haplo.bin {SimHap}R Documentