Statistical Genetics Laboratory

The goal of the Statistical Genetics Laboratory (SGL) is to understand human health and disease through the development and application of statistical methods for identifying genetic risk factors. The SGL is interested in the genetic epidemiology of lung and colon cancer and the gene mapping of causal factors and modifier loci for rare syndromes including Lynch syndrome, Peutz-Jeghers syndrome and Li-Fraumeni syndrome. The SGL is also interested in the genetic epidemiology of select autoimmune conditions including rheumatoid arthritis, primary biliary cirrhosis, and alopecia areata. The SGL facilitates these studies through the collection and management of data from family studies and is interested in the design of clinical studies to identify predictors of cancer development and progression. The SGL is directed by Dr. Chris Amos.

Example publications: 

Ma J, Xiong M, You M, Lozano G, Amos CI. Genome-wide association tests of inversions with application to psoriasis. Hum Genet. 2014 Aug;133(8):967-74.
Xiao F, Ma J, Cai G, Fang S, Lee JE, Wei Q, Amos CI. Natural and orthogonal model for estimating gene-gene interactions applied to cutaneous melanoma. Hum Genet. 2014 May;133(5):559-74.
Xiao F, Ma J, Amos CI. A unified framework integrating parent-of-origin effects for association study. PLoS One. 2013 Aug 26;8(8):e72208.
Wu CC, Shete S, Jo EJ, Xu Y, Lu EY, Chen WV, Amos CI. Whole-genome detection of disease-associated deletions or excess homozygosity in a case-control study of rheumatoid arthritis. Hum Mol Genet. 2013 Mar 15;22(6):1249-61.