SKATh: Sequence kernel association test (SKAT) with linear kernel...

Description Usage Arguments Details Value References

View source: R/skatR.R

Description

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

Usage

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

Arguments

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

Details

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.

Value

more accurate SKAT p-value

References

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. AHG, 80(2), 123-135.


baolinwu/SKATR documentation built on Nov. 24, 2017, 12:04 a.m.