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conf Refactor command resource usage for bismark align and methXtract Feb 21, 2018
.gitignore Added test data to GitHub repository. Feb 16, 2018


Build Status Nextflow

This pipeline has moved

This pipeline has been moved to the new nf-core GitHub organisation. You can now find it here:

This repository will be archived to maintain the release version for future reproducability, to allow reruns.

If you have any questions, please get in touch:

// Phil Ewels, 2018-03-12


NGI-MethylSeq is a bioinformatics best-practice analysis pipeline used for Methylation (BS-Seq) data analysis at the National Genomics Infastructure at SciLifeLab Stockholm, Sweden.

The pipeline uses Nextflow, a bioinformatics workflow tool. It pre-processes raw data from FastQ inputs, aligns the reads and performs extensive quality-control on the results.

Choice of workflows

There are two separate workflows contained in this repository - one using Bismark and one using bwa-meth / MethylDackel. The Bismark pipeline is being actively developed and maintained, the bwa-meth workflow is not (currently). The Nextflow manifest specifies the Bismark pipeline as the default workflow, so the bwa-meth script will be ignored unless explicitly run.

Hardware requirements

This pipeline is primarily used with a SLURM cluster on the Swedish UPPMAX systems. However, the pipeline should be able to run on any system that Nextflow supports. We have done some limited testing using Docker and AWS, and the pipeline comes with some configuration for these systems. See the installation docs for more information.


The NGI-MethylSeq pipeline comes with documentation about the pipeline, found in the docs/ directory:

  1. Installation and configuration
  2. Running the pipeline
  3. Output and how to interpret the results

If you're interested in running the pipeline in the cloud, please read the docs about using our pipeline with Amazon Web Services on the NGI-RNAseq pipeline (the instructions should work with this pipeline as well).


These scripts were written for use at the National Genomics Infrastructure at SciLifeLab in Stockholm, Sweden. Written by Phil Ewels (@ewels) and Rickard Hammarén (@Hammarn).

SciLifeLab National Genomics Infrastructure