def visualize_markup(self, index=1):
sequences = []
for seq in self.seq:
gff_record = next(
(x for x in self.gff if str(x.id) == str(seq.id)), None)
if gff_record:
# Filter 'gene' features
genes = [x for x in gff_record.features if x.type == 'gene']
features = []
for gene in genes:
start, end, strand = gene.location.start, gene.location.end, gene.location.strand
features.append(
GraphicFeature(start,
end,
strand,
label=gene.qualifiers['Name'],
color="#cffccc"))
sequences.append(features)
output_file("test.html")
record = GraphicRecord(sequence_length=1000, features=sequences[index])
show(record.plot_with_bokeh(figure_width=5))
def main(input, faa, fna, fasta, gff, output, log, name):
gff_path = gff.name
gff_data = {}
header = []
mol_length = {}
genome = Fasta(fasta)
for rec in gff:
rec = rec.rstrip()
if rec.startswith("##"): continue
elif rec.startswith("# Seq"):
header.append(rec.rstrip())
length = int(rec.split(";")[1].split("=")[1])
elif rec.startswith("#"): continue
elif rec == '"': continue
else:
line = rec.rstrip().split("\t")
if line[0] not in gff_data:
gff_data[line[0]] = {}
if line[0] not in mol_length:
mol_length[line[0]] = length
id = line[8].split(";")[0].split("_")[1]
id = f"{line[0]}_{id}"
gff_data[line[0]][id] = line
# print(f"Sequence length: {mol_length}")
# print(gff_data)
hits = {}
prots = {}
for line in input:
if not line.startswith("#"):
line = line.rstrip().split()
prots[line[2]] = line[0]
if line[0] in hits and line[2] not in hits[line[0]]:
hits[line[0]].append(line[2])
else:
hits[line[0]] = [line[2]]
# import pprint
# pp = pprint.PrettyPrinter(indent=4)
# pp.pprint(hits)
# pp.pprint(prots)
if "vgrg" in hits:
for vgrg in hits['vgrg']:
contig, id = vgrg.rsplit("_",1)
if f"{contig}_{int(id)-1}" in prots:
genes = build_cluster(fwd=True, start=f"{contig}_{int(id)-1}", hcp=True, annotations=hits, peptides=prots)
# print(genes)
elif f"{contig}_{int(id)+1}" in prots:
genes = build_cluster(fwd=False, start=f"{contig}_{int(id)+1}", hcp=True, annotations=hits, peptides=prots)
# print(genes)
else:
genes= build_cluster(fwd=False, start=vgrg, hcp=False, annotations=hits, peptides=prots)
# print(genes)
if any(genes[x] in ['hydrolase', 'lipase'] for x in genes):
print(f"Found Aux1 or Aux4")
gff_data = add_names(genes, gff_data, "Aux 1 or 4")
elif any(genes[x] in ['ntpase', 'transferase', 'lysm'] for x in genes):
print(f"Found Aux2")
gff_data = add_names(genes, gff_data, "Aux2")
else:
print(f"Unknown partial cluster\n{genes}")
print("Searching for Aux3 cluster")
cluster3 = {}
if "aux3" in hits:
print("Aux3 present")
for aux3 in hits["aux3"]:
contig, id = aux3.rsplit("_",1)
if f"{contig}_{int(id)-1}" in prots:
cluster3[aux3] = "effector"
cluster3[f"{contig}_{int(id)-1}"] = "PAAR"
cluster3[f"{contig}_{int(id)+1}"] = "immunity"
elif f"{contig}_{int(id)+1}" in prots:
cluster3[aux3] = "effector"
cluster3[f"{contig}_{int(id)+1}"] = "PAAR"
cluster3[f"{contig}_{int(id)-1}"] = "immunity"
else:
pass
# print(cluster3)
gff_data = add_names(cluster3, gff_data, "Aux3")
else:
print("No Aux3")
nucl = tempfile.NamedTemporaryFile(mode="r+", suffix=".nucl")
hmmout = tempfile.NamedTemporaryFile(mode="r+", suffix=".bed")
aux5gff = tempfile.NamedTemporaryFile(mode="r+", suffix=".gff")
aux5_nhmmer = f" nhmmer --cpu 4 --F1 .1 -o /dev/null --tblout {nucl.name} /home/blast/prediction_server/server/hmm_profiles//aux5 {fasta}"
print(f"Searching for Aux5 clusters: {aux5_nhmmer}")
subprocess.call(aux5_nhmmer, shell=True)
aux5_pres = False
