Meta-analysis is pervasively used to combine multiple genome-wide association studies
(GWASs). Fine-mapping of meta-analysis studies is typically performed as in a single-cohort …

Fine-mapping is commonly used to identify putative causal variants at genome-wide
significant loci. Here we propose a Bayesian model for fine-mapping that has several …

Abstract Summary echolocatoR integrates a diverse suite of statistical and functional fine-
mapping tools to identify, test enrichment in, and visualize high-confidence causal …

Motivation: The goal of fine-mapping in genomic regions associated with complex diseases
and traits is to identify causal variants that point to molecular mechanisms behind the …

Advancing from statistical associations of complex traits with genetic markers to
understanding the functional genetic variants that influence traits is often a complex process …

Despite the great success of genome-wide association studies (GWAS) in identifying genetic
loci significantly associated with diseases, the vast majority of causal variants underlying …

The R package EasyStrata facilitates the evaluation and visualization of stratified genome-
wide association meta-analyses (GWAMAs) results. It provides (i) statistical methods to test …

Rigorous organization and quality control (QC) are necessary to facilitate successful
genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple …

Background Despite the recent success of genome-wide association studies in identifying
novel loci contributing effects to complex human traits, such as type 2 diabetes and obesity …

Standard statistical approaches for prioritization of variants for functional testing in fine-
mapping studies either use marginal association statistics or estimate posterior probabilities …