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Rare-variant association analysis: study designs and statistical tests.

Seunggeung Lee1, Gonçalo R Abecasis1, Michael Boehnke1

  • 1Department of Biostatistics, University of Michigan, Ann Arbor, MI 48105, USA.

American Journal of Human Genetics
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Summary
This summary is machine-generated.

Rare variants significantly contribute to complex traits and diseases, yet remain largely unexplained. This review details statistical methods and study designs for identifying trait- and disease-associated rare variants.

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Area of Science:

  • Genetics and Genomics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Common variants explain only a fraction of the genetic basis for complex traits and diseases.
  • Rare genetic variants are increasingly recognized for their potential to explain additional heritability and disease risk.
  • The identification of trait- and disease-associated rare variants is a growing area of research.

Purpose of the Study:

  • To provide a comprehensive overview of statistical considerations in rare-variant association studies.
  • To review study designs, statistical tests, and analytical pipelines for rare-variant association analyses.
  • To discuss challenges and future directions in the field of rare-variant genetics.

Main Methods:

  • Review of various study designs, including cost-effective sequencing and genotyping platforms.
  • Comparison of gene- or region-based association tests: burden tests, variance-component tests, and omnibus tests.
  • Discussion of essential analytical components: meta-analysis, population stratification adjustment, and genotype imputation.

Main Results:

  • Detailed comparison of different statistical tests based on their assumptions and performance.
  • Exploration of strategies for efficient study design and data analysis in rare-variant association studies.
  • Identification of key challenges, including sample size requirements and statistical power.

Conclusions:

  • Rare variants are crucial for understanding the genetic architecture of complex traits and diseases.
  • Appropriate statistical methods and study designs are essential for the successful identification of rare variant associations.
  • Further research is needed to refine analytical techniques and address inherent challenges in rare-variant studies.