ASET: An end-to-end pipeline for quantification and visualization of allele specific expression

Motivation Allele-specific expression (ASE) analyses from RNA-Seq data provide quantitative insights into imprinting and genetic variants affecting transcription. Robust ASE analysis requires the integration of multiple computational steps, including read alignment, read counting, data visualization, and statistical testing—this complexity creates challenges around reproducibility, scalability, and ease of use. Results Here, we present ASE Toolkit (ASET), an end-to-end pipeline that streamlines SNP-level ASE data generation, visualization, and testing for parent-of-origin (PofO) effect. ASET includes a modular pipeline built with Nextflow for ASE quantification from short-read transcriptome sequencing reads, an R library for data visualization, and a Julia script for PofO testing. ASET performs comprehensive read quality control, SNP-tolerant alignment to reference genomes, read counting with allele and strand resolution, annotation with genes and exons, and estimation of contamination. In sum, ASET provides a complete and easy-to-use solution for molecular and biomedical scientists to identify and interpret patterns in ASE from RNA-Seq data. Availability ASET is available at https://github.com/weishwu/ASET . The ASE data preparation section is implemented in Nextflow with DSL2 syntax. The data visualization functionality is provided as an R library, directly available from the ASET repository or from https://github.com/weishwu/ASEplot . The PofO testing algorithm is implemented in a Julia script. ASET and ASEplot are also accessible as docker containers from Docker Hub: and https://hub.docker.com/repository/docker/weishwu/aseplot. Contact weishwu@umich.edu