"Does replication groups scoring reduce false positive rate in SNP interaction discovery? Response".
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.


CONCLUSIONS
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.


CONCLUSIONS
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.
Gayán
Javier
J
Neocodex, Avda, Charles Darwin 6, 41092 Sevilla, Spain.
González-Pérez
Antonio
A
Ruiz
Agustín
A
D004843:Epistasis, Genetic; D005189:False Positive Reactions; D023281:Genomics; D020641:Polymorphism, Single Nucleotide; D015203:Reproducibility of Results; D012107:Research Design; D012984:Software