def genes_from_sites(sites, rho):
"Convert samples sites to data structure ready to pass to class Data."
result = []
for (_v_g, _z_g, x_g), rho_g in zip(sites, rho):
_tmp = DictOf(list)
for x_gi, rho_gi in zip(x_g, rho_g):
_tmp[x_gi].append(rho_gi)
result.append(list(_tmp.iteritems()))
return result
'REFSEQ',
'UNIGENE',
'ENSMUSG'
]:
print ref_type, len(filter(has_ref_fn(ref_type), mouse_promoters))
print map(mgi_id_for, mouse_promoters[:20])
mgi_to_ensembl = get_mgi_to_ensembl_map()
ensembl_promoters = DictOf(list)
for p in mouse_promoters:
ensembl = ensembl_for(p)
if ensembl:
ensembl_promoters[ensembl].append(p)
sequence_analyser = get_sequence_analyser()
analysis = DictOf(list)
for ensembl, remos in ensembl_promoters.iteritems():
for remo in remos:
analysis[ensembl].append(sequence_analyser(remo.sequence))
fasta = open('mouse-promoters.fa', 'w')
for ensembl, remos in ensembl_promoters.iteritems():
for i, remo in enumerate(remos):
fasta.write('> %s - %d\n' % (ensembl, i))
fasta.write(remo.sequence)
fasta.write('\n')
fasta.close()
