def collapse_bed(self,tmp_bed,job_name,ext_bp):
msg = 'sorting bed file ... @ %s' % job_name
lib_utils.msgout('notice', msg)
if self.logger: self.logger.info(msg)
tmp_so_bed = os.path.join(self.work_dir, 'refGene_e%d_so.bed' % ext_bp)
# sort
lib_utils.sort_tsv_by_col2(tmp_bed, [1, 2, 3], ['V', 'n', 'n'], True, tmp_so_bed)
msg = 'merging exon coordinates overlapped each other... @ %s' % job_name
lib_utils.msgout('notice', msg)
if self.logger: self.logger.info(msg)
# merge boundaries if any overlapped
fp = open(tmp_so_bed, 'r')
fp2 = open(self.bed_fn, 'w')
chromp, e1p, e2p, annotp = fp.next().rstrip().split('\t')
e1p = int(e1p)
e2p = int(e2p)
wrapup = 1;
merge = 2
fp.seek(0)
for i in fp:
chrom, e1, e2, annot = i.rstrip().split('\t')
e1 = int(e1)
e2 = int(e2)
if chrom == chromp:
if e2p < e1:
action = wrapup
else:
action = merge
else:
action = wrapup
if action == wrapup:
fp2.write('%s\t%d\t%d\t%s\n' % (chromp, e1p, e2p, annotp))
chromp, e1p, e2p, annotp = chrom, e1, e2, annot
elif action == merge:
if e2p < e2:
e2p = e2
annotp += '|%s' % annot
fp2.write('%s\t%d\t%d\t%s\n' % (chromp, e1p, e2p, annotp))
fp.close()
fp2.close()
os.unlink(tmp_so_bed)
msg = 'done. @ %s' % job_name
lib_utils.msgout('notice', msg)
if self.logger: self.logger.info(msg)
def gdna_to_vcf(self, mutalyzer_batch_outfn):
if not os.path.exists(mutalyzer_batch_outfn):
raise RuntimeError('check if input file [%s] exists'%\
mutalyzer_batch_outfn)
cHgvs = Hgvs2()
cHgvs.load_resource()
fp = open(mutalyzer_batch_outfn, 'r')
fp.next()
gdna_cache = {}
for mutalyzer in fp:
mut = mutalyzer.split('\t')
if mut[1].strip(): continue
gdna = mut[2].strip()
variants = cHgvs.gdna_to_vcf(gdna)
if variants:
gdna_cache[mut[0].strip()] = variants
fp.close()
self.out_vcf = lib_utils.file_tag(self.tsv, None, 'vcf')
tmp_vcf = self.out_vcf + '.tmp'
fpw = open(tmp_vcf, 'w')
self._write_vcf_head(fpw)
qual = 100
filter = 'PASS'
rsid = '.'
for cvt in self._iterfile():
if self.may_pass(cvt): continue
if cvt.nt_change not in gdna_cache: continue
for chrom, pos, ref, alt in gdna_cache[cvt.nt_change]:
if len(ref) > 100 or len(alt) > 100: continue
info = 'cDNA=%s;' % cvt.nt_change
info += 'VC=%s;' % self.determine_vclass(cvt.rep_class)
info += 'SRC=%s;' % cvt.source
info += 'UPD=%s;' % cvt.last_upd
info += 'URL=%s' % cvt.url
if chrom.startswith('chr'):
if chrom.startswith('chrM'): chrom = 'MT'
else: chrom = chrom[3:]
cols = [chrom, pos, rsid, ref, alt, qual, filter, info]
fpw.write('%s\n' % lib_utils.joined(cols, '\t'))
fpw.close()
lib_utils.sort_tsv_by_col2(tmp_vcf,[1,2],\
['V','n'],False,self.out_vcf)
os.unlink(tmp_vcf)
def rank_pheno_gene(self):
job_name = 'rank_pheno_gene'
msg = 'selecting genes matched by patient phenotypes ... [%s;%s]'%(job_name,self.hpo_query)
lib_utils.msgout('notice',msg); self.logger.info(msg)
tmp_fn = '%s.tmp' % self.gene_rank_fn
fp2=open(tmp_fn,'w')
fp2.write('#gene\tphenotypic_score\n')
for gene,cPhenoGene in self.pheno_dmg.iteritems():
fp2.write('%s\t%g\n'%(gene,cPhenoGene.score))
fp2.close()
lib_utils.sort_tsv_by_col2(tmp_fn,[2],['gr'],False,self.gene_rank_fn)
msg = 'done. [%s]'%job_name
os.unlink(tmp_fn)
lib_utils.msgout('notice',msg); self.logger.info(msg)
def convert_node2gene(FinalNodeScores, PerturbedGenes, dProtein2gene,
lnkProteins, rank_fn):
nodeScores, dangledScores = FinalNodeScores
cPerturbedGenes, dangledGenes = PerturbedGenes
rank_fn2 = lib_utils.file_tag2(rank_fn, 'tmp', None)
fp2 = lib_utils.open2(rank_fn2, 'w')
fp2.write('#gene\tpredicted_score[-1/log10(x)]\tseed_score\n')
for n, protein in enumerate(lnkProteins):
seed_score = 0.
