BAT
BAT processes bisulfite sequencing data to quantify DNA methylation and identify differentially methylated regions (DMRs).
Key Features:
- Read Alignment: Performs alignment of bisulfite-treated sequencing reads to reference genomes, mapping converted cytosine residues indicative of methylation status.
- Quality Control: Implements quality control measures to detect sequencing or alignment issues that could affect downstream methylation analyses.
- Extraction of Methylation Information: Extracts methylation calls from aligned reads to quantify methylation levels at specific genomic loci.
- Calling Differentially Methylated Regions (DMRs): Applies statistical methods to identify genomic regions with significant methylation differences between samples or conditions.
- Downstream Analyses: Integrates methylation data with gene expression, histone modification profiles, and transcription factor binding site annotations for functional interpretation.
Scientific Applications:
- Gene regulation and development: Facilitates analysis of how DNA methylation influences gene regulation and developmental processes.
- Disease and environmental studies: Supports investigation of methylation changes associated with disease progression and response to environmental factors.
- Integrative multi-omics analyses: Enables combined analysis of methylation with gene expression, histone modifications, and transcription factor binding to study genetic and epigenetic interplay.
Methodology:
Modular architecture implementing read alignment of bisulfite-treated reads, quality control, methylation extraction, DMR calling, and downstream integration, with modules optimized for performance on large bisulfite sequencing datasets.
Topics
Details
- License:
- MIT
- Tool Type:
- command-line tool, workflow
- Programming Languages:
- R, Shell, Perl
- Added:
- 8/17/2018
- Last Updated:
- 12/10/2018
Operations
Publications
Kretzmer H, Otto C, Hoffmann S. BAT: Bisulfite Analysis Toolkit. F1000Research. 2017;6:1490. doi:10.12688/f1000research.12302.1. PMID:28979767. PMCID:PMC5590080.
Funding: - Bundesministerium für Bildung und Forschung: ICGC-DataMining01KU1505-CandG, ICGCMMML-Seq01KU1002A-J
- Fifth Framework Programme: HEALTH-F5-2011-282510