Polygenic risk scores have shown great promise in predicting complex disease risk and will
become more accurate as training sample sizes increase. The standard approach for …

We propose a method (GREML-LDMS) to estimate heritability for human complex traits in
unrelated individuals using whole-genome sequencing data. We demonstrate using …

Heritability analyses of genome-wide association study (GWAS) cohorts have yielded
important insights into complex disease architecture, and increasing sample sizes hold the …

Set tests are a powerful approach for genome-wide association testing between groups of
genetic variants and quantitative traits. We describe mtSet (http://github. com/PMBio/limix), a …

Rare genetic variants may be responsible for a significant amount of the uncharacterized
genetic risk underlying many diseases. An efficient approach to characterizing the disease …

We introduce a liability-threshold mixed linear model (LTMLM) association statistic for case-
control studies and show that it has a well-controlled false-positive rate and more power …

Large-scale genetic and genomic data are increasingly available and the major bottleneck
in their analysis is a lack of sufficiently scalable computational tools. To address this problem …

Genetic prediction based on either identity by state (IBS) sharing or pedigree information
has been investigated extensively with best linear unbiased prediction (BLUP) methods …

We surveyed 26 quantitative traits and disease outcomes to understand the proportion of
phenotypic variance explained by local ancestry in admixed African Americans. After …

Searching for genetic variants with unusual differentiation between subpopulations is an
established approach for identifying signals of natural selection. However, existing methods …