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mapping_pipeline.snake
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mapping_pipeline.snake
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## SeA-SnaP mapping pipeline for RNA-seq analysis
## version: 1.0
## author: J.P.Pett (patrick.pett@bihealth.de)
#TODO: dupradar into snakefile
import os, sys, yaml, re, textwrap, pandas as pd
from collections import OrderedDict
from time import asctime, localtime, time
from pathlib import Path
from snakemake.utils import report, format as snakemake_format, min_version
from snakemake.logging import logger
from tools.pipeline_tools import MappingPipelinePathHandler, ReportTool
yaml.add_representer(OrderedDict, lambda dumper, data: dumper.represent_dict(dict(data)))
min_version("3.7")
shell.prefix("set -e pipefail;")
# source files
SNAKEDIR = Path(workflow.current_basedir)
SNAKEFILE = workflow.snakefile
SCRIPTDIR = str(SNAKEDIR / "external_scripts")
# assemble config
config_file_name = config["file_name"] if "file_name" in config else "mapping_config.yaml"
configfile: str(SNAKEDIR / "defaults" / "mapping_config_defaults.yaml")
configfile: config_file_name
configfile: "sample_info.yaml"
if config["organism_defaults"]:
configfile: str(SNAKEDIR / "defaults" / config["organism_defaults"])
configfile: config_file_name
# create path handler
conf_ranges = str(SNAKEDIR / "defaults" / "mapping_config_ranges.yaml")
test_config = conf_ranges if config["pipeline_param"]["test_config"] else None
pph = MappingPipelinePathHandler(workflow, test_config)
# link indices
pph.link_index(step="star_index", fix="all")
pph.link_index(step="bwa_index", fix="all", add_done=True, subdir="index")
pph.link_index(step="salmon_index", fix="all")
pph.link_index(step="generate_transcriptome", fix="all", entry=config["organism"]["files"]["transcriptome"], subdir="transcriptome.fa")
# exclude symbols '.' and '/' from wildcards
wildcard_constraints:
sample="[^./]+",
mate ="[^./]+"
onstart:
# draw a dag
dag_file = pph.file_path(step="pipeline_report", extension="rule_execution.png", fix="all")
os.makedirs(os.path.dirname(dag_file), exist_ok=True)
shell("snakemake --quiet --snakefile {} --rulegraph | dot -Tpng > {}".format(SNAKEFILE, dag_file))
# info about the pipeline run
info_file = pph.file_path(step="pipeline_report", extension="summary.csv", fix="all")
os.makedirs(os.path.dirname(info_file), exist_ok=True)
shell("snakemake --quiet --snakefile {} --summary | sed 's/\t/, /g' > {}".format(SNAKEFILE, info_file))
# save merged config
config_file = pph.file_path(step="pipeline_report", extension="yaml", fix="all")
with open(config_file, "w") as f: yaml.dump(config, f, default_flow_style=False)
# warnings
mapping_choices, qc_choices = (config["pipeline_param"][key] for key in ["mapping_results", "QC_results"])
for qc_step in ["dupradar", "infer_experiment", "rna_seqc", "qualimap", "qc"]:
if qc_step in qc_choices and "star-gene_counts" not in mapping_choices:
logger.warning("{}: cannot run, because 'star-gene_counts' was not selected as mapping output".format(qc_step))
##-------------------- starting point ----------------------------------------------------------------------
def get_inputs_all():
inputs = []
# mapping results
mapping_choices = config["pipeline_param"]["mapping_results"]
if "star-gene_counts" in mapping_choices:
inputs += pph.expand_path("star", "bam", fix="!sample")
inputs += pph.expand_path("feature_counts", "feature_counts", fix="!sample")
if "salmon-transcript_counts" in mapping_choices:
inputs += pph.expand_path("salmon", "sf", fix="!sample")
if "ciri-circRNA" in mapping_choices:
inputs += pph.expand_path("bwa", "bam", fix="!sample")
inputs += pph.expand_path("ciri", "tsv", fix="!sample")
elif "bwa-gene_counts" in mapping_choices:
inputs += pph.expand_path("bwa", "bam", fix="!sample")
# QC results
qc_choices = config["pipeline_param"]["QC_results"]
if "fastqc" in qc_choices:
inputs += pph.expand_path("fastqc", "zip_names.txt")
if "star-gene_counts" in mapping_choices:
if "dupradar" in qc_choices:
inputs += pph.expand_path("dupradar", "done", fix="!sample")
if "rna_seqc" in qc_choices:
inputs += pph.expand_path("rna_seqc", "done", fix="!sample")
if "preseq_lc_extrap" in qc_choices:
inputs += pph.expand_path("preseq_lc_extrap", "future_yield.txt", fix="!sample")
