def exon_graph(depth, refseq, prefix, outdir=os.getcwd(), trans=None, genes=None, threads=0): beds = HGVS(refseq, trans=trans, genes=genes) messages = beds.get_exons() threads = cpu_count() if not int(threads) else int(threads) pool = multiprocessing.Pool(processes=threads) for transcript, trans_messages in messages.iteritems(): pool.apply_async(graph, (depth, trans_messages, outdir, prefix)) pool.close() pool.join()
def __init__(self, reference, trans=None, genes=None):
self.refdb = os.path.join(database_dir, "transdb",
"ncbi_anno_rel104.dbref.db")
reference = os.path.abspath(reference)
self.HGVS = HGVS(self.refdb, reference, trans, genes)
self._dbhandles = list()
dbtitle = defaultdict(float)
for f in glob(os.path.join(database_dir, "*", "*.bedanno.config")):
dbs = AnnoVar(os.path.abspath(f))
t = "\t".join([str(i) for i in sorted(dbs.search_value.values())])
dbtitle[t] = dbs.order
self._dbhandles.append(dbs)
self.dbtitle = "\t".join(
[j for j in sorted(dbtitle.keys(), key=lambda x: dbtitle[x])])
def __init__(self, reference, trans=None, genes=None): self.refdb = os.path.join(database_dir, "transdb", "ncbi_anno_rel104.dbref.db") reference = os.path.abspath(reference) self.HGVS = HGVS(self.refdb, reference, trans, genes) self._dbhandles = list() dbtitle = defaultdict(float) for f in glob(os.path.join(database_dir, "*", "*.bedanno.config")): dbs = AnnoVar(os.path.abspath(f)) t = "\t".join([str(i) for i in sorted(dbs.search_value.values())]) dbtitle[t] = dbs.order self._dbhandles.append(dbs) self.dbtitle = "\t".join([j for j in sorted(dbtitle.keys(), key=lambda x: dbtitle[x])])
def __init__(self, **kwargs):
self.outdir = os.path.abspath(kwargs["indir"])
self.win_len = int(kwargs["correct_win_len"]) or 30
self.shift_len = int(kwargs["correct_shift_len"]) or 25
self.contral_wins = int(100.0 / self.shift_len + 0.5) + 1
chroms = str(kwargs["chrom"]).split(",") if kwargs["chrom"] else None
samples = str(kwargs["sample"]).split(",") if kwargs["sample"] else None
all_samples = set()
contigs = list()
self.cnvdata = defaultdict(dict)
self.sample_win_data = defaultdict(dict)
for cnv_data in glob(os.path.join(self.outdir, "chr*.cnv.args")):
chrom = ".".join(os.path.basename(cnv_data).split(".")[0:-2])
if chroms is not None and chrom not in chroms:
continue
cnvdata = SaveLoad(cnv_data)
cnvdata = cnvdata.load()
contigs.append(chrom)
for sample in cnvdata.keys():
dep_f = os.path.join(self.outdir, sample, "%s.W%iS%i.fixdep.gz" % (chrom, self.win_len, self.shift_len))
if os.path.isfile(dep_f) and os.path.isfile(dep_f + '.tbi'):
self.sample_win_data[chrom][sample] = dep_f
if samples is not None and sample not in samples:
continue
all_samples.add(sample)
self.cnvdata[sample][chrom] = cnvdata[sample]
self.samples = sorted(all_samples)
self.contigs = sorted(contigs, key=lambda x: _chrom_valued(x))
databases = os.path.abspath(kwargs["dbdir"])
t_db = os.path.abspath(kwargs["transdb"]) if "transdb" in kwargs else os.path.join(databases, "transdb",
"ncbi_anno_rel104.dbref.db")
for db in glob(os.path.join(databases, "*", "*.cnvdb.config")):
db = os.path.abspath(db)
dbname = os.path.basename(os.path.dirname(db))
_AnnotationDB[dbname].add(db)
self.reference = os.path.abspath(kwargs["reference"]) if kwargs["reference"] else \
os.path.join(databases, 'aln_db/hg19/hg19_chM_male_mask.fa')
self.DBAnno = CNVAnnotation(self.reference, _AnnotationDB)
self.HGVS = HGVS(t_db)
class BedAnno(object):
def __init__(self, reference, trans=None, genes=None):
self.refdb = os.path.join(database_dir, "transdb",
"ncbi_anno_rel104.dbref.db")
reference = os.path.abspath(reference)
self.HGVS = HGVS(self.refdb, reference, trans, genes)
self._dbhandles = list()
dbtitle = defaultdict(float)
for f in glob(os.path.join(database_dir, "*", "*.bedanno.config")):
dbs = AnnoVar(os.path.abspath(f))
t = "\t".join([str(i) for i in sorted(dbs.search_value.values())])
