pleiotropyGENE: pleiotropyGENE

In SharonLutz/pleiotropy: This Package Tests For Pleiotropy

pleiotropyGENE

Description

This function tests for pleiotropy using 2 different gene based approaches

Usage

pleiotropyGENE(X, Y, Ydist, Z = NULL, covariates = FALSE, nPerm = 1000)

Arguments

X	X is a matrix of rare and/or common variants in a region where the number of rows of the matrix equal the number of subjects and the number of columns equal the number of SNPs in the region.
Y	Y is a matrix of the traits of interest where the number of rows equal the number of subjects and the number of columns equal the number of traits.
Ydist	Ydist is a vector that specifies the distribution of the each trait. For example, for one normally distributed trait and the second binary trait, then Ydist<-c("C","D"). These choices are specified by the SKAT function.
Z	Z is a matrix of covariates where the number of rows equal the number of subjects and the number of columns equal the number of covariates.
covariates	If covariates=FALSE, then the models will not be adjusted for covariates. If covariates=TRUE, then the model will be adjusted for covariates.
nPerm	nPerm is the number of permutations. Default is 1,000.

Details

For gene based tests of pleiotropy, this function computes the p-values obtained from both the cut-off based permutation approach and the Hausdorff based permutation approach.

Value

cutoffPvalue is the p-value from the cut-off based permutation approach

hausdorffPvalue is the p-value from the Hausdorff based permutation approach

Warning

SKAT R package is needed to run this function. Make sure the SKAT package has been installed first.

Author(s)

Sharon Lutz

Examples

set.seed(1)
X1<-rbinom(1000,2,0.005)
X2<-rbinom(1000,2,0.005)
X3<-rbinom(1000,2,0.005)
X4<-rbinom(1000,2,0.005)
X5<-rbinom(1000,2,0.005)
X<-cbind(X1,X2,X3,X4,X5)
Z<-matrix(rnorm(1000),nrow=1000,ncol=1)
Y1<-rnorm(1000,0.45*(X1+X2+X3+X4+X5)+0.1*Z,1)
Y2<-rnorm(1000,0.45*(X1+X2+X3+X4+X5)+0.1*Z,1)
Y<-cbind(Y1,Y2)
Ydist<-c("C","C")

pleiotropyGENE(X,Y,Ydist) # NOT adjusting for covariates Z
pleiotropyGENE(X,Y,Ydist,Z,covariates=TRUE) # Adjusting for covariates Z

SharonLutz/pleiotropy documentation built on Jan. 4, 2024, 7:51 a.m.