if "preseq_c_curve" in qc_choices:
inputs += pph.expand_path("preseq_c_curve", "complexity.txt", fix="!sample")
if "qualimap_rnaseq" in qc_choices:
inputs += pph.expand_path("qualimap_rnaseq", "done", fix="!sample")
if "qualimap_bamqc" in qc_choices:
inputs += pph.expand_path("qualimap_bamqc", "done", fix="!sample")
if "infer_experiment" in qc_choices:
inputs += pph.expand_path("infer_experiment", "strand_stat.txt", fix="!sample")
if "qc" in qc_choices:
inputs += pph.expand_path("qc", "done", fix="!sample")
if "bw_from_bam" in qc_choices:
inputs += pph.expand_path("bw_from_bam", "bw", fix="!sample")
# ATAC-seq
if "ATAC_Seq" in config["pipeline_param"]:
atacseq_choices = config["pipeline_param"]["ATAC_Seq"]
if "macs2" in atacseq_choices:
inputs += pph.expand_path("macs2", "summits.bed", fix="!sample")
return inputs
shell("rm -f {}".format(pph.file_path(step="pipeline_report", extension="report.html", fix="all")))
rule all:
input:
get_inputs_all(),
pph.file_path(step="multiqc", extension="qc_report.html", fix="all")
output:
html = pph.file_path(step="pipeline_report", extension="report.html", fix="all")
run:
mappers = "".join(["- {}\n".format(mapper) for mapper in config["pipeline_param"]["mapping_results"]])
quality_control = "".join(["- {}\n".format(qc) for qc in config["pipeline_param"]["QC_results"]])
loctime = asctime(localtime(time()))
rule_execution = pph.file_path("pipeline_report", "rule_execution.png", fix="all")
summary = pph.file_path("pipeline_report", "summary.csv", fix="all")
version_info = pph.file_path("pipeline_report", "version_info.txt", fix="all")
conda_info = pph.file_path("pipeline_report", "conda_info.txt", fix="all")
dag = rule_execution.split("/")[-1]
shell("conda list > {}".format(version_info))
shell("conda info > {}".format(conda_info))
report("""
=======================
RNAseq mapping pipeline
=======================
**Finished: {loctime}**
Produce mapping results:
{mappers}
Produce quality control results:
{quality_control}
.. image:: {dag}
File status at pipeline start:
==============================
.. csv-table::
:file: {summary}
Version info:
=============
.. include:: {version_info}
:literal:
Conda info:
===========
.. include:: {conda_info}
:literal:
""", output.html, graph = rule_execution, table = summary)
rule export:
""" export files for upload to SODAR """
input:
get_inputs_all()
run:
pph.export()
rule UCSC_export:
""" export files for UCSC track hub """
input:
get_inputs_all()
run:
pph.export(config_key = "UCSC_export")
##-------------------- fastqc -------------------------------------------------------------------------------
rule fastqc:
""" run fastqc for quality control of reads """
input:
pph.get_fastq_pairs
output:
fzip = pph.file_path(step="fastqc", extension="zip_names.txt"),
html = pph.file_path(step="fastqc", extension="html_names.txt")
log:
out = pph.file_path(step="fastqc", extension="output.log", log=True)
params:
outdir = pph.out_dir_name(step="fastqc")
threads: 2
resources:
mem_mb=4000,
h_rt="24:00:00"
run:
reads = " ".join(input)
script = textwrap.dedent(r"""
#----- prepare
set -eux
fastqc --version
rm -fr {params.outdir}/*
#----- run fastqc
fastqc -o {params.outdir} -t {threads} {reads}
#----- save fastqc output names
find {params.outdir} -type f -name '*.zip' > {output.fzip}
find {params.outdir} -type f -name '*.html' > {output.html}
""")
script_file = pph.log(log.out, snakemake_format(script), step="fastqc", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
##-------------------- star ---------------------------------------------------------------------------------
rule star_index:
input:
genome = lambda wildcards: config["organism"]["files"]["genome"] if wildcards.sample=="all_samples" else config["sample_info"][wildcards.sample]["genome"],
gtf = lambda wildcards: config["organism"]["files"]["gtf"] if wildcards.sample=="all_samples" else config["sample_info"][wildcards.sample]["gtf"]
output:
index = pph.out_dir_name(step = "star_index")+"/SA"
log:
out = pph.file_path(step="star_index", extension="output.log", log=True)
params:
options = config["rule_options"]["star_index"]["cmd_opt"]
threads: 8
resources:
mem_mb=64000,
h_rt="24:00:00"
run:
script = textwrap.dedent(r"""
#----- prepare
set -eux
rm -fr $(dirname {output.index})/*
STAR --version
#----- run STAR index
