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Family-based association tests for sequence data, and comparisons with population-based association tests.

Iuliana Ionita-Laza1, Seunggeun Lee, Vladimir Makarov

  • 1Department of Biostatistics, Columbia University, New York, NY, USA.

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Summary

Sequence-based association tests for family and population designs are compared. Family designs offer robustness to population stratification, while population designs can be more powerful for continuous traits.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical Genetics

Background:

  • High-throughput sequencing enables large cohort studies for complex traits.
  • Sequence-based association tests are crucial for genetic discovery.
  • Family-based and population-based designs have distinct advantages and disadvantages.

Purpose of the Study:

  • To present a framework for sequence-based association tests applicable to family-based designs.
  • To compare the statistical power of family-based versus population-based designs.
  • To evaluate the robustness of these designs to population stratification.

Main Methods:

  • Developed a class of sequence-based association tests for family designs.
  • Modeled tests to correspond with existing population-based Burden and variance-component tests.
  • Performed power comparisons for dichotomous and continuous traits.
  • Assessed robustness to population stratification.

Main Results:

  • Family-based designs show similar power to population-based designs for dichotomous traits, but with higher sequencing costs.
  • Population-based designs can be substantially more powerful for continuous traits.
  • Family-based designs are robust to population stratification, unlike population-based designs.
  • Applied tests to an autism spectrum disorder exome-sequencing family study.

Conclusions:

  • The choice of design (family-based vs. population-based) impacts power and robustness depending on trait type.
  • Family-based designs offer a valuable alternative, especially when population stratification is a concern.
  • The developed methods are available in public software for broader application.