Single-cell data combined with phenotypes improves variant interpretation.
Journal:
BMC genomics
Published Date:
May 28, 2025
Abstract
BACKGROUND: Whole genome sequencing offers significant potential to improve the diagnosis and treatment of rare diseases by enabling the identification of thousands of rare, potentially pathogenic variants. Existing variant prioritisation tools can be complemented by approaches that incorporate phenotype specificity and provide contextual biological information, such as tissue or cell-type specificity. We hypothesised that integrating single-cell gene expression data into phenotype-specific models would improve the accuracy and interpretability of pathogenic variant prioritisation.
