def create_optimal_path_graph(sgraph,
kmax=0,
loss_threshold=0.10,
stats_fh=None):
'''
create a path graph from the original splice graph using paths of length
'k' for assembly. The parameter 'k' will be chosen by maximizing the
number of reachable k-mers in the path graph while tolerating at most
'loss_threshold' percent of expression.
'''
# find upper bound to k
user_kmax = kmax
kmax = find_longest_path(sgraph)
if user_kmax > 0:
# user can force a specific kmax (for debugging/testing purposes)
kmax = min(user_kmax, kmax)
sgraph_id_str = '%s:%d-%d[%s]' % (sgraph.chrom, sgraph.start, sgraph.end,
Strand.to_gtf(sgraph.strand))
tot_expr = sum(sgraph.get_node_expr_data(n).mean() for n in sgraph.G)
def compute_kmers(k):
K = create_path_graph(sgraph, k)
valid = K.graph['valid']
short_transfrags = K.graph['short_transfrags']
num_lost_kmers = K.graph['num_lost_kmers']
lost_nodes = get_lost_nodes(sgraph, K)
lost_expr = sum(
sgraph.get_node_expr_data(n).mean() for n in lost_nodes)
lost_expr_frac = 0.0 if tot_expr == 0 else lost_expr / tot_expr
logging.debug('%s k=%d kmax=%d t=%d kmers=%d short_transfrags=%d '
'lost_kmers=%d tot_expr=%.3f lost_expr=%.3f '
'lost_expr_frac=%.3f valid=%d' %
(sgraph_id_str, k, kmax, len(sgraph.transfrags), len(K),
len(short_transfrags), num_lost_kmers, tot_expr,
lost_expr, lost_expr_frac, int(valid)))
if stats_fh:
fields = [
sgraph_id_str, k, kmax,
len(sgraph.transfrags),
len(K),
len(short_transfrags), num_lost_kmers, tot_expr, lost_expr,
lost_expr_frac,
int(valid)
]
print >> stats_fh, '\t'.join(map(str, fields))
if not valid:
return -k
#if lost_expr_frac > loss_threshold:
# return -k
return len(K)
k, num_kmers = maximize_bisect(compute_kmers, 1, kmax, 0)
logging.debug('Creating path graph k=%d num_kmers=%d' % (k, num_kmers))
K = create_path_graph(sgraph, k)
logging.debug('Rescuing short transfrags')
rescue_short_transfrags_saindex(K)
return K, k
def create_optimal(self, kmax=0, loss_threshold=0.10, stats_fh=None):
'''
create a graph where nodes are paths of length 'k'. the parameter
'k' is chosen to maximizing the number of reachable k-mers in the
path graph while tolerating at most 'loss_threshold' percent of
expression.
'''
if len(self.paths) == 0:
return None, 0
# find upper bound to k
user_kmax = kmax
kmax = self.longest_path_length()
if user_kmax > 0:
# user can force a specific kmax (for debugging/testing purposes)
kmax = min(user_kmax, kmax)
id_str = (
'%s:%d-%d[%s]' %
(self.chrom, self.start, self.end, Strand.to_gtf(self.strand)))
def compute_kmers(k):
K = self.create(k)
tot_expr = sum(K.exprs[i] for i in K.node_ids_iter())
lost_expr = K.lost_kmer_expr
lost_expr_frac = 0.0 if tot_expr == 0 else lost_expr / tot_expr
if stats_fh:
fields = [
self.chrom, self.start, self.end,
Strand.to_gtf(self.strand), k, kmax,
len(self.paths), K.n,
len(K.short_transfrags), K.num_lost_kmers, tot_expr,
lost_expr, lost_expr_frac,
int(K.valid)
]
print >> stats_fh, '\t'.join(map(str, fields))
if not K.valid:
return -k
#if lost_expr_frac > loss_threshold:
# return -k
return len(K)
k, num_kmers = maximize_bisect(compute_kmers, 1, kmax, 0)
logging.debug('%s creating path graph k=%d num_kmers=%d' %
(id_str, k, num_kmers))
K = self.create(k)
logging.debug('%s rescuing short transfrags kmers=%d' %
(id_str, len(K)))
num_lost = self.rescue_short_transfrags(K, K.short_transfrags)
logging.debug('%s lost %d of %d short transfrags' %
(id_str, num_lost, len(K.short_transfrags)))
return K, k
def create_optimal_path_graph(sgraph, kmax=0, loss_threshold=0.10,
stats_fh=None):
'''
create a path graph from the original splice graph using paths of length
'k' for assembly. The parameter 'k' will be chosen by maximizing the
number of reachable k-mers in the path graph while tolerating at most
'loss_threshold' percent of expression.
