BiocMAP is a Bioconductor-friendly Methylation Analysis Pipeline. It consists of two nextflow-based "modules", which together take a set of FASTQ files, described in a samples.manifest file, and ultimately produce bsseq R objects containing methylation data and an R data frame of alignment and quality metrics.
The first BiocMAP module performs speedy alignment to a reference genome by Arioc, and requires GPU resources. Methylation extraction and remaining steps are performed in the second module, optionally on a different computing system where GPUs need not be available.
- GPU-accelerated alignment to a reference genome via Arioc
- Memory-efficient, HDF5-backed bsseq output objects immediately ready for analysis with Bioconductor/R packages of choice
- Automatic management of reference files, allowing simple configuration of GENCODE release and other settings, while alternatively supporting user-provided files
- Support for docker and singularity for flexible and reproducible installation
- Automatically merge samples split across multiple FASTQ files, using the
samples.manifestinput
The BiocMAP documentation website provides a complete description of features, installation, and many other details. To quickly get started, see our quick-start guide.
We provide shell scripts for out-of-the-box execution a SLURM or SGE-based computing cluster, or for execution on a Linux-based machine. Software dependencies can be installed via the shell script install_software.sh, which makes use of docker or Anaconda/Miniconda.
We hope BiocMAP will be a useful tool for your research. Please use the following bibtex information to cite this software. Thank you!
@article {Eagles2022.04.20.488947,
author = {Eagles, Nicholas J and Wilton, Richard and Jaffe, Andrew E. and Collado-Torres, Leonardo},
title = {BiocMAP: A Bioconductor-friendly, GPU-Accelerated Pipeline for Bisulfite-Sequencing Data},
year = {2022},
doi = {10.1101/2022.04.20.488947},
publisher = {Cold Spring Harbor Laboratory},
URL = {https://doi.org/10.1101/2022.04.20.488947},
journal = {bioRxiv}
}