def genes2phens(p2entrez_file, e2z=None):
ensg2z = e2z if e2z else ut.load_dict_sets(ut.proj_path('convert', 'Hs2Hs_entrez.tab'))
def dict_sets_rem_prefix(d, sep):
d = dict([(k,set([vi.split(sep)[1] for vi in v])) for k,v in d.items()])
return d
p2z = dict_sets_rem_prefix(ut.load_dict_sets(p2entrez_file), ":")
return ut.compose_dict_sets(ensg2z, ut.dict_inverse_sets(p2z))
def load_havug_cxs(convert_ensg=True):
fname = ut.proj_path('havug_cxs')
u2e = ut.dict_inverse_sets(ut.load_dict_sets(
'../../data/convert/Hs2Hs_uni.tab'))
hcxs = ut.load_list_of_type(fname,set)
if convert_ensg:
hcxs = convert_complexes([(i,c) for i,c in
enumerate(hcxs)], u2e,
seqs.load_prots_from_fasta('../../data/sequences/canon/Hs.fasta'))
return hcxs
def ogroup_size_dict(odict):
"""
Takes a normal odict of fromid: set(toids) and returns a dict of fromid:
size of that side of the orthogroup.
"""
ogsize = {}
odinv = ut.dict_inverse_sets(odict)
for fromid in odict:
# Can just use the first one since orthogroups are cohesive
ogsize[fromid] = len(odinv[list(odict[fromid])[0]])
return ogsize
def ogroup_size_dict(odict):
"""
Takes a normal odict of fromid: set(toids) and returns a dict of fromid:
size of that side of the orthogroup.
"""
ogsize = {}
odinv = ut.dict_inverse_sets(odict)
for fromid in odict:
# Can just use the first one since orthogroups are cohesive
ogsize[fromid] = len(odinv[list(odict[fromid])[0]])
return ogsize
def remove_multi_keys(d, max_keys=1):
"""
Given a dict of key: set(vs), eliminate from the dict any keys that map to
the same set of vs.
"""
newd = d.copy()
dinv = ut.dict_inverse_sets(newd)
for k,vs in newd.items():
for v in vs:
if len(dinv[v]) > max_keys:
del newd[k]
break
return newd
def remove_multi_keys(d, max_keys=1):
"""
Given a dict of key: set(vs), eliminate from the dict any keys that map to
the same set of vs.
"""
newd = d.copy()
dinv = ut.dict_inverse_sets(newd)
for k,vs in newd.items():
for v in vs:
if len(dinv[v]) > max_keys:
del newd[k]
break
return newd
def load_seq_pairs(fname, metab_exclude=None):
"""
metab_exclude: should be in sequential_metab/metabolites_exclude.txt
"""
S, entrez_enzymes, rnames, mnames = load_metabolic_data(fname)
ez2en = ut.dict_inverse_sets(orth.convert_dict('Hs','Hs_entrez'))
if metab_exclude:
print "Excluding %s metabolites, filtering rxns" % len(metab_exclude)
S, entrez_enzymes = filter_rxns_metabs(S, entrez_enzymes, rnames,
mnames, metab_exclude)
else:
print "No filtering of metabolites and rxns."
sequentials = seq_pairs(S, entrez_enzymes, conv_dict=ez2en)
return sequentials
def load_kegg_sequentials(fname, do_convert=True):
dkegg = load_kegg_brite(fname)
kegg_paths = [ut.i1(v) for v in dkegg.values() if v]
def path_pairs(list_path):
return [(list_path[i],list_path[i+1]) for i in range(len(list_path)-1)]
group_pairs = ut.flatten([path_pairs(lpath) for lpath in kegg_paths])
#if return_groups:
#if conv_dict:
#return convert_groups_singles(labeled_pairs, conv_dict)
#else:
#return labeled_pairs
single_pairs = [(xi,yi) for x,y in group_pairs for xi in x for yi in y]
unique_pairs = pu.dedupe(single_pairs)
print "%s total, %s single, %s unique pairs returned" % (
len(group_pairs), len(single_pairs), len(unique_pairs))
if do_convert:
conv_dict = ut.dict_inverse_sets(orth.convert_dict('Hs','Hs_entrez'))
conv_pairs = convert_pairs_singles(unique_pairs, conv_dict)
print "%s converted pairs with 1-1 matches" % len(conv_pairs)
return conv_pairs
else:
return unique_pairs
def load_havug_ppis():
hints = ut.load_list_of_lists('../../docs/SupplementaryTableS2.tab')
u2e = ut.dict_inverse_sets(ut.load_dict_sets('../../data/convert/Hs2Hs_uni.tab'))
hints = [[list(u2e.get(p,['NoTranslation']))[0] for p in c[:2]]+[c[2]] for c in hints]
return hints