for l in nucl:
if l.startswith("#"): continue
l = l.rstrip().split()
percID = (max(int(l[7]),int(l[6])) - min(int(l[7]),int(l[6])))/6000
if percID > 0.9:
hmmout.write(f"{l[0]}\t{l[8]}\t{l[9]}\n")
aux5_pres = True
hmmout.seek(0)
print(hmmout.read())
bedtool_cmd = f"bedtools intersect -a {gff_path} -b {hmmout.name} > {aux5gff.name}"
subprocess.call(bedtool_cmd, shell=True)
if aux5_pres:
nucleotides = Fasta(fna.name)
aux5_fh = tempfile.NamedTemporaryFile(mode="r+", suffix=".fasta")
for rec in aux5gff:
rec.rstrip()
if rec == "": continue
else:
line = rec.rstrip().split("\t")
id = line[8].split(";")[0].split("_")[1]
id = f"{line[0]}_{id}"
aux5_fh.write(f">{id}\n{str(nucleotides[id])}\n")
aux5_fh.seek(0)
# print(aux5_fh.read())
aux5hmms = ['aux5_hcp.hmm', 'aux5_vgrg.hmm', 'aux5_tap.hmm', 'aux5_eff.hmm']
aux5hmmstat = {'aux5_hcp.hmm' : 228, 'aux5_vgrg.hmm': 2100, 'aux5_tap.hmm' : 747, 'aux5_eff.hmm': 1725}
aux5 = {}
for hmm in aux5hmms:
a5hmmout = tempfile.NamedTemporaryFile(mode="r+", suffix=".out")
a5nhmmer_cmd = f"nhmmer --F1 .1 -o /dev/null --tblout {a5hmmout.name} /home/blast/prediction_server/server/hmm_profiles/{hmm} {aux5_fh.name}"
print(f"Running nhmmer: {a5nhmmer_cmd}")
subprocess.call(a5nhmmer_cmd, shell=True, stderr=subprocess.DEVNULL )
for l in a5hmmout:
if l.startswith("#"): continue
l = l.rstrip().split()
percID = (max(int(l[7]),int(l[6])) - min(int(l[7]),int(l[6])))/aux5hmmstat[hmm]
if percID > 0.9:
print(f"Found result for {hmm}: {l[0]}")
aux5[l[0]] = l[2].split("_")[1]
# pp.pprint(aux5)
gff_data = add_names(aux5, gff_data, "Aux5")
annotation = {}
uhOhSpaghettiOs = True
for contig in gff_data:
annotation[contig] = {}
features = []
for seq in gff_data[contig]:
if gff_data[contig][seq][8].startswith("Name="):
label = gff_data[contig][seq][8].split(";")[0].split("=")[1]
# print(f"label={label},start={gff_data[contig][seq][3]}, end={gff_data[contig][seq][4]}, strand={gff_data[contig][seq][6]}1")
features.append(
GraphicFeature(start=int(gff_data[contig][seq][3]),
end=int(gff_data[contig][seq][4]),
strand=int(f"{gff_data[contig][seq][6]}1"),
color="#ffd700",
label=label)
)
annotation[contig][seq] = label
annotation[seq] = label
else:
# print(f"label={None},start={gff_data[contig][seq][3]}, end={gff_data[contig][seq][4]}, strand={gff_data[contig][seq][6]}1")
features.append(
GraphicFeature(start=int(gff_data[contig][seq][3]),
end=int(gff_data[contig][seq][4]),
strand=int(f"{gff_data[contig][seq][6]}1")
)
)
# print(mol_length[contig])
# sequence = str(genome[contig])
if annotation[contig] != {}:
uhOhSpaghettiOs = False
record = GraphicRecord(sequence_length=mol_length[contig], features=features)
plot = record.plot_with_bokeh(figure_width=15)
with open(f"{output}/{contig}.html", "w+") as f:
f.write(file_html(plot, CDN, f"{contig}"))
proteins = Fasta(faa.name)
with open(f"{output}/proteins.faa", "w+") as p_fh:
for seq in proteins.keys():
if seq in annotation:
p_fh.write(f">{annotation[seq]}\n{str(proteins[seq])}\n")
else:
p_fh.write(f">{seq}\n{str(proteins[seq])}\n")
cds = Fasta(faa.name)
with open(f"{output}/nucleotides.fna", "w+") as n_fh:
for seq in cds.keys():
if seq in annotation:
n_fh.write(f">{annotation[seq]}\n{str(cds[seq])}\n")
else:
n_fh.write(f">{seq}\n{str(cds[seq])}\n")
if uhOhSpaghettiOs:
with open(f"{output}/nohits.html", "w+") as sadface:
sadface.write('<div class="splash"><div class="middle"><h1>No T6SS predicted :(</h1></div><div class="bottomleft"><p>T6SS.Vibriocholera.com</p></div></div>\n')