gene = protein
genetic_dmg_score = 0.
if protein in dProtein2gene:
gene = dProtein2gene[protein]
if gene in cPerturbedGenes:
seed_score = cPerturbedGenes[gene].score
genetic_dmg_score = cPerturbedGenes[gene].gdmg
pred_score = 0.
if nodeScores[n] > 0:
pred_score = -1. / math.log10(nodeScores[n])
if genetic_dmg_score > 0.:
fp2.write('%s\t%g\t%g\n' % (gene, pred_score, seed_score))
#add dangled node score
for n, gene in enumerate(dangledGenes):
pred_score = 0.
if dangledScores[n] > 0:
pred_score = -1. / math.log10(dangledScores[n])
if cPerturbedGenes[gene].gdmg > 0.:
fp2.write('%s\t%g\t%g\n' %
(gene, pred_score, cPerturbedGenes[gene].score))
fp2.close()
#sort by score
lib_utils.sort_tsv_by_col2(rank_fn2, [2], ['gr'], False, rank_fn)
os.unlink(rank_fn2)
def _preproces(self, min_go_score=0.5):
#to get temp dir
tmpD = os.path.join(os.path.dirname(self.inname), 'tmp')
if not os.path.exists(tmpD):
os.makedirs(tmpD)
self.uniprot_to_gene()
inname_g = self.inname + '.gene'
fp2 = open(inname_g, 'w')
#convert uniprot to hgnc
for entry in self._iterfile(
): #uniprot1, uniprot2, score=(BP+MF+CC)/3, denominator (1<=x<=3)
if float(entry.score) >= min_go_score:
gene1 = self.uni2gene[entry.prod1]
gene2 = self.uni2gene[entry.prod2]
fp2.write('%s\t%s\t%s\n'%('\t'.join(sorted([gene1,gene2])),\
entry.score,entry.denominator))
fp2.close()
#sorting
inname_gso = inname_g + '.so'
lib_utils.sort_tsv_by_col2(inname_g, [1, 2, 3], ['V', 'V', 'g'], False,
inname_gso, tmpD) #temp dir
#take max funSim for each pair
fp = open(inname_gso, 'r')
j = fp.next().strip().split('\t')
prev_pair = '%s\t%s' % (j[0], j[1])
mx_score1 = 0.
mx_denom1 = 0
mx_score2 = 0.
mx_denom2 = 0
fp.close()
self.inname = inname_gso
fp2 = open(inname_g, 'w')
for entry in self._iterfile():
pair = '%s\t%s' % (entry.prod1, entry.prod2)
if pair != prev_pair: #wraup prev
if mx_denom2 > 0:
fp2.write('%s\t%g\t%d\n' %
(prev_pair, mx_score2, mx_denom2))
elif mx_denom1 > 0:
fp2.write('%s\t%g\t%d\n' %
(prev_pair, mx_score1, mx_denom1))
prev_pair = pair
mx_score1 = 0.
mx_denom1 = 0
mx_score2 = 0.
mx_denom2 = 0
score = float(entry.score)
denominator = int(entry.denominator)
if denominator > 1:
if score > mx_score2:
mx_score2 = score
mx_denom2 = denominator
else:
if score > mx_score1:
mx_score1 = score
mx_denom1 = denominator
#don't forget the last entries
if mx_denom2 > 0:
fp2.write('%s\t%g\t%d\n' % (prev_pair, mx_score2, mx_denom2))
elif mx_denom1 > 0:
fp2.write('%s\t%g\t%d\n' % (prev_pair, mx_score1, mx_denom1))
fp2.close()
self.inname = inname_g
os.unlink(inname_gso)
os.system('rm -rf %s' % tmpD)
def convert_node2gene(self):
'''
for only gt_dmg genes, print out gene, harmonic score, and seed score
'''
rank_fn_tmp = '%s.tmp' % self.dv.gene_rank_fn
fp2 = lib_utils.open2(rank_fn_tmp, 'w')
fp2.write(
'#gene\tpredicted_score\tseed_score\tgt_dmg_score\tpheno_score\tcontain_known_pathogenic\n'
)
genes_printed = {}
#browsing each node in the whole (original) ppi network
for n, protein in enumerate(self.Prots):
seed_score = 0.
