AlphaVaR: an R framework for the statistical interpretation of AlphaGenome variant-effect predictions

Authors

Marhaba, K., Maj, C., Schumacher, J., Dasmeh, P.

Abstract

AlphaGenome (Google DeepMind) scores a DNA variant across thousands of functional tracks at single-base resolution, reporting both the magnitude of each predicted effect and its rarity against a genome-wide background. That volume is itself the obstacle to biological interpretation. Here we present AlphaVaR, an R package that gives AlphaGenome's output a typed structure together with the statistical methods and visualizations needed to interpret it. The output schema is identical for every variant, so the same tests apply throughout it. AlphaVaR provides localization tests with multiple-testing correction and effect sizes, a specificity index measuring how far an effect concentrates on a few elements of a chosen variable, and a transparent prioritization that ranks candidates across interpretable criteria and maps each to a target gene. Results feed a plot library, reproducible reports and a code-free Shiny application. Applied to rs1427407, the lead common variant for fetal-haemoglobin level, AlphaVaR recovers the established biology of the BCL11A erythroid enhancer. Availability and implementation: https://github.com/KarimMarhaba/AlphaVaR, released under the MIT licence, R [≥] 4.2, with documentation at https://karimmarhaba.github.io/AlphaVaR/. The released version is archived at Zenodo (doi:10.5281/zenodo.21939265); the AlphaGenome scores analysed here are archived as a separate dataset (doi:10.5281/zenodo.21920988), and the scripts that regenerate every figure and reported number are in the repository (Supplementary Section S5).

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 20 Aug 2026.

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