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rnapfinder_with_hmmer_v2.py
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import os
import sys
import subprocess
import re
import shlex
import pandas
import glob
import operator
import numpy as np
from collections import defaultdict
from operator import itemgetter
from Bio import SeqIO
from Bio.Seq import Seq
from Bio.SeqRecord import SeqRecord
from Bio.Alphabet import IUPAC
working_dir = sys.argv[1]
info = open("ncldv_downloads.txt", "r")
speci_db = "hmm/RNAP.full.hmm"
#speci_db = "hmm/all.hmm"
cog_set = ['COG0085', 'COG0086', 'COG0202']
#cog_set = ["PF00164.24", "PF00177.20", "PF00181.22", "PF00189.19", "PF00203.20", "PF00237.18", "PF00238.18", "PF00252.17", "PF00281.18", "PF00297.21", "PF00298.18", "PF00312.21", "PF00333.19", "PF00338.21", "PF00366.19", "PF00380.18", "PF00410.18", "PF00411.18", "PF00416.21", "PF00466.19", "PF00573.21", "PF00673.20", "PF00687.20", "PF00861.21", "PF03719.14", "PF03946.13", "PF03947.17"]
#cog_set = ["Ribosomal_L3", "Ribosomal_L4", "Ribosom_S12_S23", "Ribosomal_S11", "Ribosomal_S13", "Ribosomal_L1", "Ribosomal_L2_C", "Ribosomal_S7", "Ribosomal_L16", "Ribosomal_L14", "Ribosomal_L22", "Ribosomal_S19", "Ribosomal_S9", "Ribosomal_S10", "Ribosomal_S8", "Ribosomal_S17", "Ribosomal_L10", "Ribosomal_S5", "Ribosomal_L11", "Ribosomal_L5_C", "Ribosomal_S3_C", "Ribosomal_S15", "Ribosomal_L18p"]
#cog_set = ["COG0012", "COG0016", "COG0018", "COG0048", "COG0049", "COG0052", "COG0080", "COG0081", "COG0085", "COG0086", "COG0087", "COG0088", "COG0090", "COG0091", "COG0092", "COG0093", "COG0094", "COG0096", "COG0097", "COG0098", "COG0099", "COG0100", "COG0102", "COG0103", "COG0124", "COG0172", "COG0184", "COG0185", "COG0186", "COG0197", "COG0200", "COG0201", "COG0202", "COG0215", "COG0256", "COG0495", "COG0522", "COG0525", "COG0533", "COG0541", "COG0552"]
#cog_set = ["COG0012", "COG0048", "COG0049", "COG0052", "COG0080", "COG0081", "COG0087", "COG0088", "COG0090", "COG0091", "COG0092", "COG0093", "COG0094", "COG0096", "COG0097", "COG0098", "COG0099", "COG0100", "COG0102", "COG0103", "COG0184", "COG0185", "COG0186", "COG0197", "COG0200", "COG0256", "COG0522"]
#for i in cog_set:
# test = open(i+".txt", "w")
combined_output = open("output.txt", "w")
#combined_output.write("name\tprotein\tacc\tspecies\tdomain\tphylum\tfamily\tgenus\thit\tcategory\tlength\tscore\talign_length\tnum_hits\tall_proteins\talignment_locations\n")
# test.close()
merged_proteins = open("RNAP.faa", "w")
final_proteins = []
# get taxonomic info
taxon_dict = {}
for j in info:
line = j.rstrip("\n")
tabs = line.split("\t")
ftp = tabs[17]
slash = ftp.split("/")
name = slash[9]
tax = [x for i,x in enumerate(tabs) if i in [6, 20, 21, 23, 24]]
taxonomic = "\t".join(tax)
taxon_dict[name] = taxonomic
print name, taxonomic
marker_tally = defaultdict(int)
exceptions = open("exceptions.txt", "w")
tally = 0
#################################################################
############# define hmm launcher function ######################
#################################################################
def hmm_launcher(folder):
for files in os.listdir(folder):
if files.endswith(".faa"):
print files
input_file = os.path.join(folder, files)
dom_output = re.sub(".faa", ".domout", files)
speci_dom_output = os.path.join(folder, dom_output)
# run against the RNAP models
cmd = "hmmsearch --cpu 16 -E 1e-5 --domtblout "+ speci_dom_output +" "+ speci_db + " " + input_file
print cmd
cmd2 = shlex.split(cmd)
subprocess.call(cmd2, stdout=open("hmm.out", 'w'), stderr=open("error_file.txt", 'a'))
# end
hmm_launcher(working_dir)
################################################################
