ASET: an end-to-end pipeline for quantification and visualization of allele specific expression
Year: 2025
Type: article
Abstract: Allele-specific expression (ASE) analyses from RNA-Seq data provide quantitative insights into genomic imprinting and the genetic variants that affect 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 for reproducibility, scalability, and ease of use. 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 of ASE from RNA-Seq data.
Source: BMC Bioinformatics
Institutions: University of Michigan, Institute for Social Research
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,990
OpenAlex ID: W4415380123