def get_cons_elms(dir, hosts, years, strains, per, d, out_file, suffix):
"""Find ELMs that are consered at some per
for all host/strain/year combinations w/
at least 50 sequences"""
d1 = {'ELM':True}
d2 = d
use_files = {}
protein_counts_pass = defaultdict(dict)
for host in hosts:
for year in years:
for strain in strains:
f = os.path.join(dir, '.'.join((host, strain, str(year))) + '.elms')
new_f = os.path.join(dir, '.'.join((host, strain, str(year))) + suffix + '.' + per)
try:
count_cons(use_files, protein_counts_pass, f, d1, new_f)
#print host, year, strain
except: pass
for f in use_files:
use_files[f] = utils_motif.protein2annotation(f, d2)
# pass_elms =
with open(out_file, 'w') as afile:
for protein in protein_counts_pass:
#print protein + '\t' + str(len(protein_counts_pass[protein])) + '\t' + str([x.split('/')[2].split('.')[0:3] for x in protein_counts_pass[protein].keys()])
elm_counts_local = defaultdict(init_zero)
for f in protein_counts_pass[protein]:
for elm in use_files[f][protein]:
elm_counts_local[elm] += 1
for elm in elm_counts_local:
if len(protein_counts_pass[protein]) == elm_counts_local[elm]:
afile.write(protein + '\t' + elm + '\n')
def predict_die(useELMs, domain_tools, netFile):
h1 = {}
h2 = {}
net = utils_graph.getEdges(netFile)
proteins = {}
tool_d = {}
tool_d['ELM'] = True
protein2elm = utils_motif.protein2annotation('/home/perry/Projects/Human_Virus/Data/human.annotations', tool_d)
getProteinsForELMs(useELMs, proteins)
expandProteinsForELMs(useELMs, proteins, domain_tools)
for g1 in proteins.keys():
if net.has_key(g1):
for elm in proteins[g1].keys():
for g2 in protein2elm.keys():
if net[g1].has_key(g2) and protein2elm[g2].has_key(elm) and g1 != g2:
if not h1.has_key(elm): h1[elm] = {}
if not h2.has_key(elm): h2[elm] = {}
h1[elm][g1] = True
h2[elm][g2] = True
return [h1, h2]
def main():
req_args = ['virus annotation file',
'annotation tool',
'% MSA cutoff']
examples = ['../../Data/ProfileScan/hiv.prosite',
'ProfileScan',
'90']
utils_scripting.checkStart(sys.argv, req_args, examples, len(req_args), True)
annotation_file = sys.argv[1]
tool = sys.argv[2]
conserved_cutoff = float(sys.argv[3])
protein2annotation = utils_motif.protein2annotation(annotation_file,
{tool:True})
[virus2annotation, virus2proteinCount] = getCounts(protein2annotation)
for vp in virus2annotation.keys():
for motif in virus2annotation[vp].keys():
percent = (float(100) * float(virus2annotation[vp][motif]) /
float(virus2proteinCount[vp]))
if percent >= conserved_cutoff:
print vp + '\t0\t0\t' + motif + '\tseq\t' + tool
sys.stderr.write(vp + '\t' + motif + '\t' + str(percent) + '\n')
# del freq_elms['LIG_PDZ_3']
# del freq_elms['MOD_CK1_1']
# del freq_elms['MOD_CK2_1']
# del freq_elms['MOD_GSK3_1']
elm2freq = {}
for elm in freq_elms:
elm2freq[elm] = {}
for s in aa_freqs:
if elm in aa_freqs[s][0]:
elm2freq[elm][s] = aa_freqs[s][0][elm]
else:
elm2freq[elm][s] = float(0)
cut = sys.argv[2]
d = {'ELM':True}
swine_H1N1_elms = utils_motif.protein2annotation('results/swine.H1N1.elms.' + cut, d)
swine_H3N2_elms = utils_motif.protein2annotation('results/swine.H3N2.elms.' + cut, d)
swine = [swine_H1N1_elms, swine_H3N2_elms]
human_H1N1_elms = utils_motif.protein2annotation('results/human.H1N1.elms.' + cut, d)
human_H3N2_elms = utils_motif.protein2annotation('results/human.H3N2.elms.' + cut, d)
human_H5N1_elms = utils_motif.protein2annotation('results/human.H5N1.elms.' + cut, d)
