Eric C. Polley

Analysis of more than 400,000 women provides case-control evidence for BRCA1 and BRCA2 variant classification

The paper uses case-control data from over 400,000 women to classify BRCA1 and BRCA2 variants, finding high consistency with ClinVar annotations for 785 previously unclassified variants.

Association of Gene Variant Type and Location with Breast Cancer Risk in the General Population

This study evaluates breast cancer risks associated with pathogenic variant type and location in BRCA2 and other genes, finding differential risks based on variant position.

Mutation prevalence tables for hereditary cancer derived from multi-gene panel testing

The paper develops a tool to estimate mutation prevalence in hereditary cancer genes based on clinical and demographic factors using data from 150,000 multi-gene panel tests.

Prediction of the functional impact of missense variants in BRCA1 and BRCA2 with BRCA-ML

BRCA-ML is a machine learning model trained to predict the functional impact of missense variants in BRCA1 and BRCA2 genes, outperforming existing methods.