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

## TL;DR

ASET is a complete pipeline for analyzing allele-specific expression from RNA-Seq data, making it easier to study genetic variants and imprinting effects.

## Contribution

ASET introduces a modular, end-to-end pipeline for ASE analysis with integrated tools for quantification, visualization, and statistical testing.

## Key findings

- ASET includes a Nextflow pipeline for SNP-level ASE quantification and quality control.
- The pipeline integrates R and Julia tools for visualization and parent-of-origin effect testing.
- ASET enables contamination estimation and allele-specific read counting with strand resolution.

## 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.

The online version contains supplementary material available at 10.1186/s12859-025-06282-2.