gene = protein
#check if this node (restart value) was assigned previously
if protein in self.dProt2Gene:
gene = self.dProt2Gene[protein]
if gene in self.dv.gene_dmg:
seed_score = self.dv.gene_dmg[gene][0]
#to get harmonic score and save into dv.gene_dmg
pred_score = 0.
if self.harmonic_sc[n][0] > 0.:
pred_score = self.harmonic_sc[n][0]
if gene in self.dv.gene_dmg:
self.dv.gene_dmg[gene][1] = pred_score
#NOTE that print only a gene having at one mutation
if (not self.dv.gt_dmg) or \
(gene in self.dv.gt_dmg and self.dv.gt_dmg[gene].score>0.):
pheno_sc = 0.
if gene in self.dv.pheno_dmg:
pheno_sc = self.dv.pheno_dmg[gene].score
if self.dv.vknown:
if gene in self.dv.vknown_genes: is_vknown = 'Y'
else: is_vknown = 'N'
else: is_vknown = 'NA'
if gene in genes_printed:
gene2 = '%s|%s' % (gene, protein)
else:
gene2 = gene
genes_printed[gene] = True
fp2.write('%s\t%g\t%g\t%g\t%g\t%s\n'%\
(gene2,pred_score,seed_score,\
self.dv.gt_dmg[gene].score,pheno_sc,is_vknown))
#repeat the same procedure to dangled nodes
for n, gene in enumerate(self.dangledGenes):
self.dv.gene_dmg[gene][1] = self.harmonic_dng_sc[n][0]
if (not self.dv.gt_dmg) or \
(gene in self.dv.gt_dmg and self.dv.gt_dmg[gene].score>0.):
pheno_sc = 0.
if gene in self.dv.pheno_dmg:
pheno_sc = self.dv.pheno_dmg[gene].score
if self.dv.vknown:
if gene in self.dv.vknown_genes: is_vknown = 'Y'
else: is_vknown = 'N'
else: is_vknown = 'NA'
fp2.write('%s\t%g\t%g\t%s\t%g\t%s\n'%\
(gene,self.dv.gene_dmg[gene][1],self.dv.gene_dmg[gene][0],\
self.dv.gt_dmg[gene].score,pheno_sc,is_vknown))
fp2.close()
#sort by score
lib_utils.sort_tsv_by_col2(\
rank_fn_tmp, [2], ['gr'], False, self.dv.gene_rank_fn)
os.unlink(rank_fn_tmp)
def create_bed(self, ext_bp=0, reuse=False):
job_name = 'RefGeneUcscTB.create_bed'
self.bed_fn = os.path.join(self.work_dir,
'refGene_e%d_so_merged.bed' % ext_bp)
msg = 'creating a bed file[%s] containing RefGene coding region (cmpl/incmpl/unk) @ %s' % (
self.bed_fn, job_name)
lib_utils.msgout('notice', msg)
if self.logger: self.logger.info(msg)
if reuse and lib_utils.check_if_file_valid(self.bed_fn):
msg = 'reuse bed file [%s] generated previously @ %s' % (
self.bed_fn, job_name)
lib_utils.msgout('notice', msg)
if self.logger: self.logger.info(msg)
return self.bed_fn
#to get a working directory
tmp_bed = os.path.join(self.work_dir, 'refGene_e%d.bed' % ext_bp)
fp = open(self.refGene_fn, 'r')
fp2 = open(tmp_bed, 'w')
for i in fp:
j = i.rstrip().split('\t')
chrom = j[2]
for e1, e2 in zip(j[9].split(',')[:-1], j[10].split(',')[:-1]):
e1_ext = int(e1) - ext_bp
e2_ext = int(e2) + ext_bp
fp2.write('%s\t%d\t%d\t%s;%s\n' %
(chrom, e1_ext, e2_ext, j[12], j[1]))
fp2.close()
fp.close()
msg = 'sorting bed file ... @ %s' % job_name
lib_utils.msgout('notice', msg)
if self.logger: self.logger.info(msg)
tmp_so_bed = os.path.join(self.work_dir, 'refGene_e%d_so.bed' % ext_bp)
#sort
lib_utils.sort_tsv_by_col2(tmp_bed, [1, 2, 3], ['V', 'n', 'n'], True,
