POWEREDBiSeq

POWEREDBiSeq estimates statistical power for detecting between-group differences in DNA methylation from bisulfite sequencing (BS) data by simulating study-specific sequencing and biological parameters.

Key Features:

• Power Estimation Framework: Employs a simulation framework to predict study-specific power for identifying differential DNA methylation, integrating read depth, sample size, and the magnitude of methylation difference.
• Data Filtering Guidance: Provides recommendations on data filtering thresholds, with emphasis on minimum read depth to optimize statistical power and reproducibility in epigenetic studies.
• User-Defined Parameters: Accepts user-specified read depth filtering criteria and minimum sample size per group to tailor simulations to specific experimental designs.

Scientific Applications:

• Epigenetic epidemiology: Simulates bisulfite sequencing scenarios to quantify how experimental setups affect power and to inform selection of sample size and read depth thresholds.

Methodology:

Leverages a large reduced representation bisulfite sequencing (RRBS) dataset to assess the distribution of read depth across methylation sites and the extent of missing data, and simulates various scenarios to evaluate how combinations of study-specific variables affect power.