The Statistical Genetics and Genetic Epidemiology Lab focuses on providing the framework and methodological tools needed to support a wide range of research efforts aimed at improving the understanding of the genetic basis and expression of disease.
Dr. Schaid and his statistical team work with world-class experts in disease and many areas of human genetics, ranging from molecular biology and cutting-edge genomic technologies to pharmacogenomics. They work on numerous software development projects and research projects.
Methodology and software development for quantitative analyses of genetic epidemiology
By developing innovative statistical methods and software that can be used widely by biomedical researchers, Dr. Schaid's lab facilitates the analyses of complex genetic mechanisms and their associations with disease.
Current projects include:
- Developing methods to evaluate the association of traits with genes using next-generation sequence data with new methods to improve power for rare variants. Methods have been developed for pedigree data and for unrelated subjects.
- Analyzing multiple traits at one time, seeking to understand whether a gene is associated simultaneously with multiple traits.
- Developing methods to aid fine-mapping of likely genetic causal variants, building models that include genomic annotation.
These types of analyses can aid decisions about which genetic variants should be targeted for laboratory functional studies.
Our lab generally aims to provide user-friendly software that implements our methods, and to make this software widely available to biomedical researchers, including related well-documented procedures and examples on their usage. Review our software.
The goals of vaccine research are to understand the immunogenetic basis of innate and acquired immunity in response to vaccines.
The projects within the vaccine research group cover a broad range of vaccines (for example, influenza, measles, mumps, rubella and smallpox), with rich laboratory measures of immune response, genomic data and patient characteristics. This provides unique opportunities for sophisticated statistical genetic analyses and systems biology analyses, aimed at the development of ever more efficacious vaccines.
Through collaborations with investigators at Columbia University, Dr. Schaid's lab has access to large-scale genomic data on pedigrees with Alzheimer's disease.
This rich resource provides opportunities to model the effects of multiple genes on the risk of Alzheimer's disease, taking advantage of pedigrees to inform the genetic models and clarify the impact for people at risk.
Breast cancer prediction methods
Using the many genetic markers discovered by genome-wide association studies, we are collaborating with a number of investigators to develop models that use genetic information to estimate the chance that a woman would have breast cancer in her remaining lifetime.