Methylation (Bisulfite-Sequencing) Best Practice analysis pipeline, part of the nf-core community..

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.

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.

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

i. Install nextflow

ii. Install one of docker, singularity or conda

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

nextflow run nf-core/methylseq -profile test,<docker/singularity/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.

iv. Start running your own analysis!

nextflow run nf-core/methylseq -profile <docker/singularity/conda/institute> --reads '*_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, found in the docs/ directory:

1. Installation
2. Pipeline configuration
   • Local installation
   • Adding your own system config
   • Reference genomes
3. Running the pipeline
4. Output and how to interpret the results
5. Troubleshooting

Credits

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

• Main author:
  • Phil Ewels (@ewels)
• Contributors:
  • Rickard Hammarén (@Hammarn)
  • Alexander Peltzer (@apeltzer)
  • Patrick Hüther (@phue)

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 Slack (you can join with this invite).

Citation

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 pre-print as follows:

Ewels PA, Peltzer A, Fillinger S, Alneberg JA, Patel H, Wilm A, Garcia MU, Di Tommaso P, Nahnsen S. nf-core: Community curated bioinformatics pipelines. bioRxiv. 2019. p. 610741. doi: 10.1101/610741.