{
  "abstract": "Motivation: Optimum contribution selection (OCS) maximizes genetic gain under a constraint on relatedness. Genomic relationship matrices are dense, so the quadratic term costs O(n^3) operations, and existing OCS software assumes pedigree sparsity. Results: We replace the relationship matrix by its leading eigenpairs, computed by randomized SVD, and solve OCS in factorized form. On Norway spruce population (n=5,525), ranks 10--30 kept the exact objective within 1% of the optimum at 110--330-fold speedups; on the QTL-MAS 2010 (n=3,226), ranks up to 100 were needed (24-211 fold). The required rank rises as the diversity constraint loosens. Gain alone is a misleading accuracy check, since coancestry exceeded the optimum by up to 28%, so we choose the rank on the exact objective, which can be checked without a dense solve. The speedup comes from computing only the leading eigenpairs. We extend the factorization to robust OCS (18-fold). Availability and implementation: Julia implementation, and examples are available at https://github.com/jonhar97/fastocs under the MIT license (archived at Zenodo, DOI 10.5281/zenodo.23214804).",
  "abstract_shown": true,
  "affiliations": [
    "Skogforsk Savar"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "J. Ahlinder"
    },
    {
      "name": "P. Waldmann"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/8yyeb4nynzxxt.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.07.757325",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.07.757325v1.full",
  "id": "8yyeb4nynzxxt",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.07.757325v1",
  "language": null,
  "licence": "CC-BY-NC",
  "licence_label": "CC BY-NC",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "bioinformatics"
    ],
    [
      "openalex",
      "1311|Genetic and phenotypic traits in livestock"
    ]
  ],
  "openalex": "W7221462548",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.07.757325v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-07",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/8yyeb4nynzxxt.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:27:09Z",
      "native_id": "10.64898/2026.10.07.757325",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.07.757325v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "Exploiting Low-Rank Structure in Genomic Relationship Matrices for Computationally Efficient Optimum Contribution Selection",
  "title_text": "Exploiting Low-Rank Structure in Genomic Relationship Matrices for Computationally Efficient Optimum Contribution Selection",
  "type": "preprint",
  "updated_at": "2026-10-30T12:27:09Z",
  "url": "https://research.draconitic.com/paper/8yyeb4nynzxxt",
  "venue": "bioRxiv",
  "versions": []
}