nf-core/methylarray
Process methylation data from Illumina arrays. Pre-processing, quality checks, confounder check and DMPs (differentially methylated positions) and DMRs (differentially methylated regions). Optionally estimates cell type composition and adjusts data for it.
Introduction
nf-core/methylarray is a bioinformatics pipeline that was designed for the analysis of methylation data generated from Illumina arrays. It offers an end-to-end solution that covers every stage of the analysis workflow, including: pre-processing, quality checks, removal of cross-reactive/SNP/gender-at-birth-dependent and confounding probes. Moreover, the pipeline also estimates and adjusts for cell composition. It also provides a way of identifying differentially methylated probes, regions and/or blocks. Pipeline consists of the following processes:
- Pre-processing:
- Uses minfi to read IDAT files, perform quality control, normalize data (via preprocessQuantile or preprocessFunnorm), and calculate methylation values.
- Removal of cross-reactive probes:
- Employs DNAmCrosshyb to identify and filter out probes that map ambiguously across the genome.
- Removal of SNP probes:
- Utilizes minfi functions to annotate and remove probes overlapping with known SNPs.
- Exclusion of sex chromosome probes:
- Uses EPIC array annotations to remove probes from the X and Y chromosomes, minimizing gender-related bias.
- Removal of confounding probes:
- Performs differential methylation analysis (using dmpFinder) to filter out probes associated with confounding factors like age.
- Cell composition adjustment:
- Uses ChAMP’s champ.refbase to correct for variations in cell type proportions, particularly in whole blood samples.
- Differential methylation analysis:
- Combines methods from ChAMP and minfi to identify differentially methylated probes between sample groups.
Usage
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.
Now, you can run the pipeline using:
nextflow run nf-core/methylarray \
-profile <docker/singularity/.../institute> \
--input samplesheet.csv \
--outdir <OUTDIR>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.
For more details and further functionality, please refer to the usage documentation and the parameter documentation.
Pipeline output
To see the results of an example test run with a full size dataset refer to the results tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the output documentation.
Credits
nf-core/methylarray was originally written by Adrian Janucik.
We thank the following people for their extensive assistance in the development of this pipeline:
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 #methylarray channel (you can join with this invite).
Citations
An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.
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.