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<p>Comprehensive interpretation of whole-genome sequencing data for phenotypes with complex genetic architecture requires integrating diverse variant classes, but most workflows remain focused on single-nucleotide changes and small indels. We present IMPACT, an open-source, phenotype-configurable pipeline that harmonizes preprocessing, applies variant-specific annotation, and consolidates single-nucleotide variants, indels, structural variants, and copy-number variants within an interactive R Shiny interface. Applied to the UK Biobank cohorts with deafness (<i>n</i> = 126) and epilepsy (<i>n</i> = 41), IMPACT prioritized 565 and 126 variants, respectively. Of these, 512 and 103 were non-incidental, phenotype-relevant candidates, which were subsequently reviewed using ACMG-aligned evidence and classified as pathogenic or candidate variants of uncertain significance where supported. All deafness participants and 87.8% of epilepsy participants carried at least one candidate variant, with configurations ranging from single high-impact variants to compound heterozygotes spanning variant classes. By coupling phenotype-aware filtering with cross-type visualization, IMPACT addresses critical gaps in genome interpretation and offers a scalable foundation for research-driven curation and precision medicine.</p><p></p>

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IMPACT: an open-source workflow for unified variant interpretation using phenotype-driven filtering

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月2日

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  • Nicholas A. Boehler,
  • Hai-Ying Mary Cheng

摘要

Comprehensive interpretation of whole-genome sequencing data for phenotypes with complex genetic architecture requires integrating diverse variant classes, but most workflows remain focused on single-nucleotide changes and small indels. We present IMPACT, an open-source, phenotype-configurable pipeline that harmonizes preprocessing, applies variant-specific annotation, and consolidates single-nucleotide variants, indels, structural variants, and copy-number variants within an interactive R Shiny interface. Applied to the UK Biobank cohorts with deafness (n = 126) and epilepsy (n = 41), IMPACT prioritized 565 and 126 variants, respectively. Of these, 512 and 103 were non-incidental, phenotype-relevant candidates, which were subsequently reviewed using ACMG-aligned evidence and classified as pathogenic or candidate variants of uncertain significance where supported. All deafness participants and 87.8% of epilepsy participants carried at least one candidate variant, with configurations ranging from single high-impact variants to compound heterozygotes spanning variant classes. By coupling phenotype-aware filtering with cross-type visualization, IMPACT addresses critical gaps in genome interpretation and offers a scalable foundation for research-driven curation and precision medicine.