if re.match(r".*txt$", file) and os.path.getsize(filePath) > 0:
with open(filePath) as infile:
for line in infile:
sampleName = ntpath.basename(filePath).split(".txt")[0]
outfile.write(line.strip() + "\t" + sampleName + "\t" + args.cohort_name + "\n")
# Eval spHMMs
rpackages.importr('base')
#packageNames = ('tidyverse','ggsci','ggpubr')
#utils = rpackages.importr('utils')
#utils.chooseCRANmirror(ind=1)
#packnames_to_install = [x for x in packageNames if not rpackages.isinstalled(x)]
#if len(packnames_to_install) > 0:
# utils.install_packages(StrVector(packnames_to_install))
rpackages.importr('tidyverse')
rpackages.importr('ggsci')
rpackages.importr('ggpubr')
hp_hmm_directory = os.path.join(build_op_dir, 'HiPer_spHMMs')
os.makedirs(hp_hmm_directory,0o777,True)
with open('EvaluateSpHMMs.R', 'r') as f:
rStr = f.read()
myfunc = STAP(rStr, "EvaluateSpHMM")
myfunc.EvaluateSpHMM(allHMMResult, allBLASTResult, gene_pos_file, args.prot_family_name, float(args.F1_Thresh), hmm_directory, hp_hmm_directory)
timeTaken = time.time() - startTime
mins = int(timeTaken / 60)
secs = int(timeTaken) % 60
print("\nTotal time taken : " + str(mins) + " mins " + str(secs) + " seconds")
def mbgcbuild(prot_alignment, prot_family_name, cohort_name,
nucl_seq_directory, prot_seq_directory, seq_fmt, pair_fmt, r1_file_suffix,
r2_file_suffix, tp_genes_nucl, blast_db_directory_map_file, blastn_search_directory, hmm_search_directory, f1_thresh,
output_directory, cpu):
try:
CPU_THREADS = 4
startTime = time.time()
if cpu is not None:
CPU_THREADS = int(cpu)
# setup paths
build_op_dir = output_directory + os.sep + "build"
hmm_directory = os.path.join(build_op_dir, 'spHMMs')
tp_genes_prot = build_op_dir + os.sep + "TPGenes.faa"
alnOutput = os.path.join(build_op_dir,"TP_Homolog_Alignment.afa")
gene_pos_file = os.path.join(build_op_dir, 'Gene_Interval_Pos.txt')
gene_pos_file_aa = os.path.join(build_op_dir, 'Gene_Interval_Pos_AA.txt')
if hmm_search_directory is None:
hmm_search_directory = os.path.join(build_op_dir, 'hmm_result')
allHMMResult = os.path.join(build_op_dir,"CombinedHmmSearch.txt")
if blastn_search_directory is None:
blastn_search_directory = os.path.join(build_op_dir, 'blastn_result')
allBLASTResult = os.path.join(build_op_dir,"CombinedBLASTSearch.txt")
# Create OP dirs
os.makedirs(hmm_directory, 0o777, True)
# Translate protein sequence
runTranSeq(tp_genes_nucl,"1",tp_genes_prot)
# Join true positives in the sample with the BGC proteins
tmpFile = os.path.join(build_op_dir,"TP_Homolog.faa")
joinedSeqs = []
tpGeneSeqs = list(SeqIO.parse(tp_genes_prot, "fasta"))
# Removing _1 added by TranSeq
for seq in tpGeneSeqs:
seq.id = seq.id[:-2]
seq.description = ""
joinedSeqs.append(seq)
SeqIO.write(joinedSeqs,tp_genes_prot,"fasta")
protAlnSeqs = list(SeqIO.parse(prot_alignment, "fasta"))
for seq in protAlnSeqs:
joinedSeqs.append(seq)
SeqIO.write(joinedSeqs, tmpFile, "fasta")
# MUSCLE align TP genes with markers
runMUSCLE(tmpFile, alnOutput)
# Gen spHMMs and interval pos
# Extract spHMM coordinates from MUSCLE alignment
hmmDict = gensphmmfiles(prot_family_name, alnOutput, tp_genes_prot,
hmm_directory, gene_pos_file, gene_pos_file_aa)
if r1_file_suffix is None:
r1_file_suffix = ""
if r2_file_suffix is None:
r2_file_suffix = ""
# #Preprocess synthetic reads
nucl_seq_directory = PreProcessReadsPar(nucl_seq_directory,
seq_fmt,pair_fmt,
r1_file_suffix.strip(),
r2_file_suffix.strip(),
build_op_dir,
CPU_THREADS)
#Check if BLAST DB directory mapping file is provided or not
if blast_db_directory_map_file is None:
blast_db_directory_map_file = ""
# Translate nucleotide seq
if not os.path.isdir(prot_seq_directory):
prot_seq_directory = TranseqReadsDir(build_op_dir, nucl_seq_directory, CPU_THREADS)
# HMMER Search
if not os.path.exists(allHMMResult):
os.makedirs(hmm_search_directory,0o777,True)
