Research Interest

My research interest is in developing novel statistical methods that integrate data collected via a wide variety of biological applications, including genomic, epigenomic and proteomic research. The underlying goal of my research is to improve existing statistical procedures to provide more powerful and informative statistical tests that in turn empower researchers in their quest to understand complex genetic interactions.

Ph.D. Research: Selecting Subsets of Traits for Quantitative Trait Loci Analysis

Identifying genetic determinants of complex traits (e.g., crop yield, disease resistance, etc.) is a fundamental challenge in genetics research. Historically, a powerful statistical procedure called quantitative trait loci (QTL) mapping has been used to investigate experimental populations for the purpose of finding genomic regions associated with phenotypic traits. When multiple traits are available, there are considerable benefits to analyzing subsets of biologically related traits in a multiple-trait QTL mapping framework. Unfortunately, prior knowledge of which traits are biologically related is often incomplete or missing altogether, which commonly results in each trait being analyzed independently. Single-trait QTL mapping procedures fail to utilize information from the correlation structure between traits. As a result, these procedures are less powerful than multi-trait QTL mapping and provide less informative hypothesis tests which make it difficult to investigate relationships between traits. The desire to utilize this valuable source of information is my primary motivation for developing efficient statistical procedures to select groups of potentially related traits that can be used in a multiple-trait QTL mapping framework.

Primary Research Interest