Many genetic variants influence complex traits by modulating gene expression, thus altering
the abundance of one or multiple proteins. Here we introduce a powerful strategy that …

Transcriptome-wide association studies integrate gene expression data with common risk
variation to identify gene-trait associations. By incorporating epigenome data to estimate the …

Deep sequence-based imputation can enhance the discovery power of genome-wide
association studies by assessing previously unexplored variation across the common-and …

Transcriptome-wide association analysis is a powerful approach to studying the genetic
architecture of complex traits. A key component of this approach is to build a model to impute …

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

Next-generation association studies can be empowered by sequence-based imputation and
by studying founder populations. Here we report∼ 9.5 million variants from whole-genome …

A key goal of biomedical research is to elucidate the complex network of gene interactions
underlying complex traits such as common human diseases. Here we detail a multistep …

Genome-wide association studies of gene expression traits and other cellular phenotypes
have successfully identified links between genetic variation and biological processes. The …

Common human diseases result from the interplay of many genes and environmental
factors. Therefore, a more integrative biology approach is needed to unravel the complexity …

Genome-wide association studies (GWAS) have identified many disease-associated
variants, yet mechanisms underlying these associations remain unclear. To understand …