SKATOh: Optimal sequence kernel association test (SKAT-O) using...

In baolinwu/SKATR: Revised implementation of sequence kernel association test for variant set

Description

Efficient SKAT-O p-value calculation using marginal variant score statistics directly

Usage

SKATOh(obj, G, W.beta = c(1, 25), rho = c(0, 0.1^2, 0.2^2, 0.3^2, 0.4^2,
  0.5^2, 0.5, 1))

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
rho	proportion weight assigned to burden test statistic

Details

Efficiently compute the SKAT-O significance p-value based on the variant test statistics (typically of much smaller dimension). The individual p-values of weighted SKAT and burden test are comptued more accurately using the SKATh. To obtain more accruate results, the one-dimensional integration is computed based on the convolution of survival function of 1-DF chi-square mixtures and 1-DF chi-square density function. For details, please see the Wu et. al (2016) reference.

Value

SKAT-O p-value

References

Lee, S., Wu, M. C., and Lin, X. (2012) Optimal tests for rare variant effects in sequencing association studies. Biostatistics, 13, 762-775.

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 May 29, 2019, 12:04 p.m.