'''
# find upper bound to k
user_kmax = kmax
kmax = find_longest_path(sgraph)
if user_kmax > 0:
# user can force a specific kmax (for debugging/testing purposes)
kmax = min(user_kmax, kmax)
sgraph_id_str = '%s:%d-%d[%s]' % (sgraph.chrom, sgraph.start, sgraph.end,
Strand.to_gtf(sgraph.strand))
tot_expr = sum(sgraph.get_node_expr_data(n).mean() for n in sgraph.G)
def compute_kmers(k):
K = create_path_graph(sgraph, k)
valid = K.graph['valid']
short_transfrags = K.graph['short_transfrags']
num_lost_kmers = K.graph['num_lost_kmers']
lost_nodes = get_lost_nodes(sgraph, K)
lost_expr = sum(sgraph.get_node_expr_data(n).mean() for n in lost_nodes)
lost_expr_frac = 0.0 if tot_expr == 0 else lost_expr / tot_expr
logging.debug('%s k=%d kmax=%d t=%d kmers=%d short_transfrags=%d '
'lost_kmers=%d tot_expr=%.3f lost_expr=%.3f '
'lost_expr_frac=%.3f valid=%d' %
(sgraph_id_str, k, kmax, len(sgraph.transfrags),
len(K), len(short_transfrags), num_lost_kmers,
tot_expr, lost_expr, lost_expr_frac, int(valid)))
if stats_fh:
fields = [sgraph_id_str, k, kmax, len(sgraph.transfrags), len(K),
len(short_transfrags), num_lost_kmers, tot_expr,
lost_expr, lost_expr_frac, int(valid)]
print >>stats_fh, '\t'.join(map(str, fields))
if not valid:
return -k
#if lost_expr_frac > loss_threshold:
# return -k
return len(K)
k, num_kmers = maximize_bisect(compute_kmers, 1, kmax, 0)
logging.debug('Creating path graph k=%d num_kmers=%d' % (k, num_kmers))
K = create_path_graph(sgraph, k)
logging.debug('Rescuing short transfrags')
rescue_short_transfrags_saindex(K)
return K, k
def create_optimal(self, kmax=0, stats_fh=None):
'''
create a graph where nodes are paths of length 'k'. the parameter
'k' is chosen to maximizing the number of reachable k-mers in the
path graph
'''
if len(self.paths) == 0:
return None, 0
# find upper bound to k
user_kmax = kmax
kmax = self.longest_path_length
if user_kmax > 0:
# user can force a specific kmax
kmax = min(user_kmax, kmax)
def compute_kmers(k):
K = self.create(k)
expr_frac = 0.0 if self.total_expr == 0 else K.graph_expr / self.total_expr
if stats_fh:
fields = self.get_stats(K, kmax=kmax)
print >> stats_fh, '\t'.join(map(str, fields))
if not K.valid:
return -k
# optimize based on kmers only (commented out)
#return len(K)
# optimize based on kmers weighted by fraction of total
# transcript expression retained in the path graph
return int(round(expr_frac * len(K)))
k, num_kmers = maximize_bisect(compute_kmers, 1, kmax, 0)
logging.debug('%s creating path graph k=%d num_kmers=%d' %
(str(self), k, num_kmers))
K = self.create(k)
logging.debug('%s rescuing short transfrags kmers=%d' %
(str(self), len(K)))
lost_short, lost_short_expr = \
self.rescue_short_transfrags(K, K.short_transfrags)
logging.debug('%s lost %d of %d short transfrags' %
(str(self), lost_short, len(K.short_transfrags)))
if stats_fh:
fields = self.get_stats(K,
kmax=kmax,
lost_short=lost_short,
lost_short_expr=lost_short_expr,
is_opt=1)
print >> stats_fh, '\t'.join(map(str, fields))
