SKAT: Resampling_FWER – R documentation

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Resampling_FWER

Obtain significant SNP sets after controlling family wise error rate (FWER)

Description

Obtain significant SNP sets after controlling for family wise error rate (FWER) using resampled residuals. To use it, SKAT_Null_Model or SKAT_Null_Model_MomentAdjust should have n.Resampling > 0.

Usage

Resampling_FWER(obj,FWER=0.05)

	Resampling_FWER_1(P.value, P.value.Resampling, FWER=0.05)

Arguments

`obj`	object returned from SKAT.SSD.All or SKATBinary.SSD.All.
`P.value`	a vector of SKAT p-values. If 100 genes were tested, this vector should have 100 p-values.
`P.value.Resampling`	a matrix of p-values of the resampled residuals. Each row represents each gene/snp set, and each column represents resampling set. For example, if you have 100 genes, and conducted resampling 1000 times ( ex.n.Resampling=1000 in SKAT_Null_Model), then it should be a 100 x 1000 matrix.
`FWER`	a numeric value of FWER rate to control (default=0.05)

Value

`results`	If the returned object from SKAT.SSD.all (or SKATBinary.SSD.All) are used, it is a sub-table of significant snp sets of the result table in the obj. If you use P.value and P.value.Resampling, it is a vector of significant p-values. If there is no significant snp set, it is NULL.
`n`	a numeric value of the number of significant snp sets.
`ID`	a vector of indexes of significant snp sets.

Author(s)

Seunggeun Lee

SKAT

SNP-Set (Sequence) Kernel Association Test

v2.0.1

GPL (>= 2)

Authors

Seunggeun (Shawn) Lee and Zhangchen Zhao, with contributions from Larisa Miropolsky and Michael Wu

Initial release

2020-10-20