for hmmSeqPosKey, hmmFileObj in hmmDict.items():
hmmInterval = str(hmmDict[hmmSeqPosKey].intervalStart)+"_"+str(hmmDict[hmmSeqPosKey].intervalEnd)
RunHMMDirectoryParallel(prot_seq_directory,hmmFileObj.hmmFile, cohort_name, prot_family_name, "30_10", hmmInterval, hmm_search_directory, CPU_THREADS)
with open(allHMMResult, 'w') as outfile:
for subdir, dirs, files in os.walk(hmm_search_directory):
for file in files:
filePath = os.path.join(subdir, file)
if re.match(r".*txt$", file) and os.path.getsize(filePath) > 0:
with open(filePath) as infile:
for line in infile:
outfile.write(line)
# BLAST Alignment
if not os.path.exists(allBLASTResult):
if not os.path.isdir(blastn_search_directory):
print("Constructing BLAST Search Dir:" + blastn_search_directory)
os.makedirs(blastn_search_directory,0o777,True)
RunMakeDBandBlastN(nucl_seq_directory, blast_db_directory_map_file,
tp_genes_nucl, "blastn", "-max_target_seqs 10000 -perc_identity 90.0 -outfmt \"6 sseqid slen sstart send qseqid qlen qstart qend pident evalue\" ",
blastn_search_directory, CPU_THREADS)
with open(allBLASTResult, 'w') as outfile:
outfile.write("sseqid\tslen\tsstart\tsend\tqseqid\tqlen\tqstart\tqend\tpident\tevalue\tSample\tsampleType\n")
for subdir, dirs, files in os.walk(blastn_search_directory):
for file in files:
filePath = os.path.join(subdir, file)
if re.match(r".*txt$", file) and os.path.getsize(filePath) > 0:
with open(filePath) as infile:
for line in infile:
sampleName = os.path.basename(filePath).split(".txt")[0]
outfile.write(line.strip() + "\t" + sampleName + "\t" + cohort_name + "\n")
# Eval spHMMs
rpackages.importr('base')
utils = rpackages.importr('utils')
packageNames = ('tidyverse','ggsci','ggpubr','dplyr','ggplot2')
packnames_to_install = [x for x in packageNames if not rpackages.isinstalled(x)]
if len(packnames_to_install) > 0:
utils.install_packages(StrVector(packnames_to_install))
rpackages.importr('tidyverse')
rpackages.importr('ggsci')
rpackages.importr('ggpubr')
rpackages.importr('dplyr')
rpackages.importr('ggplot2')
hp_hmm_directory = os.path.join(build_op_dir, 'HiPer_spHMMs')
os.makedirs(hp_hmm_directory,0o777,True)
module_dir = os.path.dirname(os.path.abspath(createhmm.__file__))
print("\nR-script path : " + module_dir)
r_script = os.path.join(module_dir,'EvaluateSpHMMs.R')
with open(r_script, 'r') as f:
rStr = f.read()
myfunc = STAP(rStr, "EvaluateSpHMM")
myfunc.EvaluateSpHMM(allHMMResult, allBLASTResult, gene_pos_file, prot_family_name, float(f1_thresh), hmm_directory, hp_hmm_directory)
timeTaken = time.time() - startTime
mins = int(timeTaken / 60)
secs = int(timeTaken) % 60
print("\nTotal time taken : " + str(mins) + " mins " + str(secs) + " seconds")
return hp_hmm_directory
except:
print("Metabgc-build has failed. Please check your inputs and contact support on : https://github.com/donia-lab/MetaBGC")
exit()
def mbgcbuild(prot_alignment, prot_family_name, cohort_name,
nucl_seq_directory, prot_seq_directory, seq_fmt, pair_fmt,
r1_file_suffix, r2_file_suffix, tp_genes_nucl,
blastn_search_directory, hmm_search_directory, f1_thresh,
output_directory, cpu):
startTime = time.time()
if cpu is not None:
CPU_THREADS = int(cpu)
# setup paths
build_op_dir = output_directory + os.sep + "build"
hmm_directory = os.path.join(build_op_dir, 'spHMMs')
prot_aln_file = os.path.join(hmm_directory,
ntpath.basename(prot_alignment))
tp_genes_prot = build_op_dir + os.sep + "TPGenes.faa"
alnOutput = os.path.join(build_op_dir, "tmp.afa")
gene_pos_file = os.path.join(build_op_dir, 'Gene_Interval_Pos.txt')
if hmm_search_directory is None:
hmm_search_directory = os.path.join(build_op_dir, 'hmm_result')
allHMMResult = hmm_search_directory + os.sep + "CombinedHmmSearch.txt"
if blastn_search_directory is None:
blastn_search_directory = os.path.join(build_op_dir, 'blastn_result')