STAR --runMode genomeGenerate --genomeDir $(dirname {output}) --outFileNamePrefix $(dirname {log.out})/ --genomeFastaFiles {input.genome} \
--sjdbGTFfile {input.gtf} --runThreadN {threads} {params.options}
""")
script_file = pph.log(log.out, snakemake_format(script), step="star_index", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
def get_star_index (wildcards):
"""get star index or compute one for all or specific samples"""
# if there's a sample-specific star index (precomputed)
if "star_index" in config["sample_info"][wildcards.sample]:
#print("using pre-computed star index for "+wildcards.sample)
return config["sample_info"][wildcards.sample]["star_index"] + "/SA"
# if there's a sample-specific genome and gtf
elif "genome" in config["sample_info"][wildcards.sample] and "gtf" in config["sample_info"][wildcards.sample]:
#print("using newly computed star index for "+wildcards.sample)
return pph.out_dir_name(step = "star_index", fix="!sample", sample = wildcards.sample) + "/SA"
# otherwise
else:
if "star_index" in config["organism"] and config["organism"]["star_index"] is not None:
#print("using pre-computed global star index for "+wildcards.sample)
return config["organism"]["star_index"] + "/SA"
else:
#print("using newly computed global star index for "+wildcards.sample)
return pph.out_dir_name(step = "star_index", fix="all") + "/SA"
rule star:
input:
index = get_star_index,
reads1 = lambda wildcards: pph.get_fastq_pairs(wildcards, mate_key="paired_end_extensions", mate=0),
reads2 = lambda wildcards: pph.get_fastq_pairs(wildcards, mate_key="paired_end_extensions", mate=1) #identical if unstranded
output:
bam = pph.file_path(step="star", extension="bam"),
usrt_bam = temp(pph.file_path(step="star", extension="unsorted.bam")),
gene_counts = pph.file_path(step="star", extension="gene_counts.tab")
log:
out = pph.file_path(step="star", extension="output.log", log=True)
params:
outdir = pph.out_dir_name(step="star"),
options = config["rule_options"]["star"]["cmd_opt"],
trim = True if config["rule_options"]["star"]["trim"]=="yes" else False
threads: 16
resources:
mem_mb=48000,
h_rt="24:00:00"
run:
# prepare read input
reads = ",".join(input.reads1)
stranded = input.reads1 != input.reads2
if stranded: reads += " " + ",".join(input.reads2)
# output column for gene counts
count_col = {"unstranded":2, "forward":3, "reverse":4}[config["sample_info"][wildcards.sample]["stranded"]]
# prepare trimming option
file_ext = config["sample_info"][wildcards.sample]["read_extension"].split(".")[-1]
if params.trim:
trim_cmd = "--readFilesCommand \"trimadap-mt -p {}\"".format(threads // 2)
elif file_ext == "fastq":
trim_cmd = ""
elif file_ext == "gz":
trim_cmd = "--readFilesCommand zcat"
else:
raise ValueError("STAR input: file extension {} not supported.".format(file_ext))
# set read groups
read_group_lines = []
for readfile in input.reads1:
read_group_line = ' "ID:{sample}" "SM:{sample}"'.format(sample=wildcards.sample)
input_wildcards = pph.wildcard_values_from(readfile)
if "library" in input_wildcards: read_group_line += ' "LB:{}"'.format(input_wildcards["library"])
if "instrument" in config["sample_info"][wildcards.sample]: read_group_line += ' "PL:{}"'.format(config["sample_info"][wildcards.sample]["instrument"])
fc="flowcell" in input_wildcards
ln="lane" in input_wildcards
if fc or ln: read_group_line += ' "PU:{}.{}"'.format(input_wildcards["flowcell"] if fc else "", input_wildcards["lane"] if ln else "")
read_group_lines.append(read_group_line)
read_groups = "--outSAMattrRGline" + " , ".join(read_group_lines)
script = textwrap.dedent(r"""
#----- prepare
set -eux
rm -fr {params.outdir}/*
STAR --version
samtools --version
#----- run STAR mapping
STAR --quantMode GeneCounts --readFilesIn {reads} --genomeDir $(dirname {input.index}) --runThreadN {threads} \
--outFileNamePrefix {params.outdir}/ {params.options} {trim_cmd} {read_groups}
cut -f1,{count_col} {params.outdir}/ReadsPerGene.out.tab > {output.gene_counts}
mv {params.outdir}/ReadsPerGene.out.tab {params.outdir}/{wildcards.sample}.ReadsPerGene.out.tab #for multiqc
mv {params.outdir}/Log.final.out {params.outdir}/{wildcards.sample}.Log.final.out #for multiqc
#----- sort BAM (coordinate sort)
samtools sort -@ $(expr {threads} / 2) -m $(expr 10000 / {threads})M -T {params.outdir}/sort -o {output.bam} {params.outdir}/Aligned.out.bam
