• Publications
  • Influence
Rare-variant association testing for sequencing data with the sequence kernel association test.
The sequence kernel association test (SKAT) is proposed, a supervised, flexible, computationally efficient regression method to test for association between genetic variants (common and rare) in a region and a continuous or dichotomous trait while easily adjusting for covariates. Expand
Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies.
A unified approach for testing the association between rare variants and phenotypes in sequencing association studies is proposed and it is shown that the unified test corresponds to the optimal test in an extended family of SKAT tests, which is referred to as SKAT-O. Expand
Powerful SNP-set analysis for case-control genome-wide association studies.
SNPs are grouped together into SNP sets on the basis of proximity to genomic features such as genes or haplotype blocks, then testing the joint effect of each SNP set, showing that SNP-set testing can have improved power over standard individual-SNP analysis under a wide range of settings. Expand
Optimal tests for rare variant effects in sequencing association studies.
This paper proposes a class of tests that include burden tests and SKAT as special cases, and derives an optimal test within this class that maximizes power, and shows that this optimal test outperforms burden testsand SKAT in a wide range of scenarios. Expand
LKB1 modulates lung cancer differentiation and metastasis
LKB1 is established as a critical barrier to pulmonary tumorigenesis, controlling initiation, differentiation and metastasis in lung cancer, and expression profiling in human lung cancer cell lines and mouse lung tumours identified a variety of metastasis-promoting genes as targets of LKB1 repression. Expand
Sequence kernel association tests for the combined effect of rare and common variants.
Several sequence kernel association tests are introduced to evaluate the cumulative effect of rare and common variants and can achieve substantial increases in power compared with the most commonly used tests, including the burden and variance-component tests. Expand
Quality of life and satisfaction with outcome among prostate-cancer survivors.
Each prostate-cancer treatment was associated with a distinct pattern of change in quality-of-life domains related to urinary, sexual, bowel, and hormonal function, and these changes influenced satisfaction with treatment outcomes among patients and their spouses or partners. Expand
Semiparametric regression of multidimensional genetic pathway data: least-squares kernel machines and linear mixed models.
It is shown that the LSKM semiparametric regression can be formulated using a linear mixed model, and both the regression coefficients of the covariate effects and the L SKM estimator of the genetic pathway effect can be obtained using the best linear unbiased predictor in the correspondinglinear mixed model formulation. Expand
Inference in generalized additive mixed modelsby using smoothing splines
Generalized additive mixed models are proposed for overdispersed and correlated data, which arise frequently in studies involving clustered, hierarchical and spatial designs. This class of modelsExpand