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On Robust Association Testing for Quantitative Traits and Rare Variants.

Peng Wei1,2, Ying Cao2, Yiwei Zhang3

  • 1Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 pwei2@mdanderson.org weip@biostat.umn.edu.

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|September 29, 2016
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Summary
This summary is machine-generated.

Commonly used rare variant (RV) association tests like SKAT and SKAT-O show inflated type I errors for non-normal traits. The adaptive sum of powered score (aSPU) test offers better robustness and power, with aSPUr providing enhanced protection against outliers.

Keywords:
SKATassociate testingnext-generation sequencingrare variantsrobustness

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Area of Science:

  • Genetics and Genomics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Rare variant (RV) association testing is crucial in genomics for identifying disease-related genetic variations.
  • Non-normal trait distributions, common in cohort studies, pose challenges for the robustness of existing RV association tests.
  • Existing methods like Sequence Kernel Association Test (SKAT) and Optimal Unified SKAT (SKAT-O) may exhibit inflated Type I error rates with skewed or heavy-tailed data.

Purpose of the Study:

  • To evaluate the robustness of commonly used rare variant association tests under non-normal trait distributions.
  • To introduce and assess a novel robust version of the adaptive sum of powered score (aSPU) test, termed aSPUr.
  • To compare the performance of aSPU and aSPUr against SKAT and SKAT-O using simulations and real-world genetic data.

Main Methods:

  • Extensive simulations were conducted to assess Type I error rates and statistical power of various RV association tests.
  • The adaptive sum of powered score (aSPU) test was modified to create a more robust version, aSPUr.
  • Association analysis was performed on triglyceride levels from the NHLBI ESP whole-exome sequencing data to compare test performance on real data.

Main Results:

  • SKAT and SKAT-O demonstrated inflated Type I error rates with non-normal trait distributions.
  • The aSPU test exhibited greater robustness and often higher power than SKAT and SKAT-O, especially with a larger number of rare variants.
  • QQ plots from real data analysis showed inflated results for SKAT and SKAT-O, while aSPU and aSPUr performed well, indicating normal behavior.

Conclusions:

  • The aSPU test is recommended as a robust and powerful alternative for rare variant association testing, particularly for non-normal traits.
  • The aSPUr test provides enhanced robustness against outliers, making it suitable when severe non-normality or outliers are suspected.
  • aSPU and aSPUr can serve as valuable complementary tools to SKAT and SKAT-O in genetic association studies.