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preprocessing_iCLIPseq.smk

Snakemake workflow for preprocessing iCLIP-seq data.

Note

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

Workflow

preprocessing_iCLIPseq.smk rulegraph

The rulegraph was created by snakevision.

  1. Quality control using fastp with the parameters specified in the config.yaml.
  2. Alignment using STAR with the parameter --outFilterMultimapNmax 1.
  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 bigWig files using deepTools bamCoverage with the parameter --binSize 1 --normalizeUsing CPM.
  6. Make summary statistics using MultiQC.

Usage

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snakemake -s /path/to/SnakeNgs/snakefile/preprocessing_iCLIPseq.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"]
star_index: /path/to/star_index
trim_front1: 9
max_len1: 35
length_required: 25
  • 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/star_index is the directory containing the STAR index.

  • trim_front1, max_len1, and length_required are the parameters for fastp.

Docker image used in the workflow