Han Chen

The paper estimates genetic and environmental correlations between complex phenotypes across different racial/ethnic groups and sexes using data from the TOPMed program.

The paper reports whole-genome association analyses of sleep-disordered breathing traits in the NHLBI TOPMed program, identifying rare and common variant associations.

The paper introduces BinomiRare, a test for rare variant association with binary outcomes in mixed models, showing it controls type 1 error in simulations and applies it to study genetic variants in disease traits.

The paper identifies novel genetic loci associated with blood pressure that interact with sleep duration across multiple ancestries.

The paper identifies five novel gene-diet interaction effects on HbA1c using UK Biobank data, highlighting interactions with dietary patterns and traits.

GEM enables scalable gene-environment interaction analysis in large samples, identifying novel loci in a gene-sex interaction study.

This paper introduces RUTH, a new HWE test that accounts for population structure and genotype uncertainty, showing it reduces false positives compared to traditional methods.

The paper introduces MAGEE, a method for efficient gene-environment interaction testing in large biobank-scale sequencing studies, reducing computational burden and enabling analysis of hundreds of thousands of individuals.

The paper catalogs structural variants across 19,652 genomes and identifies their associations with proteomic measurements and disease phenotypes.

This paper introduces a unified method for detecting gene-environment interactions involving rare variants using a generalized linear mixed effect model, showing it maintains correct type I error and high power in simulations and replicates a known association.

The paper extends a mediation effect measure to high-dimensional omics data and applies it to the Framingham Heart Study, finding that gene expression explains over half of aging-related systolic blood pressure variation.

The paper identifies DNA methylation sites associated with daytime sleepiness in African Americans using epigenome-wide association analysis in the Multi-Ethnic Study of Atherosclerosis.

The paper introduces SCANG, a dynamic scan statistic method for detecting rare-variant association regions in WGS data without pre-specifying window sizes, showing improved performance over existing methods.

The paper identifies 49 novel blood lipid loci associated with gene-sleep interactions in 126,926 individuals across 5 ancestry groups, with gene-short-sleep interactions explaining 4.25% of triglyceride variance.

The paper introduces SMMAT, a variant-set mixed model association test for continuous and binary traits in large-scale WGS studies, showing it controls type I error rates and applies to population structured and related samples.