dbtitle[t] = dbs.order
self._dbhandles.append(dbs)
self.dbtitle = "\t".join(
[j for j in sorted(dbtitle.keys(), key=lambda x: dbtitle[x])])
def __del__(self):
self.HGVS.__del__()
for dbs in self._dbhandles:
dbs.__del__()
def dbanno(self, variation):
dbinfo = defaultdict(set)
for dbs in self._dbhandles:
try:
infos = dbs.fetch(**variation.__dict__)
for info in infos:
for k, v in info.__dict__.iteritems():
if v != ".":
dbinfo[k].add(v)
except Exception:
continue
return dbinfo
def bedanno(self, bedfile, fileout=sys.stdout):
if not (bedfile and os.path.isfile(bedfile)):
raise IOError("Fail to load file: %s" % bedfile)
regions = smart_open(bedfile).readlines()
f_out = smart_open(fileout, 'w')
titles = "Transcript\tgeneSym\tgeneSym\tcHGVS\tProtein\tStand\tExonRegions"
for line in regions:
rows = line.strip().split("\t")
if len(rows) < 3:
f_out.write(line)
try:
chrom = str(rows[0])
start = int(rows[1])
stop = int(rows[2])
except ValueError:
if len(self.dbtitle):
f_out.write("\t".join(rows) +
'\t'.join([titles, self.dbtitle]) + '\n')
else:
f_out.write("\t".join(rows) + '\t' + titles + '\n')
continue
anno_m = self.HGVS.annobed(chrom, start, stop)
for anno in anno_m:
dbinfo = self.dbanno(anno)
rows[0] = str(anno.Chrom)
rows[1] = str(anno.Start)
rows[2] = str(anno.Stop)
trans = str(anno.Transcript)
gene = str(anno.geneSym)
chgvs = str(anno.cHgvs)
protein = str(anno.Protein)
stand = str(anno.Stand)
exons = str(anno.ExonRegions)
anno_message = [
str(i) for i in rows +
[trans, gene, chgvs, protein, stand, exons]
]
for i in self.dbtitle.split("\t"):
if i in dbinfo:
anno_message.append(";".join(dbinfo[i]))
else:
anno_message.append(".")
f_out.write("\t".join(anno_message) + '\n')
f_out.close()
class BedAnno(object):
def __init__(self, reference, trans=None, genes=None):
self.refdb = os.path.join(database_dir, "transdb", "ncbi_anno_rel104.dbref.db")
reference = os.path.abspath(reference)
self.HGVS = HGVS(self.refdb, reference, trans, genes)
self._dbhandles = list()
dbtitle = defaultdict(float)
for f in glob(os.path.join(database_dir, "*", "*.bedanno.config")):
dbs = AnnoVar(os.path.abspath(f))
t = "\t".join([str(i) for i in sorted(dbs.search_value.values())])
dbtitle[t] = dbs.order
self._dbhandles.append(dbs)
self.dbtitle = "\t".join([j for j in sorted(dbtitle.keys(), key=lambda x: dbtitle[x])])
def __del__(self):
self.HGVS.__del__()
for dbs in self._dbhandles:
dbs.__del__()
def dbanno(self, variation):
dbinfo = defaultdict(set)
for dbs in self._dbhandles:
try:
infos = dbs.fetch(**variation.__dict__)
for info in infos:
for k, v in info.__dict__.iteritems():
if v != ".":
dbinfo[k].add(v)
except Exception:
continue
return dbinfo
def bedanno(self, bedfile, fileout=sys.stdout):
if not (bedfile and os.path.isfile(bedfile)):
raise IOError("Fail to load file: %s" % bedfile)
regions = smart_open(bedfile).readlines()
f_out = smart_open(fileout, 'w')
titles = "Transcript\tgeneSym\tgeneSym\tcHGVS\tProtein\tStand\tExonRegions"
for line in regions:
rows = line.strip().split("\t")
if len(rows) < 3:
f_out.write(line)
try:
chrom = str(rows[0])
start = int(rows[1])
stop = int(rows[2])
except ValueError:
if len(self.dbtitle):
f_out.write("\t".join(rows) + '\t'.join([titles, self.dbtitle]) + '\n')
else:
f_out.write("\t".join(rows) + '\t' + titles + '\n')
continue
anno_m = self.HGVS.annobed(chrom, start, stop)
for anno in anno_m:
dbinfo = self.dbanno(anno)
rows[0] = str(anno.Chrom)
rows[1] = str(anno.Start)
rows[2] = str(anno.Stop)
trans = str(anno.Transcript)
gene = str(anno.geneSym)
chgvs = str(anno.cHgvs)
protein = str(anno.Protein)
stand = str(anno.Stand)
exons = str(anno.ExonRegions)
anno_message = [str(i) for i in rows + [trans, gene, chgvs, protein, stand, exons]]
for i in self.dbtitle.split("\t"):
if i in dbinfo:
anno_message.append(";".join(dbinfo[i]))
else:
anno_message.append(".")
