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Avoiding false discoveries in association studies.

Chiara Sabatti1

  • 1Department of Human Genetics, UCLA School of Medicine, Los Angeles, CA, USA.

Methods in Molecular Biology (Clifton, N.J.)
|November 7, 2007
PubMed
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Controlling false discoveries in genetic association studies is crucial. This review covers statistical methods for hypothesis testing and multiple comparison correction, focusing on linkage and association mapping strategies.

Area of Science:

  • Genetics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Association studies aim to identify genetic variants linked to traits.
  • Controlling false discoveries is essential for reliable results in genetic association studies.
  • Random chance is a primary source of false discoveries, assuming adequate study design.

Purpose of the Study:

  • To review statistical frameworks for controlling false discoveries in association studies.
  • To examine current strategies in linkage analysis and their relation to association studies.
  • To document recent methodological advancements in association mapping.

Main Methods:

  • Review of statistical hypothesis testing.
  • Analysis of multiple comparison correction methods.

Related Experiment Videos

  • Comparison of linkage and association study methodologies.

    • Main Results:

    • False discoveries in association studies primarily arise from random chance.
    • Current strategies in linkage analysis are detailed.
    • Similarities and differences between linkage and association studies are explored.

    Conclusions:

    • Effective control of false discoveries relies on appropriate statistical methods.
    • Understanding the nuances between linkage and association studies is key.
    • Recent developments offer improved approaches to association mapping.