BiocMAP

BiocMAP processes whole genome bisulfite sequencing (WGBS) data to quantify DNA methylation patterns for epigenetic studies such as cancer and psychiatric disorder research.

Key Features:

• GPU-Accelerated Alignment: Uses Arioc, a GPU-accelerated short-read aligner, to perform WGBS read alignment and reduce alignment runtime.
• Memory Efficiency: Employs an on-disk data representation strategy to minimize main memory requirements for large WGBS datasets.
• Bioconductor Compatibility: Produces Bioconductor-based objects in R for integration with R/Bioconductor methylation analysis tools.
• Two-Module Workflow: Separates processing into a GPU alignment module and a non-GPU module that handles downstream extraction and merging steps.
• Methylation Extraction and Merging: Extracts and merges DNA methylation proportions across all cells at specific genomic sites.
• Flexible Deployment: Implemented with Nextflow and containerizable via Docker or Singularity, and executable on environments using SLURM or SGE.

Scientific Applications:

• Epigenetic profiling: Enables genome-wide quantification of DNA methylation from WGBS data for studies of epigenetic modifications.
• Cancer research: Supports analysis of methylation patterns relevant to cancer biology.
• Psychiatric disorder research: Supports investigation of methylation changes associated with psychiatric disorders.

Methodology:

The workflow comprises two modules: a GPU-accelerated read alignment step using Arioc, and a non-GPU module that extracts and merges DNA methylation proportions across all cells at specific genomic sites.