mv {params.outdir}/Aligned.out.bam {output.usrt_bam}
#----- mark duplicates
picard -Xmx48G MarkDuplicates I={output.bam} O={params.outdir}/{wildcards.sample}.mdup.bam M={params.outdir}/{wildcards.sample}.metrics.out TMP_DIR={params.outdir}
mv {params.outdir}/{wildcards.sample}.mdup.bam {output.bam}
#----- generate BAM index (.bai)
samtools index {output.bam}
#----- compute statistics
samtools stats {output.bam} > $(dirname {log.out})/star.{wildcards.sample}.bamstats.txt
samtools flagstat {output.bam} > $(dirname {log.out})/star.{wildcards.sample}.flagstat.log
samtools idxstats {output.bam} > $(dirname {log.out})/star.{wildcards.sample}.idxstats.log
""")
script_file = pph.log(log.out, snakemake_format(script), step="star", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
## -----------------------------------------------------------------------------------
## Create BW files suitable for IGV / USCS browser
## -----------------------------------------------------------------------------------
rule bw_from_bam:
input:
bam = pph.file_path(step="star", extension="bam"),
output:
pph.file_path(step="bw_from_bam", extension="bw")
log:
out = pph.file_path(step="bw_from_bam", extension="output.log", log=True)
resources:
mem_mb=32000,
h_rt="4:00:00"
run:
genome_size=config["organism"]["genome_size"]
script = textwrap.dedent(r"""
#----- prepare
set -eux
bamCoverage --version
#----- run bamCoverage
bamCoverage --bam {input.bam} --outFileFormat bigwig --outFileName {output} --effectiveGenomeSize {genome_size} --extendReads --normalizeUsing RPGC
""")
script_file = pph.log(log.out, snakemake_format(script), step="bw_from_bam", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
## -----------------------------------------------------------------------------------
## Run macs2 to detect peaks in ATAC-Seq
## -----------------------------------------------------------------------------------
rule macs2:
input:
bam = pph.file_path(step="star", extension="bam"),
output:
bed=pph.file_path(step="macs2", extension="summits.bed"),
pn=pph.file_path(step="macs2", extension="peaks.narrowPeak")
log:
out = pph.file_path(step="macs2", extension="output.log", log=True)
resources:
mem_mb=32000,
h_rt="24:00:00"
run:
genome_abbr=config["organism"]["abbreviation"]
script = textwrap.dedent(r"""
#----- prepare
set -eux
macs2 --version
#----- run macs2
macs2 callpeak -t {input.bam} -f BAMPE --outdir $(dirname {output.bed}) --name $(basename {output.bed} .summits.bed) -g {genome_abbr}
mv $(dirname {output.bed})/$(basename {output.bed} .summits.bed)_summits.bed {output.bed}
mv $(dirname {output.pn})/$(basename {output.pn} .peaks.narrowPeak)_peaks.narrowPeak {output.pn}
""")
script_file = pph.log(log.out, snakemake_format(script), step="macs2", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
##-------------------- bwa ---------------------------------------------------------------------------------
GENOME_FILE_NAME = os.path.basename(config["organism"]["files"]["genome"])
rule bwa_index:
""" create index for BWA """
input:
genome = config["organism"]["files"]["genome"]
output:
done = touch(pph.file_path(step="bwa_index", extension="done")),
index = directory(pph.out_dir_name(step = "bwa_index") + "/index")
log:
out = pph.file_path(step="bwa_index", extension="output.log", log=True)
params:
options = config["rule_options"]["bwa_index"]["cmd_opt"]
resources:
mem_mb=32000,
h_rt="24:00:00"
run:
db_prefix = os.path.join(output.index, GENOME_FILE_NAME)
script = textwrap.dedent(r"""
#----- prepare
set -eux
rm -fr $(dirname {output.index})/*
#----- run bwa index
mkdir -p $(dirname {db_prefix})
ln -s {input.genome} {db_prefix}
bwa index {params.options} {db_prefix}
""")
script_file = pph.log(log.out, snakemake_format(script), step="bwa_index", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
rule bwa:
""" run BWA mem """
input:
index_present = pph.file_path(step="bwa_index", extension="done", fix="all"),
reads1 = lambda wildcards: pph.get_fastq_pairs(wildcards, mate_key="paired_end_extensions", mate=0),
reads2 = lambda wildcards: pph.get_fastq_pairs(wildcards, mate_key="paired_end_extensions", mate=1) #identical if unpaired
output:
bam = pph.file_path(step="bwa", extension="bam")
log:
out = pph.file_path(step="bwa", extension="output.log", log=True)