###### Loop through and parse the checkm HMM output ############
################################################################
def hmm_parser(folder, suffix, output):
record_list = []
score_list = {}
prot_list = []
#combined_output = open(output, "w")
combined_output.write("protein\tacc\thit\tstart\tend\taln_length\tscore\tcategory\n")
hits = []
bit_dict = {}
for filenames in os.listdir(folder):
if filenames.endswith(suffix):
acc = re.sub(suffix, "", filenames)
f = open(folder+"/"+filenames, 'r')
o = open(folder+"/"+filenames+".parsed", 'w')
faa_file = re.sub(".domout", ".faa", filenames)
protein_dict = SeqIO.to_dict(SeqIO.parse(os.path.join(folder, faa_file), "fasta"))
hit_dict = {}
start_dict = {}
end_dict = {}
bit_dict = defaultdict(int)
hit_type = {}
marker_dict = {}
for line in f.readlines():
if line.startswith("#"):
pass
else:
newline = re.sub( '\s+', '\t', line)
list1 = newline.split('\t')
ids = list1[0]
hit = list1[3]
start = list1[15]
end = list1[16]
#print start, end
score = float(list1[7])
if score > bit_dict[ids]:
hit_dict[ids] = hit
start_dict[ids] = start
end_dict[ids] = end
bit_dict[ids] = score
bit_sorted = sorted(bit_dict.items(), key=operator.itemgetter(1), reverse=True)
output_list = []
for item in bit_sorted:
entry = item[0]
output_list.append(entry +"\t"+ str(hit_dict[entry]) +"\t"+ str(start_dict[entry]) +"\t"+ str(end_dict[entry]) +"\t"+ str(bit_dict[entry]) )
hit_profile = defaultdict(int)
done = []
for line in output_list:
line1 = line.rstrip()
tabs = line1.split("\t")
ids = tabs[0]
record = protein_dict[ids]
record_list.append(record)
hits.append(ids)
cog = tabs[1]
start = tabs[2]
end = tabs[3]
aln_length = str(abs(float(end) - float(start)))
score = tabs[4]
nr = acc +"_"+ cog
if nr in done:
combined_output.write(ids +"\t"+ acc +"\t"+ cog +"\t"+ start +"\t"+ end +"\t"+ aln_length +"\t"+ score +"\tNH\t"+taxon_dict[acc]+"\n")
o.write(ids +"\t"+ acc +"\t"+ cog +"\t"+ start +"\t"+ end +"\t"+ score +"\tNH\n")
else:
combined_output.write(ids +"\t"+ acc +"\t"+ cog +"\t"+ start +"\t"+ end +"\t"+ aln_length +"\t"+ score +"\tBH\t"+taxon_dict[acc]+"\n")
o.write(ids +"\t"+ acc +"\t"+ cog +"\t"+ start +"\t"+ end +"\t"+ score +"\tBH\n")
done.append(nr)
o.close()
# output = open("output.faa", "w")
# SeqIO.write(record_list, output, "fasta")
#parse speci outputs
speci_df = hmm_parser(working_dir, ".domout", "all_hmmout.txt")
################################################################
########## Define function for parsing HMMER3 output ###########
################################################################
def parse_domout(path_to_parsed_hmmfile, acc, protein_dict, cog_name):
parsed = open(path_to_parsed_hmmfile, "r")
done = {}
protein2coords = defaultdict(list)
protein2align_length = {}
main_hit = "NAN"
rnap_hits = []
protein2cog = defaultdict(lambda:"NA")
protein2acc = {}
protein2score = {}
protein2category = {}
protein2length = {}
for n in parsed.readlines():
line = n.rstrip()
tabs = line.split("\t")
protein = tabs[0]
annot = tabs[2]
if annot == cog_name:
rnap_hits.append(protein)
id_hit = protein +"|"+ annot
hmm_score = float(tabs[5])
category = tabs[6]
if hmm_score > 1:
start = int(tabs[3])
end = int(tabs[4])
record = protein_dict[protein]
prot_length = len(record.seq)
nr = acc +"_"+ annot
protein2cog[protein] = annot
protein2acc[protein] = acc
protein2score[protein] = hmm_score
protein2length[protein] = prot_length
protein2coords[id_hit].append(start)
protein2coords[id_hit].append(end)
align_length = abs(end - start)
protein2align_length[id_hit] = align_length
if category == "BH" and annot == cog_name:
main_hit = protein
protein2dups[id_hit]
protein2category[protein] = category
parsed.close()
return main_hit, protein2cog, protein2acc, protein2score, protein2length, protein2category, protein2coords, protein2align_length
