flexiMAP

flexiMAP models differential alternative polyadenylation (APA) in standard RNA-seq datasets by applying beta regression to relative polyadenylation site usage.

Key Features:

• Implementation: Implemented as an R package.
• Statistical method: Uses beta regression to model relative polyadenylation site usage.
• Differential APA detection: Identifies differential alternative polyadenylation events from standard RNA-seq data.
• Sensitivity and specificity: Demonstrates high specificity and sensitivity, including effective detection at low fold changes.
• Covariate modeling: Allows inclusion of multiple known covariates to account for confounding factors in the statistical model.
• Validation: Validated on both simulated and real datasets, showing improved performance relative to existing methods.
• Methodological insight: Revealed previously unrecognized limitations in existing methods for analyzing alternative polyadenylation.

Scientific Applications:

• Genomics: Analyze APA events from RNA-seq to investigate gene regulation at polyadenylation sites.
• Transcriptomics: Characterize changes in 3' end usage and alternative polyadenylation across conditions.
• Molecular biology: Study mechanisms of alternative polyadenylation affecting transcript isoforms.

Methodology:

flexiMAP applies beta regression to model relative polyadenylation site usage and supports inclusion of multiple known covariates in the statistical model.