Nicholas R. Wheeler

This study evaluates two sequence-to-function models for predicting regulatory variant effects across ancestries using blood eQTL data, finding better performance for high-confidence variants in African American populations.

This study performs a multi-ancestry transcriptome-wide association study (TWAS) to identify shared and population-specific genetic effects in Alzheimer's disease using RNA-seq and genotype data from multiple cohorts.

The paper provides a whole-genome sequencing dataset of 36,361 ADSP participants, including variant annotations, phenotypes, and a linkage disequilibrium panel for Alzheimer's Disease research.

The paper introduces GenomicsDB, a public knowledgebase for Alzheimer's disease genetic datasets and annotations, enabling data sharing and discovery through harmonized GWAS summary statistics and functional annotations.

This study identifies novel Alzheimer's disease risk loci by analyzing multi-ancestry GWAS data from diverse populations, highlighting the importance of including underrepresented groups in genetic research.

This study validates the association between mosaic loss of the Y chromosome and Alzheimer's Disease using prospective analyses and Mendelian Randomization across multiple cohorts.

This paper presents a strategy to jointly analyze 20,504 whole-exome sequencing samples from nine studies, generating high-quality variant calls and addressing batch effects from different capture kits.

POKEMON improves statistical power for detecting associations between rare missense variants and phenotypes by analyzing their spatial distribution on protein structures.