ACVI-Med, an open source variant interpretation tool for medical genomics

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Authors: Moritz Stadler, Sabina Gansberger, Liliane Borik-Heil, Johannes Griss, Ichiro Okamoto, Wolfgang P. Weninger, Matthias Wielscher
Cited by: 1
References: 45

Abstract

BACKGROUND: The adoption of whole genome and exome sequencing (WGS/WES) is expanding rapidly, yet variant interpretation remains a critical bottleneck, limiting diagnostic yield and delaying precision care. We present ACVI-Med (Accelerated Candidate Variant Interpretation in Medicine), an open-source, on-premise platform for comprehensive analysis of genomic data. RESULTS: ACVI-Med integrates phenotype-aware filtering, ACMG-guided variant classification, and secondary findings detection into a unified, containerized system built for reproducibility and deployment across diverse institutional environments. Designed for accessibility, ACVI-Med enables users without extensive bioinformatics expertise to interpret variants from VCF (Variant Call Format) files through a flexible interface supporting phenotype-driven filtering, ACMG-guided variant classification, and integration of population, clinical, and predictive annotations. The software incorporates modules for secondary findings detection, aligned with ACMG Secondary Findings v3.2 recommendations, extending its utility beyond primary variant analysis. ACVI-Med’s customizable filtering logic, real-time access to curated knowledge bases, and interactive visualization tools support transparent and reproducible genomic interpretation. CONCLUSION: ACVI-Med is an open-source software for genomic variant interpretation. Unlike commercial solutions, ACVI-Med is cost-effective, containerized, and can be institutionally self-hosted, reducing barriers to adoption in research settings.

Fields of Study & Subjects

Genomics and Rare Diseases Biomedical Text Mining and Ontologies Machine Learning in Healthcare

Publication details

Journal / source
BMC Bioinformatics
Publisher
Springer Science and Business Media LLC
Volume
27
Issue
1
Publication date
4 March 2026
Language
EN