Parameters | Workflows | Sequence Kernel Association Test (SKAT)

Sequence Kernel Association Test (SKAT)
Check this box to perform the Sequence Kernel Association Test (SKAT) defined by Wu et al. (2011)1.
In this test, the variance component for all SNPs (or collapsed rare variant loci) with the same value of the Annotation Analysis Group Variable is tested for using a score statistic that follows a linear combination of chi-square distributions.
Important: This method can be used with continuous and binary traits only.
The chi-square approximation given by Liu, Tang, and Zhang (2009)2 is used to calculate p-values for this test.
Note: Random effects are ignored for this test.
To Perform the SKAT Test:

Wu, M.C., S. Lee, et al. (2011). Rare-variant association testing for sequencing data with the sequence kernel association test. American Journal of Human Genetics 89:82-93.

Liu, H., Y. Tang, and H.H. Zhang. (2009). A new chi-square approximation to the distribution of non-negative definite quadratic forms in non-central normal variables. Computational Statistics and Data Analysis 53:853-856.