My primary Center research projects involve design and analysis of expression microarray experiments to assess variation in transcript abundance within and between inbred mouse strains and tissues. Specifically, these experiments assess variation within and between inbred strains with distinct genetic backgrounds, and variation between tissues within strains. Part of this work involves investigation of relationships between patterns of transcript abundance variation and phenotypic patterns.

The Churchill lab and other labs have developed many methods for analyzing expression microarray data to enable robust statistical inferences from data with inherently complex covariance structure. In addition to understanding differences between methods and applying them appropriately, we look for modifications that will bypass some limitations of current methods. Our biological focus is bulk tissue samples from mammals and our methodological focus is variance estimation methods that combine information across multiple genes to provide more precise and effective test statistics.