SKATh: Sequence kernel association test (SKAT) with linear kernel...
In baolinwu/mkatr: Miscellaneous variant-set association test methods

Description Usage Arguments Details Value References

Compute accurate SKAT (linear kernel) p-value based on marginal variant score statistics

1	SKATh(obj, G, W.beta = c(1, 25))

`obj`	a fitted null model using KAT.null() or KAT.cnull()
`G`	genotype matrix, sample in rows, variant in columns
`W.beta`	Beta parameters for variant weights

We compute the SKAT based on the variant test statistics (typically of much smaller dimension), which leads to much more efficient computations. Davies' method is used to compute the tail probability of 1-DF chi-square mixtures with more stringent convergence criteria (acc=1e-9,lim=1e6). When it fails, we then switch to the saddlepoint approximation.

more accurate SKAT p-value

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, 82-93.

Wu,B., Guan,W., and Pankow,J.S. (2016) On efficient and accurate calculation of significance p-values for sequence kernel association test of variant set. Annals of Human Genetics, 80(2), 123-135.

baolinwu/mkatr documentation built on May 14, 2019, 6:03 a.m.