+' elif (bp1.group(1),direction) in (('+','antisense'),('-','sense')): trans_strand1 = '-' else: raise Exception if (bp2.group(1),direction) in (('+','sense'),('-','antisense')): trans_strand2 = '+' elif (bp2.group(1),direction) in (('+','antisense'),('-','sense')): trans_strand2 = '-' else: raise Exception locus1 = mygenome.locus('%s:%s-%s%s' % (bp1.group(2),int(bp1.group(3))-1,bp1.group(3),trans_strand1)) bp_gene1 = list(set(locus1.overlappingGeneL(refFlatH=refFlatH,strand_sensitive=True)).difference(gene1)) locus2 = mygenome.locus('%s:%s-%s%s' % (bp2.group(2),int(bp2.group(3))-2,bp2.group(3),trans_strand2)) bp_gene2 = list(set(locus2.overlappingGeneL(refFlatH=refFlatH,strand_sensitive=True)).difference(gene2)) if direction=='sense': key = (bp1.groups()[1:],bp2.groups()[1:]) trans_exon = (trans_exon1,trans_exon2) gene = (list(gene1),list(gene2)) bp_gene = (bp_gene1,bp_gene2) elif direction=='antisense': key = (bp2.groups()[1:],bp1.groups()[1:]) trans_exon = (trans_exon2,trans_exon1) gene = (list(gene2),list(gene1)) bp_gene = (bp_gene2,bp_gene1) else: raise Exception if key in juncHH: juncHH[key]['match'].append(r) juncHH[key]['seq'].append(r.seq()) juncHH[key]['reg'].append((direction,offset)) else: juncHH[key] = {'match':[r], 'splice_type':splice_type, 'seq':[r.seq()], 'reg':[(direction,offset)], 'trans_exon':trans_exon, 'gene':gene, 'bp_gene':bp_gene} juncKH = juncHH.items() juncKH.sort(lambda x,y: cmp(len(set(y[1]['reg'])),len(set(x[1]['reg'])))) outGsnapFile = open(outGsnapFileName,'w') outReportFile = open(outReportFileName,'w') for (key, juncH) in juncKH: if key[0][0] == key[1][0]: type = 'intra' else: type = 'inter' geneInfo1 = [] censusInfo1 = [] for geneName in juncH['gene'][0]+juncH['bp_gene'][0]: gene = mygenome.gene(geneName,geneNameH,geneSetH,geneInfoH) geneInfo1.append('%s:%s:%s' % (geneName,gene.getAttr('desc'),gene.getAttr('summary'))) censusInfo1.append('%s:%s:%s:%s' % (gene.getAttr('census_somatic'),gene.getAttr('census_germline'),gene.getAttr('census_mutType'),gene.getAttr('census_translocPartners'))) geneInfo2 = [] censusInfo2 = [] for geneName in juncH['gene'][1]+juncH['bp_gene'][1]: gene = mygenome.gene(geneName,geneNameH,geneSetH,geneInfoH) geneInfo2.append('%s:%s:%s' % (geneName,gene.getAttr('desc'),gene.getAttr('summary'))) censusInfo2.append('%s:%s:%s:%s' % (gene.getAttr('census_somatic'),gene.getAttr('census_germline'),gene.getAttr('census_mutType'),gene.getAttr('census_translocPartners'))) outReportFile.write('%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s;%s\t%s;%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\n' % \ (type, juncH['splice_type'], sampN, ':'.join(key[0]), ':'.join(key[1]), \ ','.join(juncH['trans_exon'][0]), ','.join(juncH['trans_exon'][1]), \ ','.join(juncH['gene'][0]), ','.join(juncH['bp_gene'][0]), ','.join(juncH['gene'][1]), ','.join(juncH['bp_gene'][1]), \ ';'.join(geneInfo1), ';'.join(geneInfo2), ';'.join(censusInfo1), ';'.join(censusInfo2), \ len(juncH['match']) ,len(set(juncH['seq'])), len(set(juncH['reg'])))) for m in juncH['match']: outGsnapFile.write(m.rawText()+'\n')
