# mouse)
# print utils_distance.distance_species(monkey,
# mouse)
species2dict = {}
virus2dict = {}
virus2dict['swineFlu'] = utils.get_seq2count_dict('results/flu_elmdict_swine',
float(.4))
virus2dict['chickenFlu'] = utils.get_seq2count_dict('results/flu_elmdict_chicken',
float(.4))
virus2dict['humanFlu'] = utils.get_seq2count_dict('results/flu_elmdict_human',
float(.4))
for g in ('H_sapiens', 'Gallus_gallus', 'Sus_scrofa'):
species2dict[g] = utils.get_seq2count_dict_for_seqs('results/elmdict_'
+ g + '.txt',
float(0),
virus2dict)
for v in virus2dict:
species2dict[v] = virus2dict[v]
d = utils_distance.distance_matrix(species2dict)
elm_d = utils_distance.elm_distance_matrix(species2dict)
#for elm in elm_d:
# for species_pair in elm_d[elm]:
# print elm + '\t' + species_pair + '\t' + str(elm_d[elm][species_pair])
for s1, s2 in itertools.combinations(d.keys(), 2):
print s1 + '\t' + s2 + '\t' + str(d[s1][s2])
utils_plot.distance_heatmap(elm_d, 'test.png')
for line in f:
[protein, elm, cons] = line.strip().split('\t')
d[protein][elm] = float(cons)/float(100)
return d
#genomes = ('H5N1', 'H9N2')
#species = 'chicken'
genomes = ('H1N1', 'H3N2')
species = 'swine'
conserved = {}
all_conserved = {}
for g in genomes:
conserved[g] = get_conserved(species + '.' + g + '.elms.90')
all_conserved[g] = get_all_conserved(species + '.' + g + '.elms.conservation')
for protein in conserved['H1N1']:
d = defaultdict(dict)
elms = {}
for g in genomes:
for elm in conserved[g][protein]:
elms[elm] = True
for g in genomes:
for elm in elms:
if elm in conserved[g][protein]:
d[elm][g] = float(1)
elif elm in all_conserved[g][protein]:
d[elm][g] = all_conserved[g][protein][elm]
else:
d[elm][g] = float(0)
utils_plot.distance_heatmap(d, species + '.' + protein + '.png')
def get_all_conserved(afile):
d = defaultdict(dict)
with open(afile) as f:
for line in f:
[protein, elm, cons] = line.strip().split('\t')
d[protein][elm] = float(cons)/float(100)
return d
genomes = ('human', 'swine', 'chicken', 'equine')
conserved = {}
all_conserved = {}
for g in genomes:
conserved[g] = get_conserved('results/' + g + '.elms.90')
all_conserved[g] = get_all_conserved('results/' + g + '.elms.conservation')
for protein in conserved['human']:
d = defaultdict(dict)
elms = {}
for g in genomes:
for elm in conserved[g][protein]:
elms[elm] = True
for g in genomes:
for elm in elms:
if elm in conserved[g][protein]:
d[elm][g] = float(1)
elif elm in all_conserved[g][protein]:
d[elm][g] = all_conserved[g][protein][elm]
else:
d[elm][g] = float(0)
utils_plot.distance_heatmap(d, protein + '.all.png')