f_out.write("\t".join(anno_message) + '\n')
f_out.close()
class CNVAnalysis(object):
global _AnnotationDB
def __init__(self, **kwargs):
self.outdir = os.path.abspath(kwargs["indir"])
self.win_len = int(kwargs["correct_win_len"]) or 30
self.shift_len = int(kwargs["correct_shift_len"]) or 25
self.contral_wins = int(100.0 / self.shift_len + 0.5) + 1
chroms = str(kwargs["chrom"]).split(",") if kwargs["chrom"] else None
samples = str(kwargs["sample"]).split(",") if kwargs["sample"] else None
all_samples = set()
contigs = list()
self.cnvdata = defaultdict(dict)
self.sample_win_data = defaultdict(dict)
for cnv_data in glob(os.path.join(self.outdir, "chr*.cnv.args")):
chrom = ".".join(os.path.basename(cnv_data).split(".")[0:-2])
if chroms is not None and chrom not in chroms:
continue
cnvdata = SaveLoad(cnv_data)
cnvdata = cnvdata.load()
contigs.append(chrom)
for sample in cnvdata.keys():
dep_f = os.path.join(self.outdir, sample, "%s.W%iS%i.fixdep.gz" % (chrom, self.win_len, self.shift_len))
if os.path.isfile(dep_f) and os.path.isfile(dep_f + '.tbi'):
self.sample_win_data[chrom][sample] = dep_f
if samples is not None and sample not in samples:
continue
all_samples.add(sample)
self.cnvdata[sample][chrom] = cnvdata[sample]
self.samples = sorted(all_samples)
self.contigs = sorted(contigs, key=lambda x: _chrom_valued(x))
databases = os.path.abspath(kwargs["dbdir"])
t_db = os.path.abspath(kwargs["transdb"]) if "transdb" in kwargs else os.path.join(databases, "transdb",
"ncbi_anno_rel104.dbref.db")
for db in glob(os.path.join(databases, "*", "*.cnvdb.config")):
db = os.path.abspath(db)
dbname = os.path.basename(os.path.dirname(db))
_AnnotationDB[dbname].add(db)
self.reference = os.path.abspath(kwargs["reference"]) if kwargs["reference"] else \
os.path.join(databases, 'aln_db/hg19/hg19_chM_male_mask.fa')
self.DBAnno = CNVAnnotation(self.reference, _AnnotationDB)
self.HGVS = HGVS(t_db)
def call_cnvs(self, sample):
pool = Pool(processes=cpu(use_mem=2147483648, cpu_limit=len(self.contigs)))
for chrom in self.contigs:
dep_data = self.cnvdata[sample][chrom].data
ploid = self.cnvdata[sample][chrom].ploid
if ploid < 1 or not len(dep_data):
continue
best_p = self.cnvdata[sample][chrom].best_probability
trials = self.cnvdata[sample][chrom].trials
regions = self.cnvdata[sample][chrom].regions
output = os.path.join(self.outdir, sample, "%s.cnv" % chrom)
hmm_cnv(dep_data, regions, best_p, trials, ploid, output, self.contral_wins)
pool.apply_async(hmm_cnv, (dep_data, regions, best_p, trials, ploid, output, self.contral_wins))
pool.close()
pool.join()
def z_score(self, chrom, start, stop, sample):
dep_data = list()
deps = list()
dep_handle = pysam.Tabixfile(self.sample_win_data[chrom][sample])
for i in dep_handle.fetch(chrom):
p_s, p_e, p_d = map(int, i.strip().split("\t")[1:4])
dep_data.append(p_d)
if (p_s <= start <= p_e) or (start <= p_s <= stop) or (p_s <= stop <= p_e):
