Methodology article

A method for detecting epistasis in genome-wide studies using case-control multi-locus association analysis

Javier Gayán^{* 1,2} , Antonio González-Pérez^{* 1} , Fernando Bermudo¹ , María Eugenia Sáez¹ , Jose Luis Royo¹ , Antonio Quintas¹ , Jose Jorge Galan¹ , Francisco Jesús Morón¹ , Reposo Ramirez-Lorca¹ , Luis Miguel Real¹ and Agustín Ruiz¹

¹Neocodex, Avda. Charles Darwin 6, Acc. A, 41092 Sevilla, Spain

²Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK

author email corresponding author email* Contributed equally

BMC Genomics 2008, 9:360doi:10.1186/1471-2164-9-360

Published:	31 July 2008

Abstract

Background

The difficulty in elucidating the genetic basis of complex diseases roots in the many factors that can affect the development of a disease. Some of these genetic effects may interact in complex ways, proving undetectable by current single-locus methodology.

Results

We have developed an analysis tool called Hypothesis Free Clinical Cloning (HFCC) to search for genome-wide epistasis in a case-control design. HFCC combines a relatively fast computing algorithm for genome-wide epistasis detection, with the flexibility to test a variety of different epistatic models in multi-locus combinations. HFCC has good power to detect multi-locus interactions simulated under a variety of genetic models and noise conditions. Most importantly, HFCC can accomplish exhaustive genome-wide epistasis search with large datasets as demonstrated with a 400,000 SNP set typed on a cohort of Parkinson's disease patients and controls.

Conclusion

With the current availability of genetic studies with large numbers of individuals and genetic markers, HFCC can have a great impact in the identification of epistatic effects that escape the standard single-locus association analyses.