BWASP

BWASP provides a reproducible, scalable workflow for integrative analysis of whole-genome bisulfite sequencing (WGBS) data to detect and characterize CpG DNA methylation patterns in social insects such as the honeybee, addressing generally low genome-wide methylation levels.

Key Features:

• Reproducibility and Scalability: Implements a fully reproducible and scalable workflow that enforces consistent quality-control filters and analysis parameters across studies.
• Data Quality Control: Applies stringent quality-control filters to raw WGBS sequencing data to ensure accurate methylation calling given low methylation levels in insect genomes.
• Consistent Analysis Parameters: Uses uniform analysis parameters across datasets to enable fair comparisons and facilitate dataset integration.
• Integration Across Studies: Integrates multiple WGBS datasets to produce a combined view of experiments conducted on a single species.
• Statistical Modeling: Employs statistical models to interpret methylation patterns and to evaluate genetic determinants of site accessibility and physiological control mechanisms.

Scientific Applications:

• Re-analysis of WGBS datasets: Re-analyzed publicly available WGBS datasets comprising 70 samples and 147 replicates across four social insect species.
• Honeybee CpG methylome characterization: Determined that the CpG methylome in the honeybee (Apis mellifera) comprises approximately 1.5% of CpG sites, corresponding to an estimated ~300,000 methylation sites.

Methodology:

Applies stringent data quality-control filters to raw WGBS reads; uses uniform analysis parameters across datasets to enable comparability and integration; and employs statistical models to interpret methylation patterns and to explore genetic determinants of site accessibility and physiological control mechanisms.