SecondaryPhenotype: SecondaryPhenotype

In SharonLutz/SecondaryPhenotype: This Package Runs the Secondary Phenotype Genetic Analysis

Description

Use proportional odds logistic regression to test for the association between a SNP (i.e. x) and secondary phenotype (i.e. y) while accounting for the ascertainment bias due to case-control sampling (i.e. d).

Usage

SecondaryPhenotype(x, y, d, z = null, covariates = FALSE, sigLevel = 0.05)

Arguments

x	Let x be a vector of genotypes i.e. x=0,1,2
y	Let y be a vector of the phenotype
d	Let d be a vector of case control status
z	Let z be a matrix of covariates
sigLevel	Let sigLevel be the significance level, default to 0.05
covariates	covariates=FALSE (default) then the models will not be adjusted for covariates, covariates=TRUE then the model will be adjusted for covariates.

Value

whether or not the SNP is associated with the secondary phenotype Y given case-control sampling d

Warning

All covariates included in the model for adjustment must be entered as a matrix, not individually. For instance, variables age and gender should first be combined such that z=cbind(age,gender) and z is entered into the function instead of age and gender separately.

Author(s)

Sharon Lutz, Annie Thwing

References

Lutz SM, Hokanson JE, Lange C. (2014) An Alternative Hypothesis Testing Strategy for Secondary Phenotype Data in Case-Control Genetic Association Studies. Frontiers in Genetics. 5 (188).

Examples

set.seed(1)
n<-1000
d<-c(rep(0,n/2),rep(1,n/2))
x<-rbinom(n,2,0.3)
z<-rnorm(n)
y<-rnorm(n,0.1*d+0.2*x+0.1*z)

SecondaryPhenotype(x,y,d,z,covariates=TRUE)
SecondaryPhenotype(x,y,d)

SharonLutz/SecondaryPhenotype documentation built on May 31, 2019, 3:53 a.m.