scDAPA: detection and visualization of dynamic alternative polyadenylation from single cell RNA-seq data

Here, we present a package scDAPA for detecting and visualizing dynamic APA from scRNA-seq data. Taking bam/sam files and cell cluster labels as inputs, scDAPA detects APA dynamics using a histogram-based method and the Wilcoxon rank-sum test, and visualizes candidate genes with dynamic APA. Benchmarking results demonstrated that scDAPA can effectively identify genes with dynamic APA among different cell groups from scRNA-seq data. Availability and implementation: The scDAPA package is implemented in Shell and R, and is freely available at https://scdapa.sourceforge.io.

Supplementary data are available at Bioinformatics online.