flexiMAP: a regression-based method for discovering differential alternative polyadenylation events in standard RNA-seq data

Motivation: We present flexible Modeling of Alternative PolyAdenylation (flexiMAP), a new beta-regression-based method implemented in R, for discovering differential alternative polyadenylation events in standard RNA-seq data. Results: We show, using both simulated and real data, that flexiMAP exhibits a good balance between specificity and sensitivity and compares favourably to existing methods, especially at low fold changes. In addition, the tests on simulated data reveal some hitherto unrecognized caveats of existing methods. Importantly, flexiMAP allows modeling of multiple known covariates that often confound the results of RNA-seq data analysis.

Automated summary

The study introduces a new beta-regression-based method flexiMAP for discovering differential alternative polyadenylation events in RNA-seq data. Results show that flexiMAP exhibits a good balance between specificity and sensitivity, and allows modeling of multiple confounding variables, improving the results of RNA-seq data analysis.