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Related Experiment Videos

A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each

Dale R Nyholt1

  • 1Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Brisbane, Queensland, Australia. daleN@qimr.edu.au

American Journal of Human Genetics
|March 5, 2004
PubMed
Summary

We present a straightforward method for multiple testing correction in genetic studies involving single-nucleotide polymorphisms (SNPs) that are in linkage disequilibrium (LD). This spectral decomposition approach offers a computationally efficient alternative to permutation tests.

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Area of Science:

  • Genetics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Multiple testing is a common challenge in genetic association studies.
  • Single-nucleotide polymorphisms (SNPs) are often in linkage disequilibrium (LD), meaning they are inherited together, complicating statistical analysis.
  • Existing methods for correcting multiple testing in the presence of LD can be computationally intensive.

Purpose of the Study:

  • To introduce a simple and computationally efficient method for correcting multiple testing of SNPs in linkage disequilibrium (LD).
  • To provide a user-friendly tool for implementing this correction method.
  • To facilitate the selection of informative SNPs within a genomic region.

Main Methods:

  • The study utilizes spectral decomposition (SpD) of matrices representing pairwise LD between SNPs.

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  • A user-friendly interface, SNPSpD, was developed for performing the correction.
  • The method's output includes eigenvalues, principal-component coefficients, and factor loadings after varimax rotation.
  • Main Results:

    • A simple correction for multiple testing of SNPs in LD was developed.
    • The spectral decomposition (SpD) method is computationally less intensive than permutation tests.
    • The SNPSpD tool provides additional outputs for selecting informative SNPs.

    Conclusions:

    • The described spectral decomposition method offers a practical and efficient solution for multiple testing correction in the context of SNP LD.
    • The SNPSpD tool is a valuable resource for genetic researchers.
    • The method aids in optimizing information extraction from genomic regions by enabling informed SNP selection.