Rivas Lab aims to uncover the mechanisms of disease and improve health and well-being globally. By combining methods development and
biological and biomedical datasets, we develop statistical models and computational tools for the analysis of population-scale studies.

Scientific Themes

Generating effective therapeutic hypotheses Genetics to find opportunities for modifying disease risk

Apr April 24 Tue 2018

Human Knockouts in UK Biobank

Medical relevance of protein-truncating variants across 337,205 individuals in the UK Biobank study

Apr April 14 Sat 2018

Statistical models for prioritizing targets from human genetic data

Bayesian model comparison for rare variant association studies of multiple phenotypes

Oct October 27 Fri 2017

PCSK9 LoF and Ischemic Stroke

Large-scale phenome-wide association study of PCSK9 loss-of-function variants demonstrates protection against ischemic stroke

Oct October 20 Fri 2017

Prioritizing candidate causal genes

Vulnerabilities of transcriptome-wide association studies

Generating effective therapeutic hypotheses

We’re mining large-scale human genetic, clinical outcomes, imaging, wearable sensors, and environmental data to generate effective therapeutic and preventative hypotheses for human diseases. Key disease areas of focus include: Crohn's disease, ulcerative colitis, chronic kidney disease, Alzheimer's disease, type 2 diabetes, coronary heart disease, and exploring additional diseases through electronic health records.