{
  "abstract": "Background\n\nDeep learning models can predict the functional impact of genetic variants. However, training and applying these sequence models to personalized genome sequences are severely constrained by the computational burden of storing and reading massive datasets.Results\n\nWe developed GenVarLoader, an accelerated dataloader that creates personalized genomic sequences and functional tracks on-the-fly to overcome these bottlenecks. GenVarLoader stores this personalized genomic data in formats specifically optimized for machine learning. Our tool reads variants up to 26,000 times faster than a pre-subset BCF, loads personalized data up to 130 times faster than tuned FASTA and pyBigWig pipelines, and reduces storage approximately 2,000-fold compared to existing alternatives.Conclusions\n\nBy eliminating severe data loading bottlenecks, GenVarLoader ensures efficient model training and inference. It provides a scalable solution for integrating biobank-scale personalized genomic data with deep learning applications.",
  "abstract_shown": true,
  "affiliations": [
    "Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, 92093, United States.",
    "Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, 92093, United States.",
    "Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, 92093, United States.",
    "Herbert Wertheim School of Public Health and Longevity Science, University of California, San Diego, La Jolla, CA, 92093, United States.",
    "Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, 92093, United States. gmcvicker@salk.edu.",
    "Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, 92093, United States. hkcarter@ucsd.edu.",
    "Department of Medicine, Division of Genomics and Precision Medicine, University of California, San Diego, La Jolla, CA, 92093, United States. hkcarter@ucsd.edu."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "David Laub"
    },
    {
      "affs": [
        1
      ],
      "name": "Aaron Ho"
    },
    {
      "affs": [
        2
      ],
      "name": "Loukik Raina"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Jeff Jaureguy"
    },
    {
      "affs": [
        0
      ],
      "name": "Adam Klie"
    },
    {
      "affs": [
        3
      ],
      "name": "Rany M Salem"
    },
    {
      "affs": [
        4
      ],
      "name": "Graham McVicker"
    },
    {
      "affs": [
        5,
        6
      ],
      "name": "Hannah Carter"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/fvepqv97vmd0p.bib",
  "cited_by": 2,
  "doi": "10.1186/s12864-026-13225-5",
  "fulltext_url": "https://europepmc.org/articles/PMC13682130",
  "id": "fvepqv97vmd0p",
  "issns": [
    "1471-2164"
  ],
  "landing_url": "https://europepmc.org/article/MED/42897450",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "QH426-470"
    ],
    [
      "lcc",
      "TP248.13-248.65"
    ],
    [
      "openalex",
      "1312|Genomics and Phylogenetic Studies"
    ]
  ],
  "openalex": "W4406532053",
  "pdf_url": "https://europepmc.org/articles/PMC13682130?pdf=render",
  "pmcid": "PMC13682130",
  "pmid": "42897450",
  "published": "2026-07-01",
  "publisher": "BMC",
  "ris": "https://research.draconitic.com/paper/fvepqv97vmd0p.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:41Z",
      "native_id": "MED:42897450",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42897450"
    },
    {
      "first_seen": "2026-10-30T13:45:38Z",
      "native_id": "c3b0e70f931c4de781d5cca59af469ec",
      "source": "doaj",
      "url": "https://doi.org/10.1186/s12864-026-13225-5"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Genomics and Phylogenetic Studies",
      "subfield": "molecular-biology"
    }
  ],
  "title": "GenVarLoader: an accelerated dataloader for applying deep learning to personalized genomics.",
  "title_text": "GenVarLoader: an accelerated dataloader for applying deep learning to personalized genomics.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:45:38Z",
  "url": "https://research.draconitic.com/paper/fvepqv97vmd0p",
  "venue": "BMC genomics",
  "versions": []
}