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

We present flexiMAP (flexible Modeling of Alternative PolyAdenylation), a new beta-regression-based method implemented in R, for discovering differential alternative polyadenylation events in standard RNA-seq data. 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 unrecognised caveats of existing methods. Importantly, flexiMAP allows modeling of multiple known covariates that often confound the results of RNA-seq data analysis. 

This repository contains scripts and all data required to reproduce data in the manuscript. _simulationData zip files contain extensive set of simulations which should serve as a useful resource for the development of similar methods in the future. Additionally, it contains 3’ sequencing data (PolyA-seq) and RNA-seq data from the Human Brain Reference and the Universal Human Reference MAQC samples (Bullard et al., 2010) that was used in the manuscript.