Incorporating Ethnic and Gender Disparities in Genomic Studies of Disease

Most of the burden in our health care system comes from complex human diseases, whose onset and outcome are influenced by multiple genomic variants (e.g., cardiovascular disease, cancer, and diabetes). For the past decade, human geneticists have conducted genome-wide association studies, scanning for risk alleles associated with complex disease phenotypes. These studies have generally identified variants that confer relatively small increments in disease risk.


PEGASUS: the Precise, Efficient Gene Association Score Using SNPs

PEGASUS is a freely available software package, released by Nakka et al. (2016, Genetics), for combining SNP-level p-values into gene scores and conducting gene-level association tests with a phenotype of interest. PEGASUS computes gene scores of association analytically and produces gene scores with as much as 10 orders of magnitude higher numerical precision than competing methods.

Global Vision

The global vision of the Computational Biology Core is to provide workflows and software environments to foster reproducible research and portability across computing platforms. Workflows will be developed for projects of junior investigators with the aim of expanding to the overall Brown community, the affiliated hospitals, and ultimately the global research community

Computational Biology Core

The COBRE Computational Biology Core (CBC) integrates research across multiple research focused Centers. The CBC is a service focused Core Facility.

Collaboration between empirical and computational biologists

The underlying principle of this Center is that close collaboration between empirical and computational biologists with common challenges in the analysis of large data sets can accelerate the implementation of translational medicine.

Shipra Vaishnava uses microbiome profiling of germ-free mice models to better understand irritable bowel disease and explore interactions between intestinal bacteria and the immune system.