def map_factor_sets(factor_sets):
pssm_map = get_pssm_to_ensembl_map_min_range()
return dict(
(name, extract_ensembl(map_factors_to_ensembl(name, factor_names, pssm_map)))
for name, factor_names
in factor_sets.iteritems()
)
def get_hit_counts():
if options.use_ucsc_seqs:
import ucsc_promoters
analysis = ucsc_promoters.get_analysis()
else:
raise RuntimeError('Do not know which sequences to use.')
hit_counts = dict()
logging.info('Using binding site threshold of %f to calculate hit counts.', options.hit_count_threshold)
hit_counts.update(convert_analysis_to_counts(analysis, A.get_pssm_to_ensembl_map_min_range(), options.hit_count_threshold))
remove_empty_counts(hit_counts)
return hit_counts.copy()
def get_hit_counts():
if options.use_ucsc_seqs:
import ucsc_promoters
analysis = ucsc_promoters.get_analysis()
else:
raise RuntimeError('Do not know which sequences to use.')
hit_counts = dict()
logging.info('Using binding site threshold of %f to calculate hit counts.',
options.hit_count_threshold)
hit_counts.update(
convert_analysis_to_counts(analysis,
A.get_pssm_to_ensembl_map_min_range(),
options.hit_count_threshold))
remove_empty_counts(hit_counts)
return hit_counts.copy()
def map_fn(key):
"@return: The value for the key."
return map[key]
return map_fn
if "__main__" == __name__:
import ucsc_promoters, analysis, biopsy, shared
tag = "lower"
try:
ucsc_analysis
except NameError:
ucsc_analysis = ucsc_promoters.get_analysis(tag)
pssm_map = analysis.get_pssm_to_ensembl_map_min_range()
ensembl_names = shared.get_all_ensembl_names()
for gene in [
"ENSMUSG00000000581",
"ENSMUSG00000035403",
"ENSMUSG00000022184",
"ENSMUSG00000061099",
"ENSMUSG00000031949",
"ENSMUSG00000037447",
"ENSMUSG00000026753",
"ENSMUSG00000022877",
"ENSMUSG00000066273",
"ENSMUSG00000031131",
"ENSMUSG00000015305",
"ENSMUSG00000061911",
]:
def map_factor_sets(factor_sets):
pssm_map = get_pssm_to_ensembl_map_min_range()
return dict(
(name,
extract_ensembl(map_factors_to_ensembl(name, factor_names, pssm_map)))
for name, factor_names in factor_sets.iteritems())
def map_factors_to_ensembl(name, factor_names, pssm_map):
result = dict(
(factor_name, transfac_factors.ens_genes_for(factor_name, pssm_map))
for factor_name in factor_names)
logging.info(
'%s\n%s\n', name,
'\n'.join('% 20s: %s' % (factor_name, ','.join(imap(str, ensembl)))
for factor_name, ensembl in result.iteritems()))
return result
def extract_ensembl(factor_mapping):
return set(chain(*[ensembl for ensembl in factor_mapping.values()]))
def map_factor_sets(factor_sets):
pssm_map = get_pssm_to_ensembl_map_min_range()
return dict(
(name,
extract_ensembl(map_factors_to_ensembl(name, factor_names, pssm_map)))
for name, factor_names in factor_sets.iteritems())
if '__main__' == __name__:
tremor_liver_tfs = tf_sets_by_name['tremor-liver']
pssm_map = get_pssm_to_ensembl_map_min_range()
tremor_liver_ensembl = map_factors_to_ensembl('tremor-liver',
tremor_liver_tfs, pssm_map)
def map_fn(key):
"@return: The value for the key."
return map[key]
return map_fn
if '__main__' == __name__:
import ucsc_promoters, analysis, biopsy, shared
tag = 'lower'
try:
ucsc_analysis
except NameError:
ucsc_analysis = ucsc_promoters.get_analysis(tag)
pssm_map = analysis.get_pssm_to_ensembl_map_min_range()
ensembl_names = shared.get_all_ensembl_names()
for gene in [
'ENSMUSG00000000581',
'ENSMUSG00000035403',
'ENSMUSG00000022184',
'ENSMUSG00000061099',
'ENSMUSG00000031949',
'ENSMUSG00000037447',
'ENSMUSG00000026753',
'ENSMUSG00000022877',
'ENSMUSG00000066273',
'ENSMUSG00000031131',
'ENSMUSG00000015305',
'ENSMUSG00000061911',
]:
],
}
def map_factors_to_ensembl(name, factor_names, pssm_map):
result = dict(
(factor_name, transfac_factors.ens_genes_for(factor_name, pssm_map))
for factor_name in factor_names
)
logging.info('%s\n%s\n', name, '\n'.join('% 20s: %s' % (factor_name, ','.join(imap(str, ensembl))) for factor_name, ensembl in result.iteritems()))
return result
def extract_ensembl(factor_mapping):
return set(chain(*[ensembl for ensembl in factor_mapping.values()]))
def map_factor_sets(factor_sets):
pssm_map = get_pssm_to_ensembl_map_min_range()
return dict(
(name, extract_ensembl(map_factors_to_ensembl(name, factor_names, pssm_map)))
for name, factor_names
in factor_sets.iteritems()
)
if '__main__' == __name__:
tremor_liver_tfs = tf_sets_by_name['tremor-liver']
pssm_map = get_pssm_to_ensembl_map_min_range()
tremor_liver_ensembl = map_factors_to_ensembl('tremor-liver', tremor_liver_tfs, pssm_map)
