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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

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Published on: June 21, 2018

Multiple testing and power calculations in genetic association studies.

Hon-Cheong So, Pak C Sham

Cold Spring Harbor Protocols

|January 6, 2011

Summary

Modern genetic studies test many hypotheses, increasing the risk of false positives. This review covers key multiple-testing correction methods to ensure accurate genetic association findings.

Area of Science:

Genetics
Statistical Genetics
Bioinformatics

Background:

Genetic association studies increasingly analyze multiple single-nucleotide polymorphisms (SNPs) and genes.
High-throughput genotyping enables testing millions of SNPs against disease phenotypes.
Multiple phenotypes and statistical methods amplify the number of hypothesis tests performed.

Purpose of the Study:

To review principle methods for multiple-testing correction in genetic association studies.
To provide guidance on calculating statistical power in the context of multiple testing.
To enhance understanding of the strengths and weaknesses of various correction approaches.

Main Methods:

Review of established multiple-testing correction methodologies.

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Discussion of statistical power calculations relevant to hypothesis testing.

Comparative analysis of common correction techniques.

Main Results:

Identified the risk of Type I error inflation due to numerous hypothesis tests.
Highlighted that no single multiple-testing correction method is universally optimal.
Emphasized the need for informed application of correction methods based on study design.

Conclusions:

Understanding the principles, strengths, and weaknesses of multiple-testing correction methods is crucial for accurate genetic research.
Appropriate application of these methods mitigates the risk of false positive associations.
Guidance is provided for selecting and applying correction techniques to maintain statistical rigor.