Abbye E. McEwen

The paper measures variant effects across the MAPK pathway in human cells, revealing how cell context influences variant function and identifying 14,412 previously unknown dominant negative variants.

MaveMD provides a clinical interface for MAVE data to classify variants of uncertain significance and improve genetic medicine outcomes.

Abundance scores for 8,891 TSC2 missense variants, plus mTOR pathway activity scores for 391, were calibrated to ACMG/AMP evidence. They putatively reclassify 212 of 276 clinical-cohort missense VUS.

The paper recalibrates BAP1 MAVE data for different disease phenotypes to enable accurate variant classification across related disorders.

This study explores patient experiences with genetic variant reclassifications, finding that re-contact practices significantly impact trust and perceived value of genetic testing.

The paper introduces VIS-seq, an image-based method to assess variant effects on cellular phenotypes, revealing multidimensional variant impacts across different diseases.

The paper develops a scalable workflow to reclassify variants of uncertain significance using experimental and predictive evidence, resolving 75% of VUS in 40 genes.

The paper uses saturation genome editing to evaluate BARD1 variants, resolving most variants of uncertain significance and confirming their role in tumor suppression.

This paper introduces ExCALIBR, a method to calibrate variant scores from functional assays, improving pathogenicity prediction and reducing variants of uncertain significance.

This study identifies barriers to using functional data in clinical variant interpretation and highlights the need for better access and standardized interpretation guidelines.

The paper surveys genetic professionals on functional evidence use in variant classification and identifies the need for expert recommendations and guidelines.

MaveDB v2 curates over three million variant effects from MAVE studies to facilitate analysis and dissemination of functional assay data.