SCAPE-APA: a package for estimating alternative polyadenylation events from scRNA-seq data
Year: 2025
Type: article
Abstract: SCAPE was a package that was previously developed to estimate alternative polyadenylation events from single-cell RNA-seq (scRNA-seq) data. It was composed of ad-hoc python scripts and has speed issues when handling large scRNA-seq data. To suit the needs of analyzing large scRNA-seq datasets, we present SCAPE-APA, which is a reimplementation of SCAPE with substantial changes. We made the following updates to the package: (1) we binned similar reads together to accelerate the estimation; (2) we re-derived the mixture model to tailor it for binned reads; (3) we implemented the inference algorithm using Taichi language for acceleration; (4) we re-implemented the untranslated region (UTR) annotation extraction script using the professional package gffutils for better maintenance; (5) we wrote a script to detect spurious alternative polyadenylation sites generated due to junction reads, and (6) we created a formal Python package and uploaded it to the Python Package Index website (Pypi).
Source: Open Research Europe
Authors: Guangzhao Cheng, Tien Le, Ran Zhou, Lu Cheng
Language: English
Topic: RNA Research and Splicing
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $841
Funder: Horizon 2020 Framework Programme
Award: G3672584302
OpenAlex ID: W4408225541