Snakemake based pipeline for ChIP-seq and ATAC-seq datasets processing from raw data QC and alignment to visualization and peak calling.
During peak calling steps chipseq-smk-pipeline automatically matches signal with control file by names proximity.
Input FASTQ files
Pipeline aligned FASTQ or gzipped FASTQ reads, defined in config.yaml.
Reads folder is a relative path in pipeline working directory and defined by fastq_dir property.
FASTQ reads extension is defined by fastq_ext property, e.g. could be fq, fq.gz, fastq, fastq.gz.
Input BAM files
Use start_with_bams=True config option to start with existing bam files.
Pipeline starts with BAM files in work_dir/bams folder.
| Path | Description |
|---|---|
config.yaml |
Default pipeline options |
trimmed |
Trimmed FASTQ file, if trim_reads option is True. |
bams |
BAMs with aligned reads, MAPQ >= 30 |
bw |
BAM coverage visualization using DeepTools |
macs2 |
MACS2 peaks |
sicer |
SICER peaks |
span |
SPAN peaks |
qc |
QC Reports |
multiqc |
MultiQC reports for different steps |
logs |
Shell commands logs |
The pipeline requires conda.
- If
condais not installed, follow the instructions at Conda website. - Navigate to repository directory.
Create a Conda environment for snakemake:
$ conda env create --file environment.yaml --name snakemakeActivate the newly created environment:
$ source activate snakemakeOn Ubuntu please ensure that gawk is installed:
$ sudo apt-get install gawkRun the pipeline to start with fastq reads:
$ snakemake -p -s <chipseq-smk-pipeline>/Snakefile \
all [--cores <cores>] --use-conda --directory <work_dir> \
--config fastq_dir=<fastq_dir> genome=<genome> --rerun-incompleteDefault pipeline doesn't launch peak callers.
Please add macs2=True, sicer=True, span=True to call peaks with MACS2, SICER or SPAN.
To launch MACS2 in --broad mode, use the following config:
$ snakemake -p -s <chipseq-smk-pipeline>/Snakefile \
all [--cores <cores>] --use-conda --directory <work_dir> \
--config fastq_dir=<fastq_dir> genome=<genome> \
macs2=True macs2_mode=broad macs2_params="--broad --broad-cutoff 0.1" macs2_suffix=broad0.1 \
--rerun-incompleteSee config.yaml for complete list of parameters. Use--config to override default options from config.yaml file.
Configure profile for qsub with Torque scheduler with name generic_qsub
$ mkdir -p ~/.config/snakemake
$ cd ~/.config/snakemake
$ cookiecutter https://github.com/iromeo/generic.gitExample of ATAC-Seq processing on qsub
$ snakemake -p -s <chipseq-smk-pipeline>/Snakefile \
all --use-conda --directory <work_dir> \
--profile generic_qsub --cluster-config qsub_config.yaml --jobs 150 \
--config fastq_dir=<fastq_dir> genome=<genome> \
macs2=True macs2_params="-q 0.05 -f BAMPE --nomodel --nolambda -B --call-summits" \
span=True span_params="--fragment 0" bowtie2_params="-X 2000 --dovetail" --rerun-incompleteP.S: Use --config to override default options from config.yaml file
Please download example fastq.gz files
from CD14_chr15_fastq folder.
These files are filtered on human hg19 chr15 to reduce size and make computations faster.
Launch chipseq-smk-pipeline:
$ snakemake -p -s <chipseq-smk-pipeline>/Snakefile \
all --use-conda --cores all --directory <work_dir> \
--config fastq_ext=fastq.gz fastq_dir=<work_dir> genome=hg19 macs2=True sicer=True span=True \
--rerun-incomplete- Learn more about Snakemake workflow management system
- Developed with SnakeCharm plugin for PyCharm IDE by JetBrains Research BioLabs
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