lin-lab / SKAT

Functions for kernel-regression-based association tests including Burden test, SKAT and SKAT-O. These methods aggregate individual SNP score statistics in a SNP set and efficiently compute SNP-set level p-values.

SKAT

SKAT is a SNP-set (e.g., a gene or a region) level test for association between a set of rare (or common) variants and dichotomous (case-control) or quantitative phenotypes using kernal machine methods for data from GWAS and genome-wide sequencing association studies. SKAT aggregates individual score test statistics of SNPs in a SNP set and efficiently computes SNP-set level p-values, e.g. a gene or a region level p-value, while adjusting for covariates, such as principal components, to account for population stratification. SKAT also allows for power/sample size calculations for designing for sequence association studies.

Availability

SKAT is available on CRAN. Please see the project page for more information.

User Group

Please join in the SKAT/MetaSKAT Google Group to ask/discuss/comment about SKAT/MetaSKAT.

References

• Ionita-Laza, I. * , Lee, S. * , Makarov, V., Buxbaum, J. Lin, X. (2013) Sequence kernel association tests for the combined effect of rare and common variants. American Journal of Human Genetics, 92, 841–853. doi:10.1016/j.ajhg.2013.04.015.
• Lee, Seunggeun, et al. (2012). Optimal Unified Approach for Rare-Variant Association Testing with Application to Small-Sample Case-Control Whole-Exome Sequencing Studies. American Journal of Human Genetics, 91.2, 224-237. doi:10.1016/j.ajhg.2012.06.007.
• Lee, S., Wu, M.C. and Lin, X. (2012). Optimal tests for rare variant effects in sequencing association studies. Biostatistics, 13.4, 762-775. doi:10.1093/biostatistics/kxs014. Supplementary Materials.
• 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, , 89.1, 82-93. doi:10.1016/j.ajhg.2011.05.029.
• 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. doi:10.1016/j.ajhg.2010.05.002.