The first phase of genome-wide association studies (GWAS) assessed the role of common
variation in human disease. Advances optimizing and economizing high-throughput …

Causal variants for rare genetic diseases are often rare in the general population. Rare
variants may also contribute to common complex traits and can have much larger per-allele …

Compared with linear mixed model-based genome-wide association (GWA) methods,
generalized linear mixed model (GLMM)-based methods have better statistical properties …

Insulin resistance (IR) is a well-established risk factor for metabolic disease. The ratio of
triglycerides to high-density lipoprotein cholesterol (TG: HDL-C) is a surrogate marker of IR …

Genome-wide association analysis of cohorts with thousands of phenotypes is
computationally expensive, particularly when accounting for sample relatedness or …

In genome-wide association studies (GWAS) for thousands of phenotypes in large biobanks,
most binary traits have substantially fewer cases than controls. Both of the widely used …

Rare copy-number variants (rCNVs) include deletions and duplications that occur
infrequently in the global human population and can confer substantial risk for disease. In …

Abstract Summary The Genomic Data Storage (GDS) format provides efficient storage and
retrieval of genotypes measured by microarrays and sequencing. We developed GENESIS …

Large-scale whole-genome sequencing studies have enabled the analysis of rare variants
(RVs) associated with complex phenotypes. Commonly used RV association tests have …

Set-based analysis that jointly tests the association of variants in a group has emerged as a
popular tool for analyzing rare and low-frequency variants in sequencing studies. The …