On Robust Association Testing for Quantitative Traits and Rare Variants.
With the advance of sequencing technologies, it has become a routine practice to test for association between a quantitative trait and a set of rare variants (RVs). While a number of RV association tests have been proposed, there is a dearth of studies on the robustness of RV association testing for nonnormal distributed traits, e.g., due to skewness, which is ubiquitous in cohort studies. By extensive simulations, we demonstrate that commonly used RV tests, including sequence kernel association test (SKAT) and optimal unified SKAT (SKAT-O), are not robust to heavy-tailed or right-skewed trait distributions with inflated type I error rates; in contrast, the adaptive sum of powered score (aSPU) test is much more robust. Here we further propose a robust version of the aSPU test, called aSPUr. We conduct extensive simulations to evaluate the power of the tests, finding that for a larger number of RVs, aSPU is often more powerful than SKAT and SKAT-O, owing to its high data-adaptivity. We also compare different tests by conducting association analysis of triglyceride levels using the NHLBI ESP whole-exome sequencing data. The QQ plots for SKAT and SKAT-O were severely inflated (λ = 1.89 and 1.78, respectively), while those for aSPU and aSPUr behaved normally. Due to its relatively high robustness to outliers and high power of the aSPU test, we recommend its use complementary to SKAT and SKAT-O. If there is evidence of inflated type I error rate from the aSPU test, we would recommend the use of the more robust, but less powerful, aSPUr test.
Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 pwei2@mdanderson.org weip@biostat.umn.edu.|Human Genetics Center, The University of Texas School of Public Health, Houston, Texas 77030.
Peng
P
Wei
Human Genetics Center, The University of Texas School of Public Health, Houston, Texas 77030.
Ying
Y
Cao
Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota 55455.
Yiwei
Y
Zhang
Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota 55455.
Zhiyuan
Z
Xu
Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota 55455.
Il-Youp
IY
Kwak
Human Genetics Center, The University of Texas School of Public Health, Houston, Texas 77030.|Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas 77030.
Eric
E
Boerwinkle
Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota 55455 pwei2@mdanderson.org weip@biostat.umn.edu.
Wei
W
Pan
D000465:Algorithms; D003198:Computer Simulation; D059472:Exome; D056726:Genetic Association Studies; D014644:Genetic Variation; D055106:Genome-Wide Association Study; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D008957:Models, Genetic; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D019655:Quantitative Trait, Heritable
SKAT; associate testing; next-generation sequencing; rare variants; robustness
Nat Commun. 2013;4:2872
24343240
Biometrics. 1999 Dec;55(4):997-1004
11315092
Nature. 2015 Oct 1;526(7571):82-90
26367797
Genet Epidemiol. 2013 Jul;37(5):409-18
23650101
Genetics. 2014 Aug;197(4):1081-95
24831820
N Engl J Med. 2014 Jul 3;371(1):22-31
24941081
Genet Epidemiol. 2009 Sep;33(6):497-507
19170135
Eur J Hum Genet. 2016 Aug;24(8):1188-94
26733287
Nat Genet. 2015 Jun;47(6):640-2
25915599
Am J Hum Genet. 2007 Feb;80(2):353-60
17236140
Genet Epidemiol. 2015 May;39(4):306-16
25847094
PLoS Genet. 2011 Dec;7(12):e1002382
22144906
Genet Epidemiol. 2011 May;35(4):211-6
21308765
Am J Hum Genet. 2015 Jul 2;97(1):86-98
26119817
Genetics. 2015 Aug;200(4):1089-104
26058849
Am J Hum Genet. 2011 Jul 15;89(1):82-93
21737059
Am J Hum Genet. 2014 Jul 3;95(1):5-23
24995866
Genet Epidemiol. 2011 Nov;35(7):606-19
21769936
Nat Rev Genet. 2010 Nov;11(11):773-85
20940738
Am J Hum Genet. 2012 Aug 10;91(2):224-37
22863193
Am J Hum Genet. 2008 Sep;83(3):311-21
18691683
Genet Epidemiol. 2014 Jan;38(1):51-9
24482837