params:
sam = pph.file_path(step="bwa", extension="sam"),
options = config["rule_options"]["bwa"]["cmd_opt"],
index_dir = pph.out_dir_name(step = "bwa_index", fix="all") + "/index",
trim = True if config["rule_options"]["bwa"]["trim"]=="yes" else False,
run_stats = "true" if config["rule_options"]["bwa"]["run_stats"] else "false"
threads: 8
resources:
mem_mb=32000,
h_rt="24:00:00"
run:
db_prefix = os.path.join(params.index_dir, GENOME_FILE_NAME)
# prepare read input
unpaired = input.reads1 == input.reads2
file_ext = config["sample_info"][wildcards.sample]["read_extension"].split(".")[-1]
if params.trim:
preprocess = f"trimadap-mt -p {threads//2}"
elif file_ext == "gz":
preprocess = "zcat"
else:
preprocess = "echo"
if unpaired:
reads = f"<({preprocess} {' '.join(input.reads1)})"
else:
reads = f"<({preprocess} {' '.join(input.reads1)}) <({preprocess} {' '.join(input.reads2)})"
script = textwrap.dedent(r"""
#----- prepare
set -eux
rm -fr $(dirname {output.bam})/*
#----- run bwa mem
bwa mem {params.options} -t {threads} {db_prefix} {reads} 1> {params.sam}
#----- convert to bam
#samtools sort -@ {threads} -O bam -o {output.bam} {params.sam}
samtools view -bS {params.sam} > {output.bam}
rm {params.sam}
#----- build index
#samtools index {output.bam}
#----- compute statistics
if {params.run_stats}; then
samtools stats {output.bam} > $(dirname {output.bam})/bwa.{wildcards.sample}.bamstats.txt
samtools flagstat {output.bam} > $(dirname {output.bam})/bwa.{wildcards.sample}.flagstat.log
#samtools idxstats {output.bam} > $(dirname {output.bam})/bwa.{wildcards.sample}.idxstats.log
fi
""")
script_file = pph.log(log.out, snakemake_format(script), step="bwa", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
##-------------------- ciri -------------------------------------------------------------------------------
rule ciri:
input:
index_present = pph.file_path(step="bwa_index", extension="done", sample = "all_samples", flowcell="all_flowcells", lane="all_lanes", mate="all_mates", library="all_libraries"),
bam = pph.file_path(step="bwa", extension="bam"),
gtf = config["organism"]["files"]["gtf"],
genome = config["organism"]["files"]["genome"]
output:
pph.file_path(step="ciri", extension="tsv")
log:
out = pph.file_path(step="ciri", extension="output.log", log=True)
params:
sam = pph.file_path(step="ciri", extension="sam"),
options = config["rule_options"]["ciri"]["cmd_opt"]
threads: 8
resources:
mem_mb=32000,
h_rt="24:00:00"
run:
samtools_threads = threads//2
script = textwrap.dedent(r"""
#----- prepare
set -eux
rm -fr $(dirname {output})/*
perl {SCRIPTDIR}/CIRI2.pl --help
#----- run ciri
samtools view -h -o {params.sam} {input.bam}
perl {SCRIPTDIR}/CIRI2.pl -I {params.sam} -O {output} -F {input.genome} -A {input.gtf} -T {samtools_threads} {params.options} -G {log.out}
rm {params.sam}
""")
script_file = pph.log(log.out, snakemake_format(script), step="ciri", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
##-------------------- salmon -------------------------------------------------------------------------------
rule generate_transcriptome:
input:
genome = config["organism"]["files"]["genome"],
gtf = config["organism"]["files"]["gtf"]
output:
pph.out_dir_name(step = "generate_transcriptome")+"/transcriptome.fa"
log:
out = pph.file_path(step = "generate_transcriptome", extension="output.log", log=True)
threads: 8
resources:
mem_mb=32000,
h_rt="24:00:00"
run:
script = textwrap.dedent(r"""
#----- prepare
set -eux
rm -fr $(dirname {output})/*
#----- generate transcriptome
rsem-prepare-reference --gtf {input.gtf} {input.genome} $(dirname {output})/$(basename {output} .fa)
mv $(dirname {output})/$(basename {output} .fa).idx.fa {output}
""")
script_file = pph.log(log.out, snakemake_format(script), step="generate_transcriptome", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
rule salmon_index:
input:
transcriptome = pph.out_dir_name(step = "generate_transcriptome")+"/transcriptome.fa",
genome = config["organism"]["files"]["genome"]
output:
index = pph.out_dir_name(step = "salmon_index")+"/pos.bin"
log:
out = pph.file_path(step = "salmon_index", extension="output.log", log=True)
params:
options = config["rule_options"]["salmon_index"]["cmd_opt"]
resources:
mem_mb=32000,
h_rt="24:00:00"
run:
script = textwrap.dedent(r"""
#----- prepare