tmp_so_bed)
msg = 'merging exon coordinates overlapped each other... @ %s' % job_name
lib_utils.msgout('notice', msg)
if self.logger: self.logger.info(msg)
#merge boundaries if any overlapped
fp = open(tmp_so_bed, 'r')
fp2 = open(self.bed_fn, 'w')
chromp, e1p, e2p, annotp = fp.next().rstrip().split('\t')
e1p = int(e1p)
e2p = int(e2p)
wrapup = 1
merge = 2
fp.seek(0)
for i in fp:
chrom, e1, e2, annot = i.rstrip().split('\t')
e1 = int(e1)
e2 = int(e2)
if chrom == chromp:
if e2p < e1: action = wrapup
else: action = merge
else: action = wrapup
if action == wrapup:
fp2.write('%s\t%d\t%d\t%s\n' % (chromp, e1p, e2p, annotp))
chromp, e1p, e2p, annotp = chrom, e1, e2, annot
elif action == merge:
if e2p < e2:
e2p = e2
annotp += '|%s' % annot
fp2.write('%s\t%d\t%d\t%s\n' % (chromp, e1p, e2p, annotp))
fp.close()
fp2.close()
os.unlink(tmp_bed)
os.unlink(tmp_so_bed)
msg = 'done. @ %s' % job_name
lib_utils.msgout('notice', msg)
if self.logger: self.logger.info(msg)
return self.bed_fn
def reformat_go_sim_fns(go_sim_fns,
out_fn,
method_id=1): #method_id (1) means SimRel
suflabs = ['BP', 'MF', 'CC']
fp2 = lib_utils.open2(out_fn, 'w')
v = 0
for key, go_sim_fn in go_sim_fns.iteritems(): #BP,MF,CC
print 'appending root node at the end of [%s]' % go_sim_fn
suflab = suflabs[v]
fp = lib_utils.open2(go_sim_fn, 'r')
go_sim_fn2 = lib_utils.file_tag2(go_sim_fn, 'category', None)
fp.next() #strip off head
for i in fp:
j = i.rstrip().split('\t')
if len(j) == 2:
j.append('-1.')
fp2.write('%s\t%s\n' %
('\t'.join(j), suflab)) #uniprot1,uniprot2,score,BP
fp.close()
print 'done.'
v += 1
fp2.close()
print 'sorting...'
#to get temporary file to sort
out_fn2 = lib_utils.file_tag2(out_fn, 'sort', None)
temp_sort_dir, _, _, _ = lib_utils.separateDirFn2(out_fn)
lib_utils.sort_tsv_by_col2(out_fn, [1, 2, 4], ['V', 'V', 'V'],
False,
out_fn2,
temp_dir=temp_sort_dir)
os.rename(out_fn2, out_fn)
print 'done.'
#groupping
print 'collapsing GO sim scores to make the format easier to import SQL [%s] ...' % out_fn
out_fn2 = lib_utils.file_tag2(out_fn, 'dense', None)
fp2 = lib_utils.open2(out_fn2, 'w')
#heads = '#uniprot1\tuniprot2\tscore_mode\tBP\tMF\tCC\tmethod_id'
#fp2.write('%s\n'%heads)
fp = lib_utils.open2(out_fn, 'r')
visit1 = True
idx = {'BP': 0, 'MF': 1, 'CC': 2}
prev_key = None
gosim_holder = ['-1', '-1', '-1'] #-1 means N/A
for i in fp:
prot1, prot2, score, go_class = i.rstrip().split('\t')
key = '%s\t%s' % (prot1, prot2)
if key != prev_key:
if visit1:
visit1 = False
else: #wrap up
fp2.write('%s\t%s\t%d\n' %
(prev_key, '\t'.join(gosim_holder), method_id))
gosim_holder = ['-1', '-1', '-1']
gosim_holder[idx[go_class]] = score
prev_key = key
else: #keep storing values
gosim_holder[idx[go_class]] = score
fp.close()
#don't forget the last entry
fp2.write('%s\t%s\t%d\n' % (prev_key, '\t'.join(gosim_holder), method_id))
fp2.close()
os.rename(out_fn2, out_fn)
print 'done.'