human = [human_H1N1_elms, human_H3N2_elms, human_H5N1_elms]
chicken_H5N1_elms = utils_motif.protein2annotation('results/chicken.H5N1.elms.' + cut, d)
chicken_H9N2_elms = utils_motif.protein2annotation('results/chicken.H9N2.elms.' + cut, d)
chicken = [chicken_H5N1_elms, chicken_H9N2_elms]
duck_H5N1_elms = utils_motif.protein2annotation('results/duck.H5N1.elms.' + cut, d)
duck_H9N2_elms = utils_motif.protein2annotation('results/duck.H9N2.elms.' + cut, d)
duck = [duck_H5N1_elms, duck_H9N2_elms]
for seq in seq_counts:
if float(seq_counts[seq]) / protein_count > float(0.9):
cons.append(seq)
else:
nonCons.append(seq)
return [cons, nonCons]
host_file = sys.argv[1]
elm_file = sys.argv[2]
cons_file = sys.argv[3]
ofile = sys.argv[4]
cmp_file = sys.argv[5]
cmp_host_file = sys.argv[6]
elms = utils_motif.protein2annotation(elm_file, {"ELM": True})
cmp_elms = utils_motif.protein2annotation(cmp_file, {"ELM": True})
cons_elms = utils_motif.protein2annotation(cons_file, {"ELM": True})
host_freqs = get_freq(host_file)
cmp_freqs = get_freq(cmp_host_file)
(elm_counts, protein_counts) = getProtein2elm2seq(elms, cons_elms)
(cmp_counts, cmp_protein_counts) = getProtein2elm2seq(cmp_elms, cons_elms)
lines = ""
pos = 0
neg = 0
z = 0
for protein in elm_counts:
if protein in cmp_counts:
protein_count = float(protein_counts[protein])
cmp_protein_count = float(cmp_protein_counts[protein])
for elm in e:
freq_elms[elm] = True
elm2freq = {}
for elm in freq_elms:
elm2freq[elm] = {}
for s in aa_freqs:
if elm in aa_freqs[s][0]:
elm2freq[elm][s] = aa_freqs[s][0][elm]
else:
elm2freq[elm][s] = float(0.0000000000000000000001)
cut = sys.argv[1]
d = {'ELM':True}
swine_H1N1_elms = utils_motif.protein2annotation('results/swine.H1N1.elms.' + cut, d)
swine_H3N2_elms = utils_motif.protein2annotation('results/swine.H3N2.elms.' + cut, d)
swine = [swine_H1N1_elms, swine_H3N2_elms]
human_H1N1_elms = utils_motif.protein2annotation('results/human.H1N1.elms.' + cut, d)
human_H3N2_elms = utils_motif.protein2annotation('results/human.H3N2.elms.' + cut, d)
human_H5N1_elms = utils_motif.protein2annotation('results/human.H5N1.elms.' + cut, d)
human = [human_H1N1_elms, human_H3N2_elms, human_H5N1_elms]
horse_H3N8_elms = utils_motif.protein2annotation('results/equine.H3N8.elms.' + cut, d)
horse = [horse_H3N8_elms]
chicken_H5N1_elms = utils_motif.protein2annotation('results/chicken.H5N1.elms.' + cut, d)
chicken_H9N2_elms = utils_motif.protein2annotation('results/chicken.H9N2.elms.' + cut, d)
chicken = [chicken_H5N1_elms, chicken_H9N2_elms]
""" I need to add HIV and HCV to the project,
but I must first convert the ELMs hits to
the frequencies used for this project.
"""
import utils_motif, sys
def printELMusage(elm, seq2count):
total = 0
for seq in seq2count:
total += seq2count[seq]
for seq in seq2count:
print('%s\t%s\t%d\t%.10f' %
(elm, seq, seq2count[seq],
float(seq2count[seq]/float(total))))
protein2elm = utils_motif.protein2annotation(sys.argv[1],
{'ELM':True})
elm2seq2count = {}
for p in protein2elm:
for elm in protein2elm[p]:
if elm not in elm2seq2count:
elm2seq2count[elm] = {}
for [st, stp, seq] in protein2elm[p][elm]:
if seq not in elm2seq2count[elm]:
elm2seq2count[elm][seq] = 0
elm2seq2count[elm][seq] += 1
for elm in elm2seq2count:
printELMusage(elm, elm2seq2count[elm])
""" Find ELMs that are not conserve by change.
Enter subtype & cutoff for # trial an ELM for a
protein can be found by chance.
"""
import sys, utils_motif, utils_graph
import utils
from collections import defaultdict
elm_file = sys.argv[1]
cutoff = int(sys.argv[2])
real = utils_motif.protein2annotation('results/' + elm_file,
{'ELM':True})
protein2elms = {}
for x in xrange(10):
protein2annotation = utils_motif.protein2annotation('random_seq/'
+ str(x) + '/'
+ elm_file,
{'ELM':True})
for protein in protein2annotation:
for elm in protein2annotation[protein]:
if not protein in protein2elms:
protein2elms[protein] = {}
if not elm in protein2elms[protein]:
protein2elms[protein][elm] = 0
protein2elms[protein][elm] += 1
for protein in real:
if protein in protein2elms:
for elm in real[protein]:
if elm in protein2elms[protein]:
if not protein in protein2elm2seq:
protein2elm2seq[protein] = {}
if not elm in protein2elm2seq[protein]:
protein2elm2seq[protein][elm] = {}
for [st, stp, seq] in elms[protein_id][elm]:
if not seq in protein2elm2seq[protein][elm]:
protein2elm2seq[protein][elm][seq] = 0
protein2elm2seq[protein][elm][seq] += 1
return (protein2elm2seq, proteinCounts)
host_file = sys.argv[1]
elm_file = sys.argv[2]
cons_file = sys.argv[3]
ofile = sys.argv[4]
elms = utils_motif.protein2annotation(elm_file,
{'ELM':True})
cons_elms = utils_motif.protein2annotation(cons_file,
{'ELM':True})
host_freqs = get_freq(host_file)
(elm_counts, protein_counts) = getProtein2elm2seq(elms, cons_elms)
lines = ''
for protein in elm_counts:
protein_count = float(protein_counts[protein])
for elm in elm_counts[protein]:
if elm in host_freqs:
virus_freqs = []
non_virus_freqs = []
found_seqs = {}
for seq in elm_counts[protein][elm]:
if float(elm_counts[protein][elm][seq])/protein_count > float(.9):
import utils_motif, utils_graph
use_elms = utils_graph.getNodes('use_elms')
human = utils_motif.protein2annotation('human.H1N1.elms',
{'ELM':True})
human_conserved = utils_motif.protein2annotation('human.H1N1.elms.90',
{'ELM':True})
swine = utils_motif.protein2annotation('swine.H1N1.elms',
{'ELM':True})
swine_conserved = utils_motif.protein2annotation('swine.H1N1.elms.90',
{'ELM':True})
def get_entropy(afile):
entropy = {}
with open(afile) as f:
for line in f:
[elm, entropy_st] = line.strip().split('\t')
if not elm in entropy:
entropy[elm] = {}
entropy[elm] = float(entropy_st)
return entropy
def get_best_seq(seqs):
ls = []
for seq in seqs:
ls.append([seqs[seq],seq])
ls.sort()
#if len(ls) > 1:
# print ls[0], ls[1]
import utils_motif, sys
conserved_file = sys.argv[1]
elm_file = sys.argv[2]
conserved = utils_motif.protein2annotation(conserved_file,
{'ELM':True})
elms_pre = utils_motif.protein2annotation(elm_file,
{'ELM':True})
elms = {}
for protein in elms_pre:
vp = protein.split('.')[-1]
if not vp in elms:
elms[vp] = {}
for elm in elms_pre[protein]:
if not elm in elms[vp]:
elms[vp][elm] = []
for tri in elms_pre[protein][elm]:
elms[vp][elm].append(tri)
elm2seq2count = {}
for vp in conserved:
for elm in conserved[vp]:
for [st, stp, seq] in elms[vp][elm]:
if not elm in elm2seq2count:
elm2seq2count[elm] = {}
if not seq in elm2seq2count[elm]:
elm2seq2count[elm][seq] = 0
elm2seq2count[elm][seq] += 1
for elm in elm2seq2count:
total = 0
for seq in elm2seq2count[elm]:
import utils_motif, sys
flu = sys.argv[1]
species = sys.argv[2]
strain = sys.argv[3]
human = utils_motif.protein2annotation('human.' + strain + '.elms',
{'ELM':True})
human_conserved = utils_motif.protein2annotation('human.' + strain + '.elms.90',
{'ELM':True})
swine = utils_motif.protein2annotation(flu + '.' + strain + '.elms',
{'ELM':True})
swine_conserved = utils_motif.protein2annotation(flu + '.' + strain + '.elms.90',
{'ELM':True})
def get_freq(afile):
freq = {}
with open(afile) as f:
for line in f:
#[elm_seq, freq_st] = line.strip().split('\t')
#elm, seq = elm_seq.split(':')
elm, seq, num, freq_st = line.strip().split('\t')
if not elm in freq:
freq[elm] = {}
freq[elm][seq] = float(freq_st)
return freq
def get_best_seq(seqs):
ls = []
for seq in seqs:
ls.append([seqs[seq],seq])