Related Experiment Video
Updated: Jun 8, 2026

Biomarker Identification for Gender Specificity of Alzheimer's Disease Based on the Glial Transcriptome Profiles
Published on: May 20, 2024
Significance levels in genome-wide interaction analysis (GWIA)
Tim Becker1, Christine Herold, Christian Meesters
1Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn, Germany. Tim.Becker@ukb.uni-bonn.de
Abstract:
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.
