def _get_adj_list_directional(self, umis, counts):
''' identify all umis within the hamming distance threshold
and where the counts of the first umi is > (2 * second umi counts)-1'''
adj_list = {umi: [] for umi in umis}
if self.fuzzy_match:
for umi1 in umis:
# we need a second regex for some insertions,
# e.g UMI1 = "ATCG", UMI2 = "ATTC"
comp_regex_err = regex.compile("(%s){e<=1}" % str(umi1))
comp_regex_del = regex.compile("(%s){i<=1}" % str(umi1)[::-1])
for umi2 in umis:
if umi1 == umi2:
continue
if counts[umi1] >= (counts[umi2]*self.dir_threshold):
if (max(len(umi1), len(umi2)) -
min(len(umi1), len(umi2))) > 1:
continue
if (comp_regex_err.match(str(umi2)) or
comp_regex_del.match(str(umi2))):
adj_list[umi1].append(umi2)
else:
for umi1, umi2 in itertools.combinations(umis, 2):
if edit_distance(umi1, umi2) <= 1:
if counts[umi1] >= (counts[umi2]*2)-1:
adj_list[umi1].append(umi2)
if counts[umi2] >= (counts[umi1]*2)-1:
adj_list[umi2].append(umi1)
return adj_list
def _get_adj_list_directional_adjacency(self, umis, counts, threshold):
''' identify all umis within the hamming distance threshold
and where the counts of the first umi is > (2 * second umi counts)-1'''
return {umi: [umi2 for umi2 in umis if
edit_distance(umi, umi2) == 1 and
counts[umi] >= (counts[umi2]*2)-1] for umi in umis}
def _get_adj_list_directional_adjacency(self, umis, counts, threshold):
''' identify all umis within the hamming distance threshold
and where the counts of the first umi is > (2 * second umi counts)-1'''
return {umi: [umi2 for umi2 in umis if
edit_distance(umi, umi2) == 1 and
counts[umi] >= (counts[umi2]*2)-1] for umi in umis}
def _get_adj_list_adjacency(self, umis, counts, threshold):
''' identify all umis within hamming distance threshold'''
return {
umi:
[umi2 for umi2 in umis if edit_distance(umi, umi2) <= threshold]
for umi in umis
}
def _get_adj_list_adjacency(self, umis, counts, threshold):
''' identify all umis within hamming distance threshold'''
adj_list = {umi: [] for umi in umis}
if len(umis) > 25:
umi_length = len(umis[0])
substr_idx = build_substr_idx(umis, umi_length, threshold)
iter_umi_pairs = iter_nearest_neighbours(umis, substr_idx)
else:
iter_umi_pairs = itertools.combinations(umis, 2)
for umi1, umi2 in iter_umi_pairs:
if edit_distance(umi1, umi2) <= threshold:
adj_list[umi1].append(umi2)
adj_list[umi2].append(umi1)
return adj_list
def _get_adj_list_directional(self, umis, counts, threshold=1):
''' identify all umis within the hamming distance threshold
and where the counts of the first umi is > (2 * second umi counts)-1'''
adj_list = {umi: [] for umi in umis}
if len(umis) > 25:
umi_length = len(umis[0])
substr_idx = build_substr_idx(umis, umi_length, threshold)
iter_umi_pairs = iter_nearest_neighbours(umis, substr_idx)
else:
iter_umi_pairs = itertools.combinations(umis, 2)
for umi1, umi2 in iter_umi_pairs:
if edit_distance(umi1, umi2) <= threshold:
if counts[umi1] >= (counts[umi2]*2)-1:
adj_list[umi1].append(umi2)
if counts[umi2] >= (counts[umi1]*2)-1:
adj_list[umi2].append(umi1)
return adj_list
def _get_adj_list_adjacency(self, umis, counts, threshold):
''' identify all umis within hamming distance threshold'''
return {umi: [umi2 for umi2 in umis if
edit_distance(umi, umi2) <= threshold]
for umi in umis}
def get_average_umi_distance(umis):
if len(umis) == 1:
return -1
dists = [edit_distance(*pair) for pair in itertools.combinations(umis, 2)]
return float(sum(dists))/(len(dists))
def get_average_umi_distance(umis):
if len(umis) == 1:
return -1
dists = [edit_distance(*pair) for pair in itertools.combinations(umis, 2)]
return float(sum(dists)) / (len(dists))
