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

被引：54

作者：

Gayan, Javier ^{[1
,2
]}

Gonzalez-Perez, Antonio ^{[1
]}

Bermudo, Fernando ^{[1
]}

Saez, Maria Eugenia ^{[1
]}

Royo, Jose Luis ^{[1
]}

Quintas, Antonio ^{[1
]}

Galan, Jose Jorge ^{[1
]}

Moron, Francisco Jesus ^{[1
]}

Ramirez-Lorca, Reposo ^{[1
]}

Real, Luis Miguel ^{[1
]}

Ruiz, Agustin ^{[1
]}

机构：

[1] Neocodex, Seville 41092, Spain

[2] Univ Oxford, Wellcome Trust Ctr Human Genet, Oxford OX3 7BN, England

来源：

BMC GENOMICS | 2008年 / 9卷 / 1期

关键词：

D O I：

10.1186/1471-2164-9-360

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

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.

引用

页数：14

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