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sbx_metaphlan4.smk
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sbx_metaphlan4.smk
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# -*- mode: Snakemake -*-
#
# Rules for running Metaphlan4
TARGET_METAPHLAN4_REPORT = [CLASSIFY_FP / "metaphlan4" / "metaphlan4_assignments.tsv"]
TARGET_METAPHLAN4_STRAIN = (
CLASSIFY_FP
/ "metaphlan4"
/ "output_tree"
/ f'{Cfg["sbx_metaphlan4"]["profile_strain"]}.info'
)
try:
BENCHMARK_FP
except NameError:
BENCHMARK_FP = output_subdir(Cfg, "benchmarks")
try:
LOG_FP
except NameError:
LOG_FP = output_subdir(Cfg, "logs")
rule all_metaphlan4:
input:
TARGET_METAPHLAN4_REPORT,
TARGET_METAPHLAN4_STRAIN
if Cfg["sbx_metaphlan4"]["profile_strain"]
else TARGET_METAPHLAN4_REPORT,
rule taxonomic_assignment_report:
""" generate metaphlan taxonomic assignment table """
log:
LOG_FP / "metaphlan4_report.log",
benchmark:
BENCHMARK_FP / "metaphlan4_report.tsv"
output:
CLASSIFY_FP / "metaphlan4" / "metaphlan4_assignments.tsv",
input:
expand(
CLASSIFY_FP / "metaphlan4" / "profiles" / "{sample}.profiled.txt",
sample=Samples.keys(),
),
conda:
"envs/sbx_metaphlan4_env.yml"
shell:
"""
merge_metaphlan_tables.py \
-o {output} \
{input} 2>&1 | tee {log}
"""
rule metaphlan4_bowtie:
""" make individual metaphlan profiles with intermediate bowtie outputs """
log:
LOG_FP / "metaphlan4_bowtie_{sample}.log",
benchmark:
BENCHMARK_FP / "metaphlan4_bowtie_{sample}.tsv"
output:
bt2=CLASSIFY_FP / "metaphlan4" / "bowtie2out" / "{sample}.bowtie2.bz2",
profile=CLASSIFY_FP / "metaphlan4" / "profiles" / "{sample}.profiled.txt",
sam=CLASSIFY_FP / "metaphlan4" / "sams" / "{sample}.sam.bz2",
input:
pair=expand(QC_FP / "decontam" / "{{sample}}_{rp}.fastq.gz", rp=Pairs),
params:
dbdir=Cfg["sbx_metaphlan4"]["dbdir"],
dbname=Cfg["sbx_metaphlan4"]["dbname"],
threads: Cfg["sbx_metaphlan4"]["threads"]
conda:
"envs/sbx_metaphlan4_env.yml"
shell:
"""
metaphlan {input.pair[0]},{input.pair[1]} \
-t rel_ab_w_read_stats \
--bowtie2out {output.bt2} \
--samout {output.sam} \
--nproc {threads} \
--input_type fastq \
--bowtie2db {params.dbdir} \
--index {params.dbname} \
-o {output.profile} \
2>&1 | tee {log}
"""
rule extract_markers:
""" extract markers for a given strain """
log:
LOG_FP / "extract_markers.log",
benchmark:
BENCHMARK_FP / "extract_markers.tsv"
output:
CLASSIFY_FP
/ "metaphlan4"
/ "db_markers"
/ f'{Cfg["sbx_metaphlan4"]["profile_strain"]}.fna',
input:
pickle=f'{Cfg["sbx_metaphlan4"]["dbdir"]}/{Cfg["sbx_metaphlan4"]["dbname"]}.pkl',
params:
strain=Cfg["sbx_metaphlan4"]["profile_strain"],
dbmarkers=CLASSIFY_FP / "metaphlan4" / "db_markers",
conda:
"envs/sbx_metaphlan4_env.yml"
shell:
"""
extract_markers.py \
-d {input.pickle} \
-c {params.strain} \
-o {params.dbmarkers} \
2>&1 | tee {log}
"""
# need to write this as a python script since it errors out if the sam file is empty
# basically just need to create an empty .pkl file of the sample with only the contents "[]"
rule consensus_markers:
""" extract consensus markers from the samples """
log:
LOG_FP / "{sample}_consensus_markers.log",
benchmark:
BENCHMARK_FP / "{sample}_consensus_markers.tsv"
output:
CLASSIFY_FP / "metaphlan4" / "consensus_markers" / "{sample}.pkl",
input:
CLASSIFY_FP / "metaphlan4" / "sams" / "{sample}.sam.bz2",
params:
outdir=CLASSIFY_FP / "metaphlan4" / "consensus_markers",
pickle=f'{Cfg["sbx_metaphlan4"]["dbdir"]}/{Cfg["sbx_metaphlan4"]["dbname"]}.pkl',
threads: Cfg["sbx_metaphlan4"]["threads"]
conda:
"envs/sbx_metaphlan4_env.yml"
script:
"scripts/consensus_markers.py"
rule build_tree:
""" Build the multiple sequence alignment and the phylogenetic tree """
log:
LOG_FP / "build_tree.log",
benchmark:
BENCHMARK_FP / "build_tree.tsv"
output:
CLASSIFY_FP
/ "metaphlan4"
/ "output_tree"
/ f'{Cfg["sbx_metaphlan4"]["profile_strain"]}.info',
input:
consensus_markers=expand(
CLASSIFY_FP / "metaphlan4" / "consensus_markers" / "{sample}.pkl",
sample=Samples.keys(),
),
db_markers=CLASSIFY_FP
/ "metaphlan4"
/ "db_markers"
/ f'{Cfg["sbx_metaphlan4"]["profile_strain"]}.fna',
params:
dbdir=Cfg["sbx_metaphlan4"]["dbdir"],
dbname=Cfg["sbx_metaphlan4"]["dbname"],
marker_dir=CLASSIFY_FP / "metaphlan4" / "consensus_markers",
strain=Cfg["sbx_metaphlan4"]["profile_strain"],
ref_genome=Cfg["sbx_metaphlan4"]["reference_genome"],
output_dir=CLASSIFY_FP / "metaphlan4" / "output_tree",
threads: Cfg["sbx_metaphlan4"]["threads"]
conda:
"envs/sbx_metaphlan4_env.yml"
shell:
"""
rm -rf {params.marker_dir}/tmp* &&
mkdir -p {params.output_dir} && \
strainphlan \
-d {params.dbdir}/{params.dbname}.pkl \
-s {input.consensus_markers} \
-m {input.db_markers} \
-r {params.ref_genome} \
-o {params.output_dir} -n {threads} \
-c {params.strain} --mutation_rates \
2>&1 | tee {log}
"""