def fuse(args):
"""
%prog fuse *.bed *.anchors
Fuse gene orders based on anchors file.
"""
from jcvi.algorithms.graph import BiGraph
p = OptionParser(fuse.__doc__)
opts, args = p.parse_args(args)
if len(args) < 1:
sys.exit(not p.print_help())
bedfiles = [x for x in args if x.endswith(".bed")]
anchorfiles = [x for x in args if x.endswith(".anchors")]
# TODO: Use Markov clustering to sparsify the edges
families = Grouper()
for anchorfile in anchorfiles:
af = AnchorFile(anchorfile)
for a, b, block_id in af.iter_pairs():
families.join(a, b)
allowed = set(families.keys())
logging.debug("Total families: {}, Gene members: {}".format(
len(families), len(allowed)))
# TODO: Use C++ implementation of BiGraph() when available
# For now just serialize this to the disk
for bedfile in bedfiles:
bed = Bed(bedfile, include=allowed)
print_edges(bed, families)
def fuse(args):
"""
%prog fuse *.bed *.anchors
Fuse gene orders based on anchors file.
"""
from jcvi.algorithms.graph import BiGraph
p = OptionParser(fuse.__doc__)
opts, args = p.parse_args(args)
if len(args) < 1:
sys.exit(not p.print_help())
bedfiles = [x for x in args if x.endswith(".bed")]
anchorfiles = [x for x in args if x.endswith(".anchors")]
# TODO: Use Markov clustering to sparsify the edges
families = Grouper()
for anchorfile in anchorfiles:
af = AnchorFile(anchorfile)
for a, b, block_id in af.iter_pairs():
families.join(a, b)
allowed = set(families.keys())
logging.debug("Total families: {}, Gene members: {}"
.format(len(families), len(allowed)))
# TODO: Use C++ implementation of BiGraph() when available
# For now just serialize this to the disk
G = BiGraph()
for bedfile in bedfiles:
bed = Bed(bedfile, include=allowed)
#add_bed_to_graph(G, bed, families)
print_edges(G, bed, families)
