A New Correction for Multiple Testing in Gene-Gene Interaction Studies

Area of Science:

• Genetics
• Statistical genetics
• Bioinformatics

Background:

• Gene-gene interaction studies require correcting for multiple testing.
• Linkage disequilibrium between markers complicates this correction.
• Permutation testing, the gold standard, is computationally intensive.

Purpose of the Study:

• To develop a computationally feasible method for correcting multiple testing in gene-gene interaction studies.
• To account for marker pair dependence caused by linkage disequilibrium.
• To provide a valid and efficient alternative to permutation testing.

Main Methods:

• Proposed a correction method based on the effective number of independent interaction tests.
• Calculated this number from the effective number of independent single-marker tests.
• Validated the method using simulated data and compared it to an alternative correction.

Main Results:

• The proposed method accurately estimated the effective number of independent tests.
• An alternative correction method significantly underestimated this number.
• Results aligned with estimates from a large-scale Genome-Wide Interaction Study.

Conclusions:

• The new correction method is valid, quick, and simple to apply.
• It is applicable across various marker panels and linkage disequilibrium patterns.
• This approach offers a practical solution for multiple testing correction in gene-gene interaction analyses.