Anthony Marcketta

This study quantifies cancer risk and penetrance in CHEK2 heterozygotes using genomic data from two large biobanks, finding increased risks for several cancers and younger age of onset.

The paper introduces REMETA, a tool for efficiently performing meta-analysis of gene-based tests using summary statistics, demonstrating its application on UK Biobank data.

The paper identifies SLC39A5 as a gene whose loss-of-function variants are associated with reduced type II diabetes risk and improved liver function in metabolic disorders.

The paper introduces SBAT, a method for joint testing of rare variant burden scores, showing it is well calibrated and outperforms existing tests in some scenarios.

The paper compares the effectiveness of whole genome sequencing, whole exome sequencing with imputation, and array genotyping in detecting genetic associations across 100 complex traits in the UK Biobank, finding that WES+IMP provides similar signal yield to WGS with greater efficiency.

This paper presents the largest catalog of human protein-coding variation from 985,830 individuals, identifying rare variants and their functional implications for precision medicine.

The paper identifies a rare variant that lowers ACE2 expression and reduces COVID-19 risk, and develops a genetic risk score predicting severe disease.

This study identifies parent-of-origin specific genetic associations with clinical traits from EHR in a large population study, finding that PoO effects are often captured by standard models but remain underpowered to detect.

The paper introduces REGENIE, a fast whole genome regression method for quantitative and binary traits, showing computational efficiency and accuracy on UK Biobank data.

The paper performs exome-wide association studies in large cohorts to identify genetic variants linked to human age, finding new candidates and confirming known ones.

Exomes of 49,960 UK Biobank participants reveal 231,631 predicted loss-of-function variants (>10-fold more than imputed data); burden tests implicate PIEZO1, MEPE, and COL6A1 in disease traits.

This study identifies rare genetic variants associated with type 2 diabetes using exome sequencing of 20,791 cases and 24,440 controls, and provides a Bayesian framework to improve variant prioritization.

MAD-seq detects low-level mosaic chromosomal aneuploidy using a new sequencing assay and analysis method, revealing previously unrecognized aneuploidy in public datasets.