Gayán et al. BMC Genomics 2010, 11:403 http://www.biomedcentral.com/1471-2164/11/403 C O R R E S P O N D E N C E Open Access C"oDrreospeonsderneceplication groups scoring reduce false positive rate in SNP interaction discovery?: Response" Javier Gayán, Antonio González-Pérez and Agustín Ruiz* Abstract A response to Toplak et al: Does replication groups scoring reduce false positive rate in SNP interaction discovery? BMC Genomics 2010, 11:58. Background: The genomewide evaluation of genetic epistasis is a computationally demanding task, and a current challenge in Genetics. HFCC (Hypothesis-Free Clinical Cloning) is one of the methods that have been suggested for genomewide epistasis analysis. In order to perform an exhaustive search of epistasis, HFCC has implemented several tools and data filters, such as the use of multiple replication groups, and direction of effect and control filters. A recent article has claimed that the use of multiple replication groups (as implemented in HFCC) does not reduce the false positive rate, and we hereby try to clarify these issues. Results/Discussion: HFCC uses, as an analysis strategy, the possibility of replicating findings in multiple replication groups, in order to select a liberal subset of preliminary results that are above a statistical criterion and consistent in direction of effect. We show that the use of replication groups and the direction filter reduces the false positive rate of a study, although at the expense of lowering the overall power of the study. A post-hoc analysis of these selected signals in the combined sample could then be performed to select the most promising results. Conclusion: Replication of results in independent samples is generally used in scientific studies to establish credibility in a finding. Nonetheless, the combined analysis of several datasets is known to be a preferable and more powerful strategy for the selection of top signals. HFCC is a flexible and complete analysis tool, and one of its analysis options combines these two strategies: A preliminary multiple replication group analysis to eliminate inconsistent false positive results, and a post-hoc combined-group analysis to select the top signals. Background Epistasis, the interaction among genetic loci, is a frequent phenomenon in nature [1]. However, the detection of epi- static effects in observational data has not been an easy task because of the lack of appropriate samples and meth- odologies [2,3]. Thanks to the recent collection of large genetic datasets, we are now at a position where the study of epistasis in humans is becoming possible. Nonetheless, the genomewide evaluation of genetic epistasis is a com- putationally and statistically demanding task, due to the large number of possible combinations of loci that can be formed. For example, for a genomewide analysis with * Correspondence: aruiz@neocodex.es 1 Neocodex, Avda. Charles Darwin 6, 41092 Sevilla, Spain Full list of author information is available at the end of the article 100,000 SNPs, there are 5 × 109 two-locus combinations, and 1.7 × 1014 three-locus combinations. For 1 million SNPs, there are 5 × 1011 two-locus and 1.7 × 1017 three- locus combinations. The exhaustive search for epistasis across this large data space is a challenge for today's genehunters. In this context, a variety of software has been released to tackle this issue ([4] for review). HFCC (Hypothesis-Free Clini- cal Cloning) [4] is one of these tools that have made pos- sible genomewide epistasis analysis. This software uses case-control samples to test for single-locus or multi- locus genetic association. Multi-locus combinations that are significantly associated with a trait are then subjected to a variety of post-hoc tests to determine the degree of non-additivity of the marker combination, that is, to sep- © 2010 Gayán et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.