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Data-driven insights to inform splice-altering variant assessment.

Patricia J Sullivan1, Julian M W Quinn2, Pamela Ajuyah3

  • 1Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Sydney, NSW, Australia; School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Sydney, NSW, Australia; University of New South Wales Centre for Childhood Cancer Research, UNSW Sydney, Sydney, NSW, Australia.

American Journal of Human Genetics
|March 8, 2025
PubMed
Summary

This study introduces data-driven heuristics to interpret human splice-altering variants (SAVs), improving the understanding of genetic variants affecting mRNA splicing. These evidence-based tools enhance variant evaluation beyond traditional binary predictions.

Keywords:
RNA splicingcancer genomicsclinical genomicsgenomicsmedical genomicsnext-generation sequencingpersonalized medicinesplice-altering variantsvariant classificationwhole-genome sequencing

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