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preprocessing_ChIPseq_single.smk

Snakemake workflow for preprocessing single-end ChIP-seq/ATAC-seq data.

Note

Please make sure that you have Singularity and Snakemake installed on your system and cloned the SnakeNgs repository.

Workflow

preprocessing_ChIPseq_single.smk rulegraph

The rulegraph was created by snakevision.

  1. Quality control using fastp with the default parameters.
  2. Alignment using Bowtie2 with the parameter specified in the config.yaml.
  3. Convert the SAM file to BAM file and sort using samtools.
  4. Remove duplicates using Picard MarkDuplicates with the parameter --REMOVE_DUPLICATES true.
  5. Make fingerprint plots using deepTools plotFingerprint with the parameter --minMappingQuality 30 --skipZeros --numberOfSamples 50000 --binSize 10000.
  6. Make bigWig files using deepTools bamCoverage with the parameter --binSize 1 --normalizeUsing CPM.
  7. Make summary statistics using MultiQC.

Usage

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snakemake -s /path/to/SnakeNgs/snakefile/preprocessing_ChIPseq_single.smk \
--configfile /path/to/config.yaml \
--cores <int> \
--use-singularity \
--rerun-incomplete

config.yaml should contain the following information:

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workdir: path/to/output
samples: ["SRRXXXXXX", "SRRYYYYYY", "SRRZZZZZZ"]
bowtie2_index: path/to/bowtie2_index
bowtie2_args: ""
  • path/to/output should contain fastq directory with the following structure:
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output/
└── fastq
    ├── SRRXXXXXX.fastq.gz
    ├── SRRYYYYYY.fastq.gz
    └── SRRZZZZZZ.fastq.gz
  • path/to/bowtie2_index is the directory containing the Bowtie2 index.

  • bowtie2_args is the optional argument for Bowtie2 (e.g., --very-sensitive).

Please refer to the tutorial for more information.

Docker image used in the workflow