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return _(""Last year"")
else:
return str(day_diff / 365) + _("" years ago"")"
4390,"def get_dst(date_obj):
""""""Determine if dst is locally enabled at this time""""""
dst = 0
if date_obj.year >= 1900:
tmp_date = time.mktime(date_obj.timetuple())
# DST is 1 so reduce time with 1 hour.
dst = time.localtime(tmp_date)[-1]
return dst"
4391,"def utc_to_localtime(
date_str,
fmt=""%Y-%m-%d %H:%M:%S"",
input_fmt=""%Y-%m-%dT%H:%M:%SZ""):
""""""
Convert UTC to localtime
Reference:
- (1) http://www.openarchives.org/OAI/openarchivesprotocol.html#Dates
- (2) http://www.w3.org/TR/NOTE-datetime
This function works only with dates complying with the
""Complete date plus hours, minutes and seconds"" profile of
ISO 8601 defined by (2), and linked from (1).
Eg: 1994-11-05T13:15:30Z
""""""
date_struct = datetime.strptime(date_str, input_fmt)
date_struct += timedelta(hours=get_dst(date_struct))
date_struct -= timedelta(seconds=time.timezone)
return strftime(fmt, date_struct)"
4392,"def njsd_all(network, ref, query, file, verbose=True):
""""""Compute transcriptome-wide nJSD between reference and query expression profiles.
Attribute:
network (str): File path to a network file.
ref (str): File path to a reference expression file.
query (str): File path to a query expression file.
""""""
graph, gene_set_total = util.parse_network(network)
ref_gene_expression_dict = util.parse_gene_expression(ref, mean=True)
query_gene_expression_dict = util.parse_gene_expression(query, mean=False)
maximally_ambiguous_gene_experession_dict = util.get_maximally_ambiguous_network(query_gene_expression_dict)
gene_set_present = set(query_gene_expression_dict.keys())
with open(file, 'w') as outFile:
print('nJSD_NT', 'nJSD_TA', 'tITH', sep='\t', file=outFile)
normal_to_tumor_njsd = entropy.njsd(network=graph,
ref_gene_expression_dict=ref_gene_expression_dict,
query_gene_expression_dict=query_gene_expression_dict,
gene_set=gene_set_present)
tumor_to_ambiguous_njsd = entropy.njsd(network=graph,
ref_gene_expression_dict=maximally_ambiguous_gene_experession_dict,
query_gene_expression_dict=query_gene_expression_dict,
gene_set=gene_set_present)
tITH = normal_to_tumor_njsd / (normal_to_tumor_njsd + tumor_to_ambiguous_njsd)
with open(file, 'a') as outFile:
print(normal_to_tumor_njsd, tumor_to_ambiguous_njsd, tITH, sep='\t', file=outFile)
return normal_to_tumor_njsd / (normal_to_tumor_njsd + tumor_to_ambiguous_njsd)"
4393,"def njsd_geneset(network, ref, query, gene_set, file, verbose=True):
""""""Compute gene set-specified nJSD between reference and query expression profiles.
Attribute;
network (str): File path to a network file.
ref (str): File path to a reference expression file.
query (str): File path to a query expression file.
geneset (str): File path to a gene set file.
""""""
graph, gene_set_total = util.parse_network(network)
ref_gene_expression_dict = util.parse_gene_expression(ref, mean=True)
query_gene_expression_dict = util.parse_gene_expression(query, mean=False)
group_gene_set_dict = util.parse_gene_set(gene_set)
maximally_ambiguous_gene_experession_dict = util.get_maximally_ambiguous_network(query_gene_expression_dict)
gene_set_present = set(query_gene_expression_dict.keys())
with open(file, 'w') as outFile:
print('Gene_set_ID', 'nJSD_NT', 'nJSD_TA', 'tITH', sep='\t', file=outFile)
for group, gene_set in group_gene_set_dict.items():
gene_set_to_be_analyzed = gene_set.intersection(gene_set_present)
# If no genes are available for the group, just ignore it.
if len(gene_set_to_be_analyzed) == 0:
logger.warning('%s has no genes available for analysis. Ignoring the group.' % group)
continue
# If every gene has a single neighbor, just ignore it.
if all([graph.degree(gene) == 1 for gene in gene_set_to_be_analyzed]):
logger.warning('%s has no genes with enough neighbors. Ignoring the group.' % group)
continue
normal_to_tumor_njsd = entropy.njsd(network=graph,
ref_gene_expression_dict=ref_gene_expression_dict,
query_gene_expression_dict=query_gene_expression_dict,
gene_set=gene_set)
tumor_to_ambiguous_njsd = entropy.njsd(network=graph,
ref_gene_expression_dict=maximally_ambiguous_gene_experession_dict,
query_gene_expression_dict=query_gene_expression_dict,