An R package for weighted region comethylation network analysis.
Overview
Comethyl builds upon the WGCNA package to identify and interpret modules of comethylated regions from whole-genome bisulfite sequencing data. Regions are defined from clusters of CpG sites or from genomic annotations, and then percent methylation values are used to identify comethylation modules. Interesting modules are identified and explored by comparing with sample traits and examining functional enrichments. Results are then visualized with high-quality, editable plots from ggplot2.
Installation
Option 1: pixi (Recommended)
pixi provides a fully reproducible, cross-platform environment with all dependencies pinned via a lock file.
# Install pixi (macOS / Linux / WSL2)
curl -fsSL https://pixi.sh/install.sh | bash
```bash
#set the pixi home and cache directory e.g for Mac below
export PIXI_HOME=/Users/$USER/.pixi
export PIXI_CACHE_DIR=/Users/$USER/.pixi
unset RATTLER_CACHE_DIR
unset XDG_CACHE_HOME
# Clone the repo and install the environment
git clone https://github.com/lasallegrp/comethyl.git
cd comethyl
pixi install
pixi run install-comethylSee the Get Started vignette for full installation instructions including Windows (WSL2) and Apple Silicon support.
Option 2: remotes
If you already have R ≥ 4.3 and Bioconductor set up:
install.packages(c("BiocManager", "remotes"))
# Install Bioconductor dependencies first if needed
BiocManager::install(c(
"bsseq",
"GenomicRanges",
"IRanges",
"annotatr",
"WGCNA",
"sva",
"rGREAT"
))
# Install comethyl from GitHub
remotes::install_github("lasallegrp/comethyl", dependencies = TRUE)
library(comethyl)Documentation
Complete documentation is available at https://lasallegrp.github.io/comethyl/.
Citation
Mordaunt CE, Mouat JS, Schmidt RJ, and LaSalle JM. (2022) Comethyl: a network-based methylome approach to investigate the multivariate nature of health and disease. Briefings in Bioinformatics bbab554. https://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbab554/6509051