cog_out = open("cogs.txt", "w")
for i in os.listdir(working_dir):
if i.endswith(".faa"):
protein_file = os.path.join(working_dir, i)
gff_file = re.sub(".faa", ".gff", protein_file)
domout = re.sub(".faa", ".domout", protein_file)
parsed = re.sub(".faa", ".domout.parsed", protein_file)
acc = re.sub(".faa", "", i)
# get a dictionary of protein sequences
seq_handle = open(protein_file, "r")
seq_dict = SeqIO.to_dict(SeqIO.parse(seq_handle, "fasta"))
orf_set = [record.id for record in seq_dict.values()]
# parse domout file and get protein hits and coordinates
for cog in cog_set:
protein2dups = defaultdict(lambda:"single_besthit")
merged = open("full_output.txt", "a")
# merged = open("RNAP.faa", "a")
rnap, protein2cog, protein2acc, protein2score, protein2length, protein2category, protein2coords, protein2align_length = parse_domout(parsed, acc, seq_dict, cog)
if rnap == "NAN":
print acc, cog, rnap
else:
already_done = []
num_proteins = defaultdict(lambda:int(1))
prot2protlist = defaultdict(list)
prot2loc = defaultdict(list)
prot2protlist[rnap].append(rnap)
id_hit1 = rnap +"|"+ cog
range1 = protein2coords[id_hit1]
r1 = range(range1[0], range1[1])
meanloc1 = np.mean(range1)
prot2loc[rnap].append(meanloc1)
orf_set.remove(rnap)
for d in orf_set:
if protein2cog[d] == cog:
id_hit2 = d +"|"+ cog
range2 = protein2coords[id_hit2]
r2 = range(range2[0], range2[1])
meanloc2 = np.mean(range2)
set1 = set(r1)
inter = set1.intersection(r2)
if int(len(inter)) > 50:
protein2dups[id_hit2] = "false_hit"
else:
protein2dups[id_hit1] = "main_hit"
protein2dups[id_hit2] = "secondary_hit"
minrange = min(range1 + range2)
maxrange = max(range1 + range2)
protein2coords[id_hit1] = [minrange, maxrange]
protein2align_length[id_hit1] = abs(maxrange - minrange)
protein2length[rnap] = int(protein2length[rnap]) + int(protein2length[d])
protein2score[rnap] = float(protein2score[rnap]) + float(protein2score[d])
prot2protlist[rnap].append(d)
prot2loc[rnap].append(meanloc2)
num_proteins[id_hit1] +=1
for item in protein2dups:
#print item
if protein2dups[item] == "main_hit" or protein2dups[item] == "single_besthit": #or protein2dups[item] == "NEXT" or protein2dups[item] == "SECO":
items = item.split("|")
protein = items[0]
hit = items[1]
protlist = prot2protlist[protein]
loc_list = [str(loc) for loc in prot2loc[protein]]
index_list = [i[0] for i in sorted(enumerate(loc_list), key=lambda x:x[1])]
sorted_loc_list = [i[1] for i in sorted(enumerate(loc_list), key=lambda x:x[1])]
sorted_prot_list = [protlist[index] for index in index_list]
prot_str = ";".join(sorted_prot_list)
loc_str = ";".join(sorted_loc_list)
acc = protein2acc[protein]
final_name = re.sub("_", ".", acc) +"_"+ hit
merged.write(final_name +"\t"+ protein +"\t"+ acc +"\t"+ taxon_dict[acc] +"\t"+ hit +"\t"+ protein2dups[item] +"\t"+ str(protein2length[protein]) +"\t"+ str(protein2score[protein]) +"\t"+ str(protein2align_length[item]) +"\t"+ str(num_proteins[item]) +"\t"+ prot_str +"\t"+ loc_str +"\n")
if len(sorted_prot_list) > 1:
tally = tally + len(sorted_prot_list)
newrecord = SeqRecord(Seq("", IUPAC.protein), id=final_name, name=protein+" JOINED", description=protein2acc[protein])
for fragment in sorted_prot_list:
subrecord = seq_dict[fragment]
subseq = subrecord.seq
subseq = re.sub("\*", "", str(subseq))
newrecord.seq = newrecord.seq +""+ subseq
final_proteins.append(newrecord)
else:
tally +=1
record = seq_dict[protein]
record.id = final_name
final_proteins.append(record)
names = [i.id for i in final_proteins]
for cog in cog_set:
name_set = [i for i in names if cog in i]
name_str = "\t".join(name_set)
cog_out.write(name_str +"\n")
SeqIO.write(final_proteins, merged_proteins, "fasta")
print tally