gxgRC: gxgRC

Description Usage Arguments Details Value Author(s)

View source: R/gxgRC.R

Description

Tests for the effect of a SNP on the outcome in the presence of epistasis.

Usage

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gxgRC(n=1000,nSim=1000,MAF1=0.2,gamma0=0,gammaX1=0.2,
beta0=0,betaX1=0.1,betaX2=0.1,betaI=seq(from=0.1,to=0.5,by=0.1),varY=1,
alpha_level=0.05,plot.pdf=T,plot.name="gxgRC.pdf",SEED=1)

Arguments

n

is the sample size

nSim

is the number of simulations

MAF1

is the MAF for X1

gamma0

is the intercept for the association between the SNP X1 and the SNP X2 where logit(X2)=gamma0+gammaX1*X1

gammaX1

is the effect of SNP X1 on SNP X2 where logit(X2)=gamma0+gammaX1*X1

beta0

is the intercept for E[Y]=beta0+betaX1*X1+betaX2*X2+betaI*X1*X2

betaX1

is the association between X1 and Y for E[Y]=beta0+betaX1*X1+betaX2*X2+betaI*X1*X2

betaX2

is the association between X2 and Y for E[Y]=beta0+betaX1*X1+betaX2*X2+betaI*X1*X2

betaI

is the interaction between X1 and X2 on Y for E[Y]=beta0+betaX1*X1+betaX2*X2+betaI*X1*X2

varY

is the variance for Y

alpha_level

is the significance level, default 0.05

plot.pdf

equals T to output a plot, equals F to not output a plot

plot.name

is the name of the plot

SEED

sets the seed

Details

Tests for the effect of a SNP on the outcome in the presence of epistasis.

Value

a matrix of estimates and p-values

Author(s)

Sharon Lutz


SharonLutz/gxgRC documentation built on Dec. 21, 2020, 4:26 p.m.