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GSM-pipeline: GENE-SWitCH project methylation analysis pipeline image

author Jani

image

Schematic of the gs-meth pipeline. In yellow the pre-existing nf-core pipeline, and the blue shows the extensions that have been added to the pipeline.

About this project

The GENE-SWitCH project has received funding from the European Union’s Horizon 2020 ( https://ec.europ a.eu/programmes/horizon2020/ ) research and innovation program under Grant Agreement No 817998. This repository reflects only the listed contributors views. Neither the European Commission nor its Agency REA are responsible for any use that may be made of the information it contains.

nf-core/methylseq

DOI GitHub Actions CI Status GitHub Actions Linting Status Nextflow

install with bioconda Docker Get help on Slack

nf-core/methylseq is a bioinformatics analysis pipeline used for Methylation (Bisulfite) sequencing data. It pre-processes raw data from FastQ inputs, aligns the reads and performs extensive quality-control on the results.

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It comes with docker containers making installation trivial and results highly reproducible.

Pipeline Summary

The pipeline allows you to choose between running either Bismark or bwa-meth / MethylDackel. Choose between workflows by using --aligner bismark (default, uses bowtie2 for alignment), --aligner bismark_hisat or --aligner bwameth.

Step Bismark workflow bwa-meth workflow
Generate Reference Genome Index (optional) Bismark bwa-meth
Raw data QC FastQC FastQC
Adapter sequence trimming Trim Galore! Trim Galore!
Align Reads Bismark bwa-meth
Deduplicate Alignments Bismark Picard MarkDuplicates
Extract methylation calls Bismark MethylDackel
Sample report Bismark -
Summary Report Bismark -
Alignment QC Qualimap Qualimap
Sample complexity Preseq Preseq
Project Report MultiQC MultiQC

Quick Start

  1. Install nextflow

  2. Install any of Docker, Singularity, Podman, Shifter or Charliecloud for full pipeline reproducibility (please only use Conda as a last resort; see docs)

  3. Download the pipeline and test it on a minimal dataset with a single command:

    nextflow run nf-core/methylseq -profile test,<docker/singularity/podman/shifter/charliecloud/conda/institute>

    Please check nf-core/configs to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use -profile <institute> in your command. This will enable either docker or singularity and set the appropriate execution settings for your local compute environment.

  4. Start running your own analysis!

    nextflow run nf-core/methylseq -profile <docker/singularity/podman/shifter/charliecloud/conda/institute> --input '*_R{1,2}.fastq.gz' --genome GRCh37

See usage docs for all of the available options when running the pipeline.

Documentation

The nf-core/methylseq pipeline comes with documentation about the pipeline: usage and output.

Credits

These scripts were originally written for use at the National Genomics Infrastructure at SciLifeLab in Stockholm, Sweden.

Contributions and Support

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

For further information or help, don't hesitate to get in touch on the Slack #methylseq channel (you can join with this invite).

Citations

If you use nf-core/methylseq for your analysis, please cite it using the following doi: 10.5281/zenodo.2555454

You can cite the nf-core publication as follows:

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.

In addition, references of tools and data used in this pipeline are as follows: