Work

SCAPE-APA: a package for estimating alternative polyadenylation events from scRNA-seq data

Year: 2024

Type: article

Abstract: Summary SCAPE is a package we previously developed to estimate alternative polyadenylation events from single cell RNA-seq (scRNA-seq) data, which is 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 re-implementation 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 made a formal python package and uploaded it to the Python Package Index website (Pypi). Availability and Implementation Scape-apa is freely available at https://github.com/chengl7-lab/scape and can be easily installed using pip. Contact [email protected]

Source: Open Research Europe

DOI: 10.12688/openreseurope.18673.1

Authors: Guangzhao Cheng, Tien Le, Ran Zhou, Lu Cheng

Institutions: Aalto University, Sichuan University, West China Hospital of Sichuan University, State Key Laboratory of Biotherapy

Language: English

Topic: RNA Research and Splicing

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $841

Funder: Horizon 2020 Framework Programme