return K, k
def create_optimal(self, kmax=0, stats_fh=None):
'''
create a graph where nodes are paths of length 'k'. the parameter
'k' is chosen to maximizing the number of reachable k-mers in the
path graph
'''
if len(self.paths) == 0:
return None, 0
# find upper bound to k
user_kmax = kmax
kmax = self.longest_path_length
if user_kmax > 0:
# user can force a specific kmax
kmax = min(user_kmax, kmax)
def compute_kmers(k):
K = self.create(k)
expr_frac = 0.0 if self.total_expr == 0 else K.graph_expr / self.total_expr
if stats_fh:
fields = self.get_stats(K, kmax=kmax)
print >>stats_fh, '\t'.join(map(str, fields))
if not K.valid:
return -k
# optimize based on kmers only (commented out)
#return len(K)
# optimize based on kmers weighted by fraction of total
# transcript expression retained in the path graph
return int(round(expr_frac * len(K)))
k, num_kmers = maximize_bisect(compute_kmers, 1, kmax, 0)
logging.debug('%s creating path graph k=%d num_kmers=%d' %
(str(self), k, num_kmers))
K = self.create(k)
logging.debug('%s rescuing short transfrags kmers=%d' %
(str(self), len(K)))
lost_short, lost_short_expr = \
self.rescue_short_transfrags(K, K.short_transfrags)
logging.debug('%s lost %d of %d short transfrags' %
(str(self), lost_short, len(K.short_transfrags)))
if stats_fh:
fields = self.get_stats(K, kmax=kmax,
lost_short=lost_short,
lost_short_expr=lost_short_expr,
is_opt=1)
print >>stats_fh, '\t'.join(map(str, fields))
return K, k
def create_optimal(self, kmax=0, loss_threshold=0.10, stats_fh=None):
'''
create a graph where nodes are paths of length 'k'. the parameter
'k' is chosen to maximizing the number of reachable k-mers in the
path graph while tolerating at most 'loss_threshold' percent of
expression.
'''
if len(self.paths) == 0:
return None, 0
# find upper bound to k
user_kmax = kmax
kmax = self.longest_path_length()
if user_kmax > 0:
# user can force a specific kmax (for debugging/testing purposes)
kmax = min(user_kmax, kmax)
id_str = ('%s:%d-%d[%s]' % (self.chrom, self.start, self.end,
Strand.to_gtf(self.strand)))
def compute_kmers(k):
K = self.create(k)
tot_expr = sum(K.exprs[i] for i in K.node_ids_iter())
lost_expr = K.lost_kmer_expr
lost_expr_frac = 0.0 if tot_expr == 0 else lost_expr / tot_expr
if stats_fh:
fields = [self.chrom, self.start, self.end,
Strand.to_gtf(self.strand), k, kmax,
len(self.paths), K.n, len(K.short_transfrags),
K.num_lost_kmers, tot_expr, lost_expr,
lost_expr_frac, int(K.valid)]
print >>stats_fh, '\t'.join(map(str, fields))
if not K.valid:
return -k
#if lost_expr_frac > loss_threshold:
# return -k
return len(K)
k, num_kmers = maximize_bisect(compute_kmers, 1, kmax, 0)
logging.debug('%s creating path graph k=%d num_kmers=%d' %
(id_str, k, num_kmers))
K = self.create(k)
logging.debug('%s rescuing short transfrags kmers=%d' %
(id_str, len(K)))
num_lost = self.rescue_short_transfrags(K, K.short_transfrags)
logging.debug('%s lost %d of %d short transfrags' %
(id_str, num_lost, len(K.short_transfrags)))
return K, k
