{
  "abstract": "AlphaGenome Atlas, released in September 2026, provides functional predictions for nearly all possible human single-nucleotide variants using the AlphaGenome Variant Impact (AVI) score. However, empirical thresholds relating AVI quantile rank (AVI_QUANTILE) to clinical variant classifications have not been established. We derived AVI_QUANTILE thresholds distinguishing ClinVar pathogenic, likely pathogenic, uncertain, conflicting, likely benign, and benign SNVs using receiver operating characteristic analyses. Pathogenic/likely pathogenic variants were strongly enriched at the upper end of the AVI_QUANTILE distribution, yielding a Youden-optimal ClinVar-derived cutoff of 0.9938. Optimal cutoffs were generally consistent across several major molecular consequence classes, although lower thresholds were observed for selected noncoding categories. Similarly, most well-powered gene-disease groups showed cutoffs close to the global threshold, with modest gene-specific variation. Among 24,989 variants of uncertain significance, 11,357 (45.45%) exceeded the global cutoff, identifying a substantial subset with AlphaGenome-predicted functional effects comparable to those observed among pathogenic/likely pathogenic variants and potentially warranting further evaluation. In a steroid-dependent asthma fine-mapping analysis, AVI_QUANTILE showed little correspondence with SuSiE posterior inclusion probabilities, indicating that AlphaGenome functional predictions capture information distinct from statistical fine-mapping.",
  "abstract_shown": true,
  "affiliations": [
    "Children's Hospital of Philadelphia"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "name": "H.-Q. Qu"
    },
    {
      "affs": [
        0
      ],
      "name": "H. Hakonarson"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/17phbvnj2vec4.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.26.754650",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.26.754650v1.full",
  "id": "17phbvnj2vec4",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.26.754650v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "genomics"
    ],
    [
      "openalex",
      "1311|Genomics and Rare Diseases"
    ]
  ],
  "openalex": "W7215085451",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.26.754650v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-26",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/17phbvnj2vec4.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:25:44Z",
      "native_id": "10.64898/2026.09.26.754650",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.26.754650v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:genomics",
      "subfield": "genetics-genomics"
    }
  ],
  "title": "Applying AlphaGenome Variant Impact for SNV Prioritization",
  "title_text": "Applying AlphaGenome Variant Impact for SNV Prioritization",
  "type": "preprint",
  "updated_at": "2026-10-30T12:25:44Z",
  "url": "https://research.draconitic.com/paper/17phbvnj2vec4",
  "venue": "bioRxiv",
  "versions": []
}