allBLASTResult = blastn_search_directory + os.sep + "CombinedBLASTSearch.txt"
# Gen spHMMs and interval pos
os.makedirs(hmm_directory, 0o777, True)
copyfile(prot_alignment, prot_aln_file)
hmmDict = gensphmmfiles(prot_family_name, prot_aln_file, hmm_directory)
runTranSeq(tp_genes_nucl, "1", tp_genes_prot)
tmpFile = os.path.join(build_op_dir, "tmp.fa")
# Join true positives in the sample with the BGC proteins
joinedSeqs = []
tpGeneSeqs = list(SeqIO.parse(tp_genes_prot, "fasta"))
# Removing _1 added by TranSeq
for seq in tpGeneSeqs:
seq.id = seq.id[:-2]
seq.description = ""
joinedSeqs.append(seq)
protAlnSeqs = list(SeqIO.parse(prot_aln_file, "fasta"))
for seq in protAlnSeqs:
joinedSeqs.append(seq)
SeqIO.write(joinedSeqs, tmpFile, "fasta")
# MUSCLE align TP genes with markers
runMUSCLE(tmpFile, alnOutput)
# Extract spHMM coordinates from MUSCLE alignment
gengeneposlist(prot_family_name, protAlnSeqs, hmmDict, alnOutput,
gene_pos_file)
if r1_file_suffix is None:
r1_file_suffix = ""
if r2_file_suffix is None:
r2_file_suffix = ""
# #Preprocess synthetic reads
nucl_seq_directory = PreProcessReadsPar(nucl_seq_directory, seq_fmt,
pair_fmt, r1_file_suffix.strip(),
r2_file_suffix.strip(),
build_op_dir, CPU_THREADS)
# Translate nucleotide seq
if not os.path.isdir(prot_seq_directory):
prot_seq_directory = TranseqReadsDir(build_op_dir, nucl_seq_directory,
CPU_THREADS)
# HMMER Search
os.makedirs(hmm_search_directory, 0o777, True)
for hmmSeqPosKey, hmmFileObj in hmmDict.items():
hmmInterval = str(hmmDict[hmmSeqPosKey].intervalStart) + "_" + str(
hmmDict[hmmSeqPosKey].intervalEnd)
RunHMMDirectory(prot_seq_directory, hmmFileObj.hmmFile, cohort_name,
prot_family_name, "30_10", hmmInterval,
hmm_search_directory, CPU_THREADS)
with open(allHMMResult, 'w') as outfile:
for subdir, dirs, files in os.walk(hmm_search_directory):
for file in files:
filePath = os.path.join(subdir, file)
if re.match(r".*txt$", file) and os.path.getsize(filePath) > 0:
with open(filePath) as infile:
for line in infile:
outfile.write(line)
# BLAST Alignment
if not os.path.isdir(blastn_search_directory):
os.makedirs(blastn_search_directory, 0o777, True)
RunBLASTNDirectoryPar(nucl_seq_directory, tp_genes_nucl,
blastn_search_directory, CPU_THREADS)
with open(allBLASTResult, 'w') as outfile:
outfile.write(
"sseqid\tslen\tsstart\tsend\tqseqid\tqlen\tqstart\tqend\tpident\tevalue\tSample\tsampleType\n"
)
for subdir, dirs, files in os.walk(blastn_search_directory):
for file in files:
filePath = os.path.join(subdir, file)
if re.match(r".*txt$", file) and os.path.getsize(filePath) > 0:
with open(filePath) as infile:
for line in infile:
sampleName = ntpath.basename(filePath).split(
".txt")[0]
outfile.write(line.strip() + "\t" + sampleName +
"\t" + cohort_name + "\n")
# Eval spHMMs
rpackages.importr('base')
utils = rpackages.importr('utils')
packageNames = ('tidyverse', 'ggsci', 'ggpubr', 'dplyr', 'ggplot2')
packnames_to_install = [
x for x in packageNames if not rpackages.isinstalled(x)
]
if len(packnames_to_install) > 0:
utils.install_packages(StrVector(packnames_to_install))
rpackages.importr('tidyverse')
rpackages.importr('ggsci')
rpackages.importr('ggpubr')
rpackages.importr('dplyr')
rpackages.importr('ggplot2')
hp_hmm_directory = os.path.join(build_op_dir, 'HiPer_spHMMs')
os.makedirs(hp_hmm_directory, 0o777, True)
r_script = os.path.join(sys.path[0], 'metabgc', 'src', 'EvaluateSpHMMs.R')
with open(r_script, 'r') as f:
rStr = f.read()
myfunc = STAP(rStr, "EvaluateSpHMM")
myfunc.EvaluateSpHMM(allHMMResult,
allBLASTResult, gene_pos_file, prot_family_name,
float(f1_thresh), hmm_directory, hp_hmm_directory)
timeTaken = time.time() - startTime
mins = int(timeTaken / 60)
secs = int(timeTaken) % 60
print("\nTotal time taken : " + str(mins) + " mins " + str(secs) +
" seconds")
return hp_hmm_directory
