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.