The vast majority of genome-wide association study (GWAS) risk loci fall in non-coding
regions of the genome. One possible hypothesis is that these GWAS risk loci alter the …

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 …

Recently, large scale genome‐wide association study (GWAS) meta‐analyses have boosted
the number of known signals for some traits into the tens and hundreds. Typically, however …

Large-scale whole-genome sequence data sets offer novel opportunities to identify genetic
variation underlying human traits. Here we apply genotype imputation based on whole …

Genome wide association studies (GWAS) provide a powerful approach for uncovering
disease-associated variants in human, but fine-mapping the causal variants remains a …

Functional annotations have been shown to improve both the discovery power and fine-
mapping accuracy in genome-wide association studies. However, the optimal strategy to …

Genome-wide association studies (GWAS) have revealed numerous genomic'hits'
associated with complex phenotypes. In most cases these hits, along with surrogate genetic …

Fine-mapping causal variants is challenging due to linkage disequilibrium and the lack of
interpretation of noncoding mutations. Existing fine-mapping methods do not scale well on …

In the last decade, genome-wide association studies have helped to advance our
understanding of the genetic architecture of many important traits, including diseases …

Several important and fundamental aspects of disease genetics models have yet to be
described. One such property is the relationship of disease association statistics at a marker …