Benchmarking the AlphaGenome Variant Impact score against SpliceAI on post-release ClinVar classifications and experimental splicing assays
Open accessAbstract
The AlphaGenome Variant Impact (AVI) score ranks variants by predicted impact, and its developers report large gains over other genome-wide scores for intronic ClinVar variants. We tested AVI on two kinds of ground truth the developers did not use, under an analysis plan set before scoring: ClinVar classifications made after the developers' ClinVar release (87,666 rare single-nucleotide variants outside AVI's training chromosomes), and six splicing assays whose variants no predictor chose. In intronic variants at least 3 bases from an exon (449 pathogenic or likely pathogenic, 28,188 benign or likely benign), AVI reached an area under the receiver operating characteristic curve (AUROC) of 0.957. It did not differ detectably from SpliceAI (difference −0.005, 95% interval −0.017 to 0.006) or Pangolin (−0.006, −0.018 to 0.007); both intervals exclude differences larger than about 0.02. AVI had a higher AUROC than CADD (+0.071). In deep intronic variants it trailed SpliceAI (−0.070, −0.118 to −0.026). Under an adapted ClinGen calibration, AVI gave strong evidence to 52% of pathogenic variants on the pooled test set, but its levels did not hold in every region. It gave benign evidence to 24% of benign variants, against 90% for SpliceAI. On the assays, AVI ranked splice-altering variants below raw SpliceAI (pooled difference −0.089, −0.129 to −0.049) and did not differ from masked SpliceAI (+0.003). SpliceAI2, released during the study, led AVI on both kinds of ground truth. AVI did not outperform splicing predictors on AUROC and gave little benign evidence. AlphaGenome outputs are provided for research use, not for diagnostic decisions.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
The publisher hasn’t deposited this paper’s reference list.
Cited by
Sorted by citations
Babazade, A., Dolaş, Y., Duzenli, T., Vural, O., Furtana, C., & Ergun, M. A. (2026) · doi:10.64898/2026.10.21.760715
- Authors
- Cavus, O. A., & Kuskucu, A.
- Affiliations
- AIstanbul Research Group, Istanbul, Türkiye
- Department of Medical Genetics, Faculty of Medicine, Yeditepe University, Istanbul, Türkiye
- Corresponding author
- Cavus, Ozge A.
- Venue
- bioRxiv (Cold Spring Harbor Laboratory)
- Publisher
- openRxiv
- Published
- 2026-10-17
- OpenAlex
- W7222880099
- Cited by
- 1
- References
- 0
- Citations by year
- 2026: 1
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- SpliceAI, variant effect prediction, intronic variants, deep intronic variants, pangolins, CADD
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review