set -eux
rm -fr $(dirname {output.index})/*
logdir=$(dirname {log.out})
salmon --version
#----- extract names of genome targets
grep "^>" <(gunzip -cf {input.genome}) | cut -d " " -f 1 > $logdir/decoys.txt
sed -i.bak -e 's/>//g' $logdir/decoys.txt
#----- make gentrome
gzip -cdf {input.transcriptome} {input.genome} | gzip > $logdir/gentrome.fa.gz
#----- Salmon index
salmon index -t $logdir/gentrome.fa.gz -d $logdir/decoys.txt -i $(dirname {output.index}) {params.options}
#----- cleanup
rm -f $logdir/gentrome.fa.gz
""")
script_file = pph.log(log.out, snakemake_format(script), step="salmon_index", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
rule salmon:
input:
index = pph.out_dir_name(step = "salmon_index", fix="all")+"/pos.bin",
reads1 = lambda wildcards: pph.get_fastq_pairs(wildcards, mate_key="paired_end_extensions", mate=0),
reads2 = lambda wildcards: pph.get_fastq_pairs(wildcards, mate_key="paired_end_extensions", mate=1) #identical if unpaired
output:
sf = pph.file_path(step = "salmon", extension="sf")
log:
out = pph.file_path(step = "salmon", extension="output.log", log=True)
params:
options = config["rule_options"]["salmon"]["cmd_opt"],
trim = True if config["rule_options"]["salmon"]["trim"]=="yes" else False
threads: 8
resources:
mem_mb=32000,
h_rt="24:00:00"
run:
# prepare read input and trimming
unpaired = input.reads1 == input.reads2
if params.trim:
if unpaired:
reads = "-r <(for var in {rds}; do trimadap-mt $var -p {thr}; done)".format(thr=threads//2, rds=" ".join(input.reads1))
else:
reads = "-1 <(trimadap-mt -p {thr} {rds1}) -2 <(trimadap-mt -p {thr} {rds2})".format(thr=threads//2, rds1=" ".join(input.reads1), rds2=" ".join(input.reads2))
else:
if unpaired:
reads = "-r {rds}".format(rds=" ".join(input.reads1))
else:
reads = "-1 {rds1} -2 {rds2}".format(rds1=" ".join(input.reads1), rds2=" ".join(input.reads2))
script = textwrap.dedent(r"""
#----- prepare
set -eux
rm -fr $(dirname {output.sf})/*
salmon --version
#----- Salmon mapping
salmon quant --validateMappings -i $(dirname {input.index}) -l A {reads} -p {threads} {params.options} -o $(dirname {output.sf})
mv $(dirname {output.sf})/quant.sf {output.sf}
ln -s meta_info.json $(dirname {output.sf})/aux_info/{wildcards.sample}.meta_info.json #for multiqc
mv $(dirname {output.sf})/libParams/flenDist.txt $(dirname {output.sf})/libParams/{wildcards.sample}.flenDist.txt #for multiqc
""")
script_file = pph.log(log.out, snakemake_format(script), step="salmon", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
##-------------------- feature counts -----------------------------------------------------------------------
rule feature_counts:
input:
bam = pph.file_path(step="star", extension="unsorted.bam"),
gtf = config["organism"]["files"]["gtf"]
output:
pph.file_path(step="feature_counts", extension="feature_counts")
log:
out = pph.file_path(step="feature_counts", extension="output.log", log=True)
params:
nsrt_bam = pph.file_path(step="feature_counts", extension="name_sorted.bam"),
options = config["rule_options"]["feature_counts"]["cmd_opt"]
threads: 2
resources:
mem_mb=32000,
h_rt="24:00:00"
run:
protocol = {"unstranded":0, "forward":1, "reverse":2}[config["sample_info"][wildcards.sample]["stranded"]]
paired = "-p" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else ""
script = textwrap.dedent(r"""
#----- prepare
set -eux
samtools --version
#----- sort BAM (name sort)
samtools sort -n -@ $(expr {threads} \* 2) -m $(expr 2500 / {threads})M -T $(dirname {output})/sort -o {params.nsrt_bam} {input.bam}
#----- feature counts
featureCounts {params.options} -T {threads} -t exon -g gene_id -a {input.gtf} -s {protocol} {paired} -o {output} {params.nsrt_bam}
#----- clean up
rm {params.nsrt_bam}
""")
script_file = pph.log(log.out, snakemake_format(script), step="feature_counts", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
##-------------------- dupradar -----------------------------------------------------------------------------
rule dupradar:
input:
bam = pph.file_path(step="star", extension="bam"),
gtf = config["organism"]["files"]["gtf"]
output:
touch(pph.file_path(step="dupradar", extension="done"))
log:
out = pph.file_path(step="dupradar", extension="output.log", log=True)
threads: 8
resources:
mem_mb=32000,
h_rt="24:00:00"
run:
