gap (version 1.1-16)

htr: Haplotype trend regression

Description

Haplotype trend regression (with permutation)

Usage

htr(y,x,n.sim=0)

Arguments

y

a vector of phenotype

x

a haplotype table

n.sim

the number of permutations

Value

The returned value is a list containing:

f

the F statistic for overall association

p

the p value for overall association

fv

the F statistics for individual haplotypes

pi

the p values for individual haplotypes

References

Zaykin DV, Westfall PH, Young SS, Karnoub MA, Wagner MJ, Ehm MG (2002) Testing association of statistically inferred haplotypes with discrete and continuous traits in samples of unrelated individuals. Hum. Hered. 53:79-91 Xie R, Stram DO (2005). Asymptotic equivalence between two score tests for haplotype-specific risk in general linear models. Genet. Epidemiol. 29:186-170

See Also

hap.score

Examples

## Not run: 
# # 26-10-03
# # this is now part of demo
# test2<-read.table("test2.dat")
# y<-test2[,1]
# x<-test2[,-1]
# y<-as.matrix(y)
# x<-as.matrix(x)
# htr.test2<-htr(y,x)
# htr.test2
# htr.test2<-htr(y,x,n.sim=10)
# htr.test2
# 
# # 13-11-2003
# data(apoeapoc)
# apoeapoc.gc<-gc.em(apoeapoc[,5:8])
# y<-apoeapoc$y
# for(i in 1:length(y)) if(y[i]==2) y[i]<-1
# htr(y,apoeapoc.gc$htrtable)
# 
# # 20-8-2008
# # part of the example from useR!2008 tutorial by Andrea Foulkes
# # It may be used beyond the generalized linear model (GLM) framework
# HaploEM <- haplo.em(Geno,locus.label=SNPnames)
# HapMat <- HapDesign(HaploEM)
# m1 <- lm(Trait~HapMat)
# m2 <- lm(Trait~1)
# anova(m2,m1)
# ## End(Not run)