deps.append(p_d)
dep_handle.close()
if len(deps) == 0:
return 0
d_m = np.mean(dep_data)
s_d = np.std(dep_data)
score = 0.0
for i in deps:
score += (i - d_m + 0.0) / s_d
return round(score / len(deps), 4)
def plot(self, sample, f_in):
fin = smart_open(f_in)
f_out = os.path.join(os.path.dirname(f_in), sample + ".cnv.out.pdf")
pdf = PdfPages(f_out)
for line in fin.readlines():
rows = line.strip().split("\t")
try:
chrom = str(rows[0])
start = max(int(rows[2]) - self.win_len, 0)
stop = int(rows[3]) + self.win_len
except ValueError:
continue
plt.figure()
samples = sorted(self.sample_win_data[chrom].keys())
deps = list()
for s in samples:
d = list()
dep_handle = pysam.Tabixfile(self.sample_win_data[chrom][s])
for lines in dep_handle.fetch(chrom, start, stop):
p_s, p_e, p_d = map(int, lines.strip().split("\t")[1:4])
d.append(p_d)
dep_handle.close()
deps.append(d)
deps = np.array(deps)
deps = np.log2(deps / deps.mean(axis=0))
for s in range(len(samples)):
d = deps[s]
if samples[s] == sample:
plt.plot(d, color="k")
else:
plt.plot(d, color="m")
plt.tick_params(axis='x', which='both', bottom='off', top='off', labelbottom='off')
plt.title("%s_%s_%s_%s" % (rows[0], rows[2], rows[3], rows[5]))
pdf.savefig()
plt.close()
pdf.close()
def annotation(self, sample, debug=False):
output = os.path.join(self.outdir, sample, "%s.cnv.anno.tsv" % sample)
f_out = smart_open(output, 'w')
titles = ["#Chrom", "Ploid", "Start", "Stop", "length", "copyNumber", "Mtype", "meanP", "Z-score", "GCpr",
"MutationName"]
dbtitle = self.DBAnno.dbtitle.split("\t")
titles.extend(dbtitle)
f_out.write("\t".join(titles) + '\n')
for chrom in self.contigs:
cnvs = os.path.join(self.outdir, sample, "%s.cnv" % chrom)
if not os.path.exists(cnvs):
continue
f_in = smart_open(cnvs)
for line in f_in:
rows = line.strip().split("\t")
try:
chrom = str(rows[0])
start = int(rows[2])
stop = int(rows[3])
mtype = str(rows[6])
except ValueError:
continue
z_s = self.z_score(chrom, start, stop, sample)
gcr = count_gc(self.DBAnno.refer.fetch(chrom, start, stop))
if not (0.3 <= gcr <= 0.7):
continue
variation = dict([("Chrom", chrom), ("Start", start), ("Stop", stop), ("Mtype", mtype)])
m_name = set()
for hgvs in self.HGVS.annobed(chrom, start, stop):
trans = str(hgvs.Transcript)
gene = str(hgvs.geneSym)
chgvs = str(hgvs.cHgvs)
protein = str(hgvs.Protein)
exons = str(hgvs.ExonRegions)
mess = ":".join(filter(lambda x: x != ".", [trans, protein, gene, chgvs, exons]))
m_name.add(mess)
dbinfo = self.DBAnno.dbanno(variation)
anno_message = [str(i) for i in rows]
anno_message.append(str(z_s))
anno_message.append(str(gcr))
anno_message.append("|".join(m_name))
for i in dbtitle:
if i in dbinfo:
anno_message.append("|".join(dbinfo[i]))
else:
anno_message.append(".")
f_out.write("\t".join(anno_message) + '\n')
f_in.close()
if not debug:
os.remove(cnvs)
f_out.close()
return output