protocol = {"unstranded":0, "forward":1, "reverse":2}[config["sample_info"][wildcards.sample]["stranded"]]
paired = "TRUE" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else "FALSE"
script = textwrap.dedent(r"""
#----- prepare
set -eux
#----- work on temp dir (because of sort)
TMPDIR=$(mktemp -d)
trap "rm -rf $TMPDIR" EXIT
bam=$(realpath {input.bam})
gtf=$(realpath {input.gtf})
out=$(realpath {output})
cd $TMPDIR
#----- dupradar
Rscript --vanilla {SCRIPTDIR}/dupradar.R $bam {wildcards.sample} $gtf {protocol} {paired} {threads} $(dirname $out)
""")
script_file = pph.log(log.out, snakemake_format(script), step="dupradar", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
##-------------------- infer experiment ---------------------------------------------------------------------
rule infer_experiment:
input:
bam = pph.file_path(step="star", extension="bam"),
bed = config["organism"]["files"]["bed"]
output:
pph.file_path(step="infer_experiment", extension="strand_stat.txt")
log:
out = pph.file_path(step="infer_experiment", extension="output.log", log=True)
resources:
mem_mb=32000,
h_rt="24:00:00"
run:
script = textwrap.dedent(r"""
#----- prepare
set -eux
#----- infer experiment
infer_experiment.py -r {input.bed} -i {input.bam} -q 255 > {output}
""")
script_file = pph.log(log.out, snakemake_format(script), step="infer_experiment", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
##-------------------- preseq -------------------------------------------------------------------------------
rule preseq_lc_extrap:
input:
bam = pph.file_path(step="star", extension="bam")
output:
pph.file_path(step="preseq_lc_extrap", extension="future_yield.txt")
log:
out = pph.file_path(step="preseq_lc_extrap", extension="output.log", log=True)
resources:
mem_mb=32000,
h_rt="24:00:00"
run:
paired = "-P" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else ""
script = textwrap.dedent(r"""
#----- prepare
set -eux
preseq
#----- infer experiment
preseq lc_extrap -v {paired} -B {input.bam} -o {output} -l 10000000
""")
script_file = pph.log(log.out, snakemake_format(script), step="preseq_lc_extrap", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
rule preseq_c_curve:
input:
bam = pph.file_path(step="star", extension="bam")
output:
pph.file_path(step="preseq_c_curve", extension="complexity.txt")
log:
out = pph.file_path(step="preseq_c_curve", extension="output.log", log=True)
resources:
mem_mb=32000,
h_rt="24:00:00"
run:
paired = "-P" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else ""
script = textwrap.dedent(r"""
#----- prepare
set -eux
preseq
#----- infer experiment
preseq c_curve -v {paired} -B {input.bam} -o {output} -l 10000000
""")
script_file = pph.log(log.out, snakemake_format(script), step="preseq_c_curve", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
##-------------------- qualimap -----------------------------------------------------------------------------
rule qualimap_rnaseq:
input:
bam = pph.file_path(step="star", extension="bam"),
gtf = config["organism"]["files"]["gtf"]
output:
outdir = directory(pph.file_path(step="qualimap_rnaseq", extension="results")),
done = touch(pph.file_path(step="qualimap_rnaseq", extension="done"))
log:
out = pph.file_path(step="qualimap_rnaseq", extension="output.log", log=True)
resources:
mem_mb=32000,
h_rt="24:00:00"
run:
protocol = {"unstranded":"non-strand-specific", "forward":"strand-specific-forward", "reverse":"strand-specific-reverse"}[config["sample_info"][wildcards.sample]["stranded"]]
paired = "-pe" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else ""
script = textwrap.dedent(r"""
#----- prepare
set -eux
#----- set tmpdir
export TMPDIR=$(mktemp -d)
trap "rm -rf $TMPDIR" EXIT
export JAVA_OPTS="-Djava.io.tmpdir=$TMPDIR"
#----- rna-seqc
qualimap --java-mem-size={resources.mem_mb}M rnaseq -bam {input.bam} -gtf {input.gtf} -outdir {output.outdir} -p {protocol} {paired}
find {output.outdir} -name "*.txt" -exec sh -c 'mv "{{}}" $(dirname "{{}}")/{wildcards.sample}_$(basename "{{}}")' \;
""")
script_file = pph.log(log.out, snakemake_format(script), step="qualimap_rnaseq", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
rule qualimap_bamqc:
input:
bam = pph.file_path(step="star", extension="bam")
output:
outdir = directory(pph.file_path(step="qualimap_bamqc", extension="results")),
