survSNP (version 0.26)

survSNP-package: Power Calculations for SNP Studies with Censored Outcomes

Description

This package can be used to conduct asymptotic and empirical power and sample size calculations for Single-nucleotide Polymorphism (SNP) association studies with right censored time to event outcomes.

Author

Kouros Owzar, Zhiguo Li, Nancy Cox, Sin-Ho Jung and Chanhee Yi

Details

Package:	survSNP
Type:	Package
Version:	0.26
Date:	2023-01-20
License:	GPL-3
LazyLoad:	yes

The functions sim.snp.expsurv.power and survSNP.power.table can be used to conduct power and sample size calculations. The package vignette serves as a tutorial for using this package. The technical details are provided in the reference cited below. It is highly recommended that the vignette along with this are reviewed before using this package. Currently, this package only supports additive risk models.

References

Kouros Owzar, Zhiguo Li, Nancy Cox and Sin-Ho Jung. Power and Sample Size Calculations for SNP Association Studies with Censored Time-to-Event Outcomes. https://onlinelibrary.wiley.com/doi/full/10.1002/gepi.21645

Examples

# See vignette for examples including details on the example
# considered below

results<-sim.snp.expsurv.power(GHR=1.25, B=0, n=500, raf=0.1, erate=0.75, pilm=0.5, 
                               lm=1, model="additive", test="additive", alpha=0.05)
results[,c("n","erate","alpha","pow0")]


GHRs<-seq(1.05,1.5,by=0.05)
ns<-c(100,500,700)
rafs<-c(0.1,0.3,0.5)
erates<-c(0.5,0.7,0.9)
res<-survSNP.power.table(GHRs,ns,rafs,erates,pilm=0.5,lm=1,model="additive",
                         test="additive",alpha=0.05)

# Create key for illustration
KEY=paste("q=",levels(factor(res$raf)),sep="")
KEY<-list(lines=list(col=1:length(KEY),lty=1:length(KEY)),
          text=list(labels=paste("q=",levels(factor(res$raf)),sep="")),
          column=3)


# Illustrate Power
print(xyplot(pow0~GHR|factor(erate)*factor(n),group=factor(raf),
             data=res,type="l",lty=KEY$lines$lty,col=KEY$lines$col,
             key=KEY,
             xlab="Genotype Hazard Ratio",ylab="Power"))

# Illustrate Power (restricted to n=100)

print(xyplot(pow0~GHR|factor(erate),group=factor(raf),
             data=subset(res,n==ns[1]),
             type="l",lty=KEY$lines$lty,col=KEY$lines$col,
             key=KEY,
             xlab="Genotype Hazard Ratio",ylab="Power",
             sub=paste("n=",ns[1],", alpha=",round(unique(res$alpha),2))))