SKAT is a R package for performing

(1) association tests between a set of common and rare SNPs and continuous and dichotomous (case-control) phenotypes using kernel machine methods for data from GWAS and genome-wide sequencing association studies

(2) sample size and power calculatons for sequencing association studies.

References:

• Lee, S., Wu, M.C. and Lin, X. (2012). Optimal tests for rare variant effects in sequencing association studies. Biostatistics, in press. Supplementary Mat erials.

• Wu, M. C., Lee, S., Cai, T., Li, Y., Boehnke, M. and Lin, X (2011) Rare Variant Association Testing for Sequencing Data Using the Sequence Kernel Association Test (SKAT). American Journal of Human Genetics, , in press
• Wu, M. C., Kraft, P., Epstein, M. P.,Taylor, D., M., Chanock, S. J., Hunter, D., J., and Lin, X. (2010) Powerful SNP Set Analysis for Case-Control GenomeWide Association Studies. American Journal of Human Genetics, , 86, 929-942.

An R function for testing for differential expression of a gene set/pathway based on the sparse linear discriminant analysis approach. A SAS Macro for estimating and testing for the effect of a genetic pathway on a disease outcome using logistic kernel machine regression via logistic mixed models. A SAS Macro for doing semiparametric regression of multi-dimensional genetic pathway data, using least squares kernel machines and linear mixed models.

References:

• Wu, M.,C., Zhang, L., Wang, Z., Christiani, D. C., Lin, Sparse linear discriminant analysis for simultaneous gene set/pathway significance test and gene selection. , Bioinformatics, , 25,1145-1151.
• Liu, D., Ghosh, D. and Lin, X. (2008) Estimation and Testing for the Effect of a Genetic Pathway on a Disease Outcome Using Logistic Kernel Machine Regression via Logistic Mixed Models. BMC Bioinformatics, 9, 292.
• Liu, D., Lin, X. and Ghosh, D. (2007) Semiparametric Regression of Multi-Dimensional Genetic Pathway Data: Least Squares Kernel Machines and Linear Mixed Models. Biometrics, 63, 1079-1088.

A SAS Macro to fit smoothing splines mixed models, with documentation. A SAS Macro for calculating a cubic smoothing spline using PROC MIXED. A SAS Macro to fit generalized additive mixed models using smoothing splines.

References:

• Zhang D., Lin X., Raz J., and Sowers M. (1998). Semiparametric stochastic mixed models for longitudinal data, Journal of the American Statistical Association, 93, 710-719.
• Lin X. and Zhang D. (1999). Inference in generalized additive mixed models using smoothing splines, Journal of the Royal Statistical Society, Series B, 61, 381-400.
• Zhang D., Lin X. and Sowers M. (2000). Periodic semiparametric regression for longitudinal hormone data from multiple menstrual cycles. Biometrics, , 56, 31-39.