Description Usage Arguments Value References Examples
Compute the significance p-value for SKAT-O based on LRT. The computational algorithm is based on a new approach described in detail at Wu et. al (2015).
1 |
obj |
a fitted null binomial model using KAT.null() |
G |
genotype matrix, sample in rows, variant in columns |
W.beta |
Beta parameters for variant weights |
rho |
weights for burden test |
SKATOL p-value
Lee, S., Wu, M. C., and Lin, X. (2012) Optimal tests for rare variant effects in sequencing association studies. Biostatistics, 13, 762-775.
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., Pankow,J.S., Guan,W. (2015) Sequence kernel association analysis of rare variant set based on the marginal regression model for binary traits. Genetic Epidemiology, 39(6), 399-405.
Wu,B., Guan,W., 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.
1 2 3 4 5 6 7 8 | library(CompQuadForm)
D = rbinom(5000,1,0.5); X = matrix(rnorm(10000),5000,2)
G = matrix(rbinom(100000,2,0.01), 5000,10)
SKATL(KAT.null(D,X), G, c(1.5,25.5))
SKATOL(KAT.null(D,X), G, c(1.5,25.5))
## library(SKAT)
## SKAT(G, SKAT_Null_Model(D~X, out_type='D'), method='davies')$p.value
## SKAT(G, SKAT_Null_Model(D~X, out_type='D'), method='optimal.adj')$p.value
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