def merge2IntervalTree(mergeTree):
convTree = ChromTree()
i = 0
for chrom, trees in mergeTree.iteritems():
for beg, end, ns in mergeTree[chrom].getregions():
convTree.insert(chrom,beg,end,(beg,end))
return convTree
def merge2IntervalTree(mergeTree):
convTree = ChromTree()
i = 0
for chrom, trees in mergeTree.iteritems():
for beg, end, ns in mergeTree[chrom].getregions():
convTree.insert(chrom,beg,end,(beg,end))
return convTree
def intervalTree(fin):
"""
Reads gzipped bed file as interval tree
"""
i = 0
tree = ChromTree()
for line in gzip.open(fin, 'r'):
i+= 1
chrom, start, end = line.rstrip().split("\t")[:3]
if chrom == "Chrom": continue
tree.insert(chrom, int(start), int(end), (int(start),int(end)))
print "Read {i} lines from {fin}".format(**locals())
return tree
def intervalTree(fin):
"""
Reads gzipped bed file as interval tree
"""
i = 0
tree = ChromTree()
for line in gzip.open(fin, 'r'):
i+= 1
chrom, start, end = line.rstrip().split("\t")[:3]
if chrom == "Chrom": continue
tree.insert(chrom, int(start), int(end), (int(start),int(end)))
print "Read {i} lines from {fin}".format(**locals())
return tree
def main(args):
snps = pd.read_csv(args.bfile + '.bim',
header=None,
delimiter='\t',
names=['CHR', 'SNP', 'CM', 'BP', 'A1', 'A2'])
n_snp = len(snps)
n_annot = len(args.annot_bed)
annot_matrix = np.zeros((n_snp, n_annot), dtype=np.int8)
annot_names = []
extend = args.extend_bp + 1
for i in range(n_annot):
trees = ChromTree()
bed = pd.read_csv(args.annot_bed[i], header=None, delimiter='\t')
annot_name = os.path.basename(
args.annot_bed[i]
)[:-4] if args.annot_name is None else args.annot_name[i]
annot_names.append(annot_name)
if args.chr is not None:
args.chr = trees._format_chrom(args.chr)
bed = bed[bed[0] == args.chr]
bed.apply(
lambda x: trees.insert(x[0], x[1] - extend, x[2] + extend, i),
axis=1)
idx = snps.apply(lambda x: trees.find(x[0], x[3], x[3]), axis=1)
[[annot_matrix.itemset((j, i), 1) for _ in v]
for j, v in idx.iteritems()]
out_fname_annot = args.out + '.annot'
comp = None
if not args.only_annot:
annot_df = pd.concat(
[snps[['CHR', 'BP', 'SNP', 'CM']],
pd.DataFrame(annot_matrix)],
axis=1)
annot_df.columns = ['CHR', 'BP', 'SNP', 'CM'] + annot_names
out_fname_annot += '.gz'
comp = 'gzip'
else:
annot_df = pd.DataFrame(annot_matrix)
annot_df.columns = annot_names
annot_df.to_csv(out_fname_annot,
sep="\t",
header=True,
index=False,
float_format='%.4f',
compression=comp)