Significance Levels in Genome-Wide Interaction Analysis (GWIA)

Authors

  • Tim Becker,

    Corresponding author
    1. Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn, Bonn, Germany
    2. German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
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  • Christine Herold,

    1. Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn, Bonn, Germany
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  • Christian Meesters,

    1. Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn, Bonn, Germany
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  • Manuel Mattheisen,

    1. Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn, Bonn, Germany
    2. Department of Genomics, Life & Brain Center, Institute of Human Genetics, University of Bonn, Bonn, Germany
    3. Institute of Human Genetics, University of Bonn, Bonn, Germany
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  • Max P. Baur

    1. Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn, Bonn, Germany
    2. German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
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Corresponding author: Priv.-Doz. Dr. Tim Becker, Institute for Medical Biometry, Informatics, and Epidemiology, University of Bonn, Sigmund-Freud-Str. 25, D-53105 Bonn, Germany. Tel: +49-228-287-14812; Fax: +49-228-287-15854; E-mail: Tim.Becker@ukb.uni-bonn.de

Summary

Interaction between genetic variants is hypothesized to be one of several putative explanations for the ‘case of missing heritability.’ Therefore, Genome-Wide Interaction Analysis (GWIA) has recently gained substantial interest. GWIA is computationally challenging and respective power type I error studies are particularly difficult. Therefore, an accepted significance level for GWIA studies does not currently exist. It has been shown that for a GWAS single-marker analysis with n SNPs a correction for multiple testing with 1/2 ·n is appropriate for populations of European ancestry. We speculated that for GWIA, correction by 1/4 ·m should be appropriate, where m=n· (n− 1)/2 is the number of SNP pairs. We tried to verify this hypothesis using the INTERSNP program that implements interaction analysis and genome-wide Monte-Carlo (MC) simulation. Using a type I error study based on Illumina® HumanHap 550 data, we were able to reproduce the published result for single-marker analysis. For GWIA using a test for allelic interaction, we show that correction with roughly 0.4 ·m is appropriate, a number that is somewhat larger than that of our hypothesis. In summary, it can be stated that for an Illumina®-type marker panel with 500,000 SNPs, an uncorrected P-value of 1.0 × 10−12 is needed to establish genome-wide significance at the 0.05 level.

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