done = touch(pph.file_path(step="qualimap_bamqc", extension="done"))
log:
out = pph.file_path(step="qualimap_bamqc", extension="output.log", log=True)
resources:
mem_mb=32000,
h_rt="24:00:00"
run:
protocol = {"unstranded":"non-strand-specific", "forward":"strand-specific-forward", "reverse":"strand-specific-reverse"}[config["sample_info"][wildcards.sample]["stranded"]]
script = textwrap.dedent(r"""
#----- prepare
set -eux
#----- set tmpdir
export TMPDIR=$(mktemp -d)
trap "rm -rf $TMPDIR" EXIT
export JAVA_OPTS="-Djava.io.tmpdir=$TMPDIR"
#----- rna-seqc
qualimap --java-mem-size={resources.mem_mb}M bamqc -bam {input.bam} -outdir {output.outdir} -c -ip -p {protocol}
find {output.outdir} -name "*.txt" -exec sh -c 'mv "{{}}" $(dirname "{{}}")/{wildcards.sample}_$(basename "{{}}")' \;
""")
script_file = pph.log(log.out, snakemake_format(script), step="qualimap_bamqc", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
##-------------------- rna-seqc -----------------------------------------------------------------------------
rule collapse_annotation:
""" run a script from https://github.com/broadinstitute/gtex-pipeline to prepare GTF for RNA-SeQC """
input:
gtf = config["organism"]["files"]["gtf"]
output:
pph.file_path(step="collapse_annotation", extension="genes.gtf")
log:
out = pph.file_path(step="collapse_annotation", extension="output.log", log=True)
resources:
mem_mb=32000,
h_rt="24:00:00"
run:
script = textwrap.dedent(r"""
#----- prepare
set -eux
#----- collapse annotation
{SCRIPTDIR}/collapse_annotation.py {input.gtf} {output}
""")
script_file = pph.log(log.out, snakemake_format(script), step="collapse_annotation", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
rule rna_seqc:
input:
bam = pph.file_path(step="star", extension="bam"),
gtf = pph.file_path(step="collapse_annotation", extension="genes.gtf", fix="all")
output:
touch(pph.file_path(step="rna_seqc", extension="done"))
log:
out = pph.file_path(step="rna_seqc", extension="output.log", log=True)
resources:
mem_mb=32000,
h_rt="24:00:00"
params:
options = config["rule_options"]["rna_seqc"]["cmd_opt"]
run:
protocol = {"unstranded":"", "forward":"--stranded=FR", "reverse":"--stranded=RF"}[config["sample_info"][wildcards.sample]["stranded"]]
paired = "" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else "--unpaired"
script = textwrap.dedent(r"""
#----- prepare
set -eux
rnaseqc --version
#----- rna-seqc
rnaseqc {input.gtf} {input.bam} --coverage $(dirname {output}) {paired} {protocol} {params.options}
""")
script_file = pph.log(log.out, snakemake_format(script), step="rna_seqc", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
##-------------------- qc -----------------------------------------------------------------------------------
# deprecated
#TODO: keep script? rename, several steps, hard coded star report file path
rule qc:
input:
genome = config["organism"]["files"]["genome"],
gtf = config["organism"]["files"]["seqc_gtf"],
bam = pph.file_path(step="star", extension="bam"),
fastqc = pph.file_path(step="fastqc", extension="zip")
output:
touch(pph.file_path(step="qc", extension="done"))
log:
out = pph.file_path(step="qc", extension="output.log", log=True)
resources:
mem_mb=4000,
h_rt="4:00:00"
run:
paired = '' if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else '-e'
script = textwrap.dedent(r"""
#----- prepare
set -eux
#----- qc
if [ ! -f {input.genome}.fai ] ; then exit 1; fi
{SCRIPTDIR}/run_my_qc.sh {paired} -l $(dirname {input.bam})/../report/Log.final.out -f $(dirname {input.fastqc}) -b {input.bam} -g {input.gtf} -r {input.genome} -o $( echo $(dirname {output}) | sed 's:/*$::')
if [ ! -f $(dirname {output})/RNA-SeQC/metrics.tsv ] ; then exit 1; fi
""")
script_file = pph.log(log.out, snakemake_format(script), step="qc", extension="sh", **wildcards)
shell("bash '{script_file}' &>> '{log.out}'")
##-------------------- multiQC ------------------------------------------------------------------------------
rule multiqc:
input:
get_inputs_all()
output:
pph.file_path(step="multiqc", extension="qc_report.html")
log:
out = pph.file_path(step="multiqc", extension="output.log", log=True),
multiqc_config = pph.file_path(step="multiqc", extension="multiqc_conf.yaml", log=True)
resources:
mem_mb=4000,
h_rt="4:00:00"
run:
# compile multiqc config
multiqc_dict = config["report"]["multiqc"]