vizAPA: visualizing dynamics of alternative polyadenylation from bulk and single-cell data.

Motivation: Alternative polyadenylation (APA) is a widespread post-transcriptional regulatory mechanism across all eukaryotes. With the accumulation of genome-wide APA sites, especially those with single-cell resolution, it is imperative to develop easy-to-use visualization tools to guide APA analysis.

Results: We developed an R package called vizAPA for visualizing APA dynamics from bulk and single-cell data. vizAPA implements unified data structures for APA data and genome annotations. vizAPA also enables identification of genes with differential APA usage across biological samples and/or cell types. vizAPA provides four unique modules for extensively visualizing APA dynamics across biological samples and at the single-cell level. vizAPA could serve as a plugin in many routine APA analysis pipelines to augment studies for APA dynamics.

Availability And Implementation: https://github.com/BMILAB/vizAPA.