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...s/auxiliary_workflows/benchmark/resources/method_definitions/viloca_alpha_0.00001_K100.py
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# GROUP: global | ||
# CONDA: libshorah | ||
# CONDA: biopython = 1.79 | ||
# PIP: git+https://github.com/LaraFuhrmann/shorah@master | ||
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import subprocess | ||
from pathlib import Path | ||
from os import listdir | ||
from os.path import isfile, join | ||
from Bio import SeqIO | ||
import gzip | ||
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def gunzip(source_filepath, dest_filepath, block_size=65536): | ||
with gzip.open(source_filepath, "rb") as s_file, open( | ||
dest_filepath, "wb" | ||
) as d_file: | ||
while True: | ||
block = s_file.read(block_size) | ||
if not block: | ||
break | ||
else: | ||
d_file.write(block) | ||
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def main( | ||
fname_bam, | ||
fname_reference, | ||
fname_insert_bed, | ||
fname_results_snv, | ||
fname_result_haplos, | ||
dname_work, | ||
): | ||
genome_size = str(fname_bam).split("genome_size~")[1].split("__coverage")[0] | ||
alpha = 0.00001 | ||
n_max_haplotypes = 100 | ||
n_mfa_starts = 1 | ||
win_min_ext = 0.85 | ||
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read_length = str(fname_bam).split("read_length~")[1].split("__")[0] | ||
if read_length == "Ten_strain_IAV": | ||
sampler = "learn_error_params" | ||
win_min_ext = 0.5 | ||
else: | ||
sampler = "use_quality_scores" | ||
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dname_work.mkdir(parents=True, exist_ok=True) | ||
if fname_insert_bed == []: | ||
subprocess.run( | ||
[ | ||
"shorah", | ||
"shotgun", | ||
"-b", | ||
fname_bam.resolve(), | ||
"-f", | ||
Path(fname_reference).resolve(), | ||
"--mode", | ||
str(sampler), | ||
"--alpha", | ||
str(alpha), | ||
"--n_max_haplotypes", | ||
str(n_max_haplotypes), | ||
"--n_mfa_starts", | ||
str(n_mfa_starts), | ||
"--win_min_ext", | ||
str(win_min_ext), | ||
], | ||
cwd=dname_work, | ||
) | ||
else: | ||
# insert bed file is there | ||
subprocess.run( | ||
[ | ||
"shorah", | ||
"shotgun", | ||
"-b", | ||
fname_bam.resolve(), | ||
"-f", | ||
Path(fname_reference).resolve(), | ||
"-z", | ||
Path(fname_insert_bed).resolve(), | ||
"--mode", | ||
str(sampler), | ||
"--alpha", | ||
str(alpha), | ||
"--n_max_haplotypes", | ||
str(n_max_haplotypes), | ||
"--n_mfa_starts", | ||
str(n_mfa_starts), | ||
"--win_min_ext", | ||
str(win_min_ext), | ||
], | ||
cwd=dname_work, | ||
) | ||
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(dname_work / "snv" / "SNVs_0.010000_final.vcf").rename(fname_results_snv) | ||
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mypath = (dname_work / "support").resolve() | ||
onlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))] | ||
print("onlyfiles", onlyfiles) | ||
for file in onlyfiles: | ||
if "reads-support.fas" in file: | ||
file_name = onlyfiles[0] | ||
fname_haplos = (dname_work / "support" / onlyfiles[0]).resolve() | ||
if file.endswith(".gz"): | ||
fname_zipped = (dname_work / "support" / onlyfiles[0]).resolve() | ||
fname_haplos = onlyfiles[0].split(".gz")[0] | ||
fname_unzipped = (dname_work / "support" / fname_haplos).resolve() | ||
# unzip | ||
gunzip(fname_zipped, fname_result_haplos) | ||
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elif file.endswith(".fas"): | ||
fname_haplos = (dname_work / "support" / onlyfiles[0]).resolve() | ||
(dname_work / "support" / file).rename(fname_result_haplos) | ||
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# fix frequency information | ||
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freq_list = [] | ||
for record in SeqIO.parse(fname_result_haplos, "fasta"): | ||
freq_list.append(float(record.description.split("ave_reads=")[-1])) | ||
norm_freq_list = [float(i) / sum(freq_list) for i in freq_list] | ||
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record_list = [] | ||
for idx, record in enumerate(SeqIO.parse(fname_result_haplos, "fasta")): | ||
record.description = f"freq:{norm_freq_list[idx]}" | ||
record_list.append(record) | ||
SeqIO.write(record_list, fname_result_haplos, "fasta") | ||
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if __name__ == "__main__": | ||
main( | ||
Path(snakemake.input.fname_bam), | ||
Path(snakemake.input.fname_reference), | ||
snakemake.input.fname_insert_bed, | ||
Path(snakemake.output.fname_result), | ||
Path(snakemake.output.fname_result_haplos), | ||
Path(snakemake.output.dname_work), | ||
) |