Introduction

ew/qctrimalign is a bioinformatics pipeline optimized for processing low-input/picogram ChIP-seq (picoChIP-seq) experiments. This pipeline takes a sample sheet, FASTQ files, and a pre-built index as input. It performs quality control (QC), read filtering, and mapping. The final output is generated in BED format. Please note that this pipeline does not contain a deduplication step.

1. Merge resequenced FastQ files (cat)
2. QC raw reads (FastQC)
3. Trim and filter raw reads (Trim Galore!)
4. QC trimmed reads (FastQC)
5. Map trimmed reads either with (Bowtie) or (Bowtie2)
6. Sort BAM files (SAMtools)
7. Convert BAM files to BED format (BEDtools)
8. Present QC (MultiQC)

Usage

Note

If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

First, prepare a samplesheet with your input data that looks as follows:

samplesheet.csv:

sample,fastq_1,fastq_2
MII_REP1,MII_S1_L001_R1_001.fastq.gz,MII_S1_L001_R2_001.fastq.gz

Each row represents a fastq file (single-end) or a pair of fastq files (paired end). This samplesheet can be generated using get_samplesheet scripts from lerdruplab/hpc_scripts repository.

Now, you can run the pipeline using:

nextflow run ew/qctrimalign \
   -profile <docker/singularity/.../institute> \
   --input samplesheet.csv \
   --index /indexes/mm10/index/bowtie_canonical/ \
   --outdir <OUTDIR>

Warning

Please provide pipeline parameters via the CLI or Nextflow -params-file option. Custom config files including those provided by the -c Nextflow option can be used to provide any configuration except for parameters; see docs.

Credits

ew/qctrimalign was originally written by Erkut Ilaslan.

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

Citations

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT license.

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.