Open Access Open Badges Methodology article

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

Javier Gayán12, Antonio González-Pérez1, 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*

Author affiliations

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

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

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Citation and License

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

Published: 31 July 2008



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.


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.


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.