The goal of the Statistical Genomics Laboratory (SGL) is to develop cutting-edge biostatistical methods for the analysis of high-dimensional omics data. Recent work has focused on the detection of gene-gene interactions in genome-wide association data. The SGL is directed by Dr. Jiang Gui.
Gui J, Tosteson TD, Borsuk M. Weighted multiple testing procedures for genomic studies. BioData Min. 2012 Jun 7;5(1):4.
Gui J, Moore JH, Kelsey KT, Marsit CJ, Karagas MR, Andrew AS. A novel survival multifactor dimensionality reduction method for detecting gene-gene interactions with application to bladder cancer prognosis. Hum Genet. 2010, in press. 2011 Jan;129(1):101-10.
Gui J, Andrew AS, Andrews P, Nelson HM, Kelsey KT, Karagas MR, Moore JH. A simple and computationally efficient sampling approach to covariate adjustment for multifactor dimensionality reduction analysis of epistasis. Hum Hered. 2010;70(3):219-25.