Many methods have been developed to leverage expression quantitative trait loci (eQTL)
data to nominate candidate genes from genome-wide association studies. These methods …

A recent study by Cheung et al. demonstrates how to identify expression quantitative trait
loci (eQTLs) underlying gene expression phenotypes through a combination of genome …

Transcriptome-wide association studies (TWAS) integrate genome-wide association studies
(GWAS) and gene expression datasets to identify gene–trait associations. In this …

Most signals in genome-wide association studies (GWAS) of complex traits implicate
noncoding genetic variants with putative gene regulatory effects. However, currently …

There is increasing evidence that many risk loci found using genome-wide association
studies are molecular quantitative trait loci (QTLs). Here we introduce a new set of functional …

Transcriptome-wide association studies using predicted expression have identified
thousands of genes whose locally regulated expression is associated with complex traits …

Most signals in genome-wide association studies (GWAS) of complex traits point to
noncoding genetic variants with putative gene regulatory effects. However, currently …

Genome-wide association studies (GWAS) have identified hundreds of genetic variants
associated with complex traits and diseases. However, elucidating the causal genes …

Genetic association mapping produces statistical links between phenotypes and genomic
regions, but identifying causal variants remains difficult. Whole-genome sequencing (WGS) …

How to interpret the biological causes underlying the predisposing markers identified
through genome-wide association studies (GWAS) remains an open question. One direct …