cols = line.rstrip().split()
if len(cols) == 5 :
if int(cols[2]) >= 50 and int(cols[3]) >= 50 and int(cols[4]) == 1 : # reciprocal identity is >= 50%, high confidence
- if cols[0] in dict_ens_ids.keys() :
+ if cols[0] in dict_ens_ids :
dict_ens_ids[cols[0]].append(cols[1])
else :
dict_ens_ids[cols[0]] = [cols[1]]
cols = line.rstrip().split()
os_locus = cols[1].rstrip(".1")
prj_locus = cols[2].rsplit("_",1)[0].rsplit(".",1)[0] # remove any isoform suffixes
- if os_locus in dict_inp_ids.keys() :
+ if os_locus in dict_inp_ids :
dict_inp_ids[os_locus].append(prj_locus)
else :
dict_inp_ids[os_locus] = [prj_locus]
prj_loci = cols[1].split(',')
# build ref_dict
- if os_locus in ref_dict.keys() :
+ if os_locus in ref_dict :
ref_dict[os_locus][0].extend(prj_loci) # add ens projected loci in the first list slot
else :
ref_dict[os_locus] = [prj_loci, []]
prj_loci = cols[1].split(',')
# continue build of ref_dict
- if os_locus in ref_dict.keys() :
+ if os_locus in ref_dict :
ref_dict[os_locus][1].extend(prj_loci) # put the inp projected loci in the second list slot
else :
ref_dict[os_locus] = [[], prj_loci] # create an empty slot for the ens projected loci, put the inp projected loci in the second list slot