Original Paper

Backward Genotype-Trait Association (BGTA)-Based Dissection of Complex Traits in Case-Control Designs
Tian Zheng, Hui Wang, Shaw-Hwa Lo

Department of Statistics, Columbia University, New York, N.Y., USA

Address of Corresponding Author

Hum Hered 2006;62:196-212 (DOI: 10.1159/000096995)

  Key Words

• Multi-locus
• Genotype
• Association mapping
• Case-control design
• Complex traits
• Epistasis

  Abstract

Background: The studies of complex traits project new challenges to current methods that evaluate association between genotypes and a specific trait. Consideration of possible interactions among loci leads to overwhelming dimensions that cannot be handled using current statistical methods. Methods: In this article, we evaluate a multi-marker screening algorithm - the backward genotype-trait association (BGTA) algorithm for case-control designs, which uses unphased multi-locus genotypes. BGTA carries out a global investigation on a candidate marker set and automatically screens out markers carrying diminutive amounts of information regarding the trait in question. To address the 'too many possible genotypes, too few informative chromosomes' dilemma of a genomic-scale study that consists of hundreds to thousands of markers, we further investigate a BGTA-based marker selection procedure, in which the screening algorithm is repeated on a large number of random marker subsets. Results of these screenings are then aggregated into counts that the markers are retained by the BGTA algorithm. Markers with exceptional high counts of returns are selected for further analysis. Results and Conclusion: Evaluated using simulations under several disease models, the proposed methods prove to be more powerful in dealing with epistatic traits. We also demonstrate the proposed methods through an application to a study on the inflammatory bowel disease.

Copyright © 2006 S. Karger AG, Basel

  Author Contacts

Tian Zheng, PhD
Department of Statistics Columbia University
Room 1005, 1255 Amsterdam, MC 4690
New York, NY 10027 (USA)
Tel. +1 212 851 2134, Fax +1 212 851 2164, E-Mail tzheng@stat.columbia.edu

  Article Information

Received: May 4, 2006
Accepted after revision: September 9, 2006
Published online: November 15, 2006
Number of Print Pages : 17
Number of Figures : 3, Number of Tables : 2, Number of References : 40