def fusion_proc_annot(inReportFileName, outReportFileName, inCnaGctFileName=None): geneDB = mygenome.getGeneDB() frameInfoH = mygenome.getFrameInfoH() refFlatH = mygenome.loadRefFlatByChr() if inCnaGctFileName: cnaDB = mygenome.tcgaCnaDB(inCnaGctFileName) else: cnaDB = None outReportFile = open(outReportFileName, 'w') for line in open(inReportFileName): (splice_type, sampN, bp1, bp2, teStr1, teStr2, nmatch, nseq, nreg) = line[:-1].split('\t') if inCnaGctFileName: indivId = re.match('.*(TCGA-[0-9]{2}-[0-9]{4}).*', sampN).group(1) geneStatL = [] for (bp, teStr) in ((bp1, teStr1), (bp2, teStr2)): geneS = set() teL = [] for te in teStr.split(','): rm = re.match('(.*)\.exon([0-9]*)/[0-9]*', te) if rm: t = rm.group(1) e = int(rm.group(2)) g = mygenome.gene(t, geneDB=geneDB) if g.geneName: geneS.add(g.geneName) teL.append((t, e)) rm = re.match('([+-])(chr[^:]*):([0-9]*)', bp) bp_geneS = set( mygenome.locus('%s:%s-%s%s' % (rm.group(2), int(rm.group(3)) - 1, rm.group(3), rm.group(1))).overlappingGeneL( refFlatH=refFlatH, strand_sensitive=True)) bp_geneS = bp_geneS.difference(geneS) cnaInfo = [] geneInfo = [] censusInfo = [] goInfoS = set() keggInfoS = set() biocartaInfoS = set() for geneName in list(geneS) + list(bp_geneS): gene = mygenome.gene(geneName, geneDB=geneDB) if cnaDB: cnaInfo.append('%s:%s' % (geneName, cnaDB.query(indivId, geneName))) geneInfo.append( '%s:%s:%s' % (geneName, gene.getAttr('desc'), gene.getAttr('summary'))) censusInfo.append('%s:%s:%s:%s' % (gene.getAttr('census_somatic'), gene.getAttr('census_germline'), gene.getAttr('census_mutType'), gene.getAttr('census_translocPartners'))) goInfoS = goInfoS.union(set(gene.getAttr('go'))) keggInfoS = keggInfoS.union(set(gene.getAttr('kegg'))) biocartaInfoS = biocartaInfoS.union( set(gene.getAttr('biocarta'))) geneStatL.append( (bp1.split(':')[0], bp, teStr, teL, geneS, bp_geneS, cnaInfo, geneInfo, censusInfo, goInfoS, keggInfoS, biocartaInfoS)) (chrom1, bp1, teStr1, teL1, geneS1, bp_geneS1, cnaInfo1, geneInfo1, censusInfo1, goInfoS1, keggInfoS1, biocartaInfoS1) = geneStatL[0] (chrom2, bp2, teStr2, teL2, geneS2, bp_geneS2, cnaInfo2, geneInfo2, censusInfo2, goInfoS2, keggInfoS2, biocartaInfoS2) = geneStatL[1] if chrom1 == chrom2: type = 'intra' else: type = 'inter' frameL = [] for (t1, e1) in teL1: for (t2, e2) in teL2: cons = mygenome.frameCons(t1, e1, t2, e2, frameInfoH) if cons == 'Y': frameL.append('%s.%s-%s.%s:%s' % (t1, e1, t2, e2, cons)) outReportFile.write('%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\n' % \ (sampN, splice_type, type, bp1,bp2, teStr1,teStr2, ','.join(frameL), ','.join(cnaInfo1), ','.join(cnaInfo2), \ '%s;%s' % (','.join(geneS1),','.join(bp_geneS1)), ';'.join(geneInfo1), ';'.join(censusInfo1), \ ';'.join(map(str,goInfoS1)), ';'.join(map(str,keggInfoS1)), ';'.join(map(str,biocartaInfoS1)), '%s;%s' % (','.join(geneS2),','.join(bp_geneS2)), ';'.join(geneInfo2), ';'.join(censusInfo2), \ ';'.join(map(str,goInfoS2)), ';'.join(map(str,keggInfoS2)), ';'.join(map(str,biocartaInfoS2)), nmatch,nseq,nreg))
def genKgCompositeModel(outTextFileName,outFaFileName): kgH = mygenome.loadKgByChr() outTextFile = open(outTextFileName, 'w') outFaFile = open(outFaFileName, 'w') for chrNum in range(1,23)+['X','Y','M']: #for chrNum in [1]: chrom = 'chr%s' % chrNum txnLocusL_combined = [] for strand in ['+','-']: txnLocusL = [mygenome.locus('%s:%s-%s%s' % (chrom,h['txnSta'],h['txnEnd'],strand),h['kgId']) for h in filter(lambda x: x['strand']==strand, kgH[chrom])] n_before = len(txnLocusL) txnLocusL = mygenome.mergeLoci(txnLocusL) n_after = len(txnLocusL) #print chrom, strand, n_before, n_after txnLocusL_combined += txnLocusL txnLocusL_combined.sort(lambda x,y: cmp(x.chrEnd,y.chrEnd)) txnLocusL_combined.sort(lambda x,y: cmp(x.chrSta,y.chrSta)) for txnLoc in txnLocusL_combined: exnLocusL = [] for h in filter(lambda x: x['kgId'] in txnLoc.id, kgH[chrom]): for (exnSta,exnEnd) in h['exnList']: exnLocusL.append(mygenome.locus('%s:%s-%s%s' % (chrom, exnSta, exnEnd, h['strand']))) exnLocusL.sort(lambda x,y: cmp(x.chrEnd,y.chrEnd)) exnLocusL.sort(lambda x,y: cmp(x.chrSta,y.chrSta)) exnLocusL = mygenome.mergeLoci(exnLocusL) exnStaL = [str(exnLoc.chrSta) for exnLoc in exnLocusL] exnEndL = [str(exnLoc.chrEnd) for exnLoc in exnLocusL] outTextFile.write('%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\n' % (txnLoc.id,txnLoc.chrom,txnLoc.strand,txnLoc.chrSta,txnLoc.chrEnd,len(exnLocusL),','.join(exnStaL),','.join(exnEndL))) outFaFile.write('>%s|%s|%s|%s|%s\n' % (txnLoc.id,txnLoc.chrom,txnLoc.strand,txnLoc.chrSta,txnLoc.chrEnd)) # for exnLoc in exnLocusL: # outFaFile.write(exnLoc.nibFrag()) txnLocCopy = copy.deepcopy(txnLoc) # print whole txn sequence in positive strand txnLocCopy.strand = '+' outFaFile.write(txnLocCopy.nibFrag()) outFaFile.write('\n') outTextFile.close() outFaFile.close()
def fusion_proc_annot(inReportFileName,outReportFileName,inCnaGctFileName=None): geneDB = mygenome.getGeneDB() frameInfoH = mygenome.getFrameInfoH() refFlatH = mygenome.loadRefFlatByChr() if inCnaGctFileName: cnaDB = mygenome.tcgaCnaDB(inCnaGctFileName) else: cnaDB = None outReportFile = open(outReportFileName,'w') for line in open(inReportFileName): (splice_type,sampN,bp1,bp2,teStr1,teStr2,nmatch,nseq,nreg) = line[:-1].split('\t') if inCnaGctFileName: indivId = re.match('.*(TCGA-[0-9]{2}-[0-9]{4}).*',sampN).group(1) geneStatL = [] for (bp,teStr) in ((bp1,teStr1),(bp2,teStr2)): geneS = set() teL = [] for te in teStr.split(','): rm = re.match('(.*)\.exon([0-9]*)/[0-9]*',te) if rm: t = rm.group(1) e = int(rm.group(2)) g = mygenome.gene(t,geneDB=geneDB) if g.geneName: geneS.add(g.geneName) teL.append((t,e)) rm = re.match('([+-])(chr[^:]*):([0-9]*)',bp) bp_geneS = set(mygenome.locus('%s:%s-%s%s' % (rm.group(2),int(rm.group(3))-1,rm.group(3),rm.group(1))).overlappingGeneL(refFlatH=refFlatH,strand_sensitive=True)) bp_geneS = bp_geneS.difference(geneS) cnaInfo = [] geneInfo = [] censusInfo = [] goInfoS = set() keggInfoS = set() biocartaInfoS = set() for geneName in list(geneS) + list(bp_geneS): gene = mygenome.gene(geneName,geneDB=geneDB) if cnaDB: cnaInfo.append('%s:%s' % (geneName,cnaDB.query(indivId,geneName))) geneInfo.append('%s:%s:%s' % (geneName,gene.getAttr('desc'),gene.getAttr('summary'))) censusInfo.append('%s:%s:%s:%s' % (gene.getAttr('census_somatic'),gene.getAttr('census_germline'),gene.getAttr('census_mutType'),gene.getAttr('census_translocPartners'))) goInfoS = goInfoS.union(set(gene.getAttr('go'))) keggInfoS = keggInfoS.union(set(gene.getAttr('kegg'))) biocartaInfoS = biocartaInfoS.union(set(gene.getAttr('biocarta'))) geneStatL.append((bp1.split(':')[0],bp,teStr,teL,geneS,bp_geneS,cnaInfo,geneInfo,censusInfo,goInfoS,keggInfoS,biocartaInfoS)) (chrom1,bp1,teStr1,teL1,geneS1,bp_geneS1,cnaInfo1,geneInfo1,censusInfo1,goInfoS1,keggInfoS1,biocartaInfoS1) = geneStatL[0] (chrom2,bp2,teStr2,teL2,geneS2,bp_geneS2,cnaInfo2,geneInfo2,censusInfo2,goInfoS2,keggInfoS2,biocartaInfoS2) = geneStatL[1] if chrom1 == chrom2: type = 'intra' else: type = 'inter' frameL = [] for (t1,e1) in teL1: for (t2,e2) in teL2: cons = mygenome.frameCons(t1,e1, t2,e2, frameInfoH) if cons=='Y': frameL.append('%s.%s-%s.%s:%s' % (t1,e1,t2,e2,cons)) outReportFile.write('%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\n' % \ (sampN, splice_type, type, bp1,bp2, teStr1,teStr2, ','.join(frameL), ','.join(cnaInfo1), ','.join(cnaInfo2), \ '%s;%s' % (','.join(geneS1),','.join(bp_geneS1)), ';'.join(geneInfo1), ';'.join(censusInfo1), \ ';'.join(map(str,goInfoS1)), ';'.join(map(str,keggInfoS1)), ';'.join(map(str,biocartaInfoS1)), '%s;%s' % (','.join(geneS2),','.join(bp_geneS2)), ';'.join(geneInfo2), ';'.join(censusInfo2), \ ';'.join(map(str,goInfoS2)), ';'.join(map(str,keggInfoS2)), ';'.join(map(str,biocartaInfoS2)), nmatch,nseq,nreg))