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Related Experiment Videos

Variance calculations for identity-by-descent estimation.

Matthew B McQueen1, Deborah Blacker, Nan M Laird

  • 1Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA. mmcqueen@hsph.harvard.edu

American Journal of Human Genetics
|May 11, 2006
PubMed
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Researchers developed a bootstrap method to calculate standard errors for estimated mean identity by descent (IBD), enhancing genetic linkage analysis for complex diseases. This improves effect-size estimates, confidence intervals, and meta-analyses in genetic studies.

Area of Science:

  • Genetics
  • Biostatistics
  • Complex Trait Analysis

Background:

  • Nonparametric linkage strategies commonly use identity by descent (IBD) estimation for complex trait mapping.
  • Existing methods primarily focus on statistical testing rather than effect size estimation.

Purpose of the Study:

  • To develop and validate a bootstrap procedure for estimating standard errors of mean IBD.
  • To enhance the utility of IBD estimates in genetic linkage studies.

Main Methods:

  • A bootstrap procedure was developed for linkage-scan datasets.
  • Standard errors were calculated for estimated mean IBD.

Main Results:

  • The bootstrap procedure provides broadly applicable standard errors for estimated mean IBD.

Related Experiment Videos

  • Demonstrated application in National Institute of Mental Health Human Genetics Initiative samples for bipolar disorder and Alzheimer disease.

    • Conclusions:

    • Estimated mean IBD with standard errors are valuable for assessing linkage-scan samples.
    • Enhances effect-size estimation, confidence intervals, meta-analyses, and discordant-sibling-pair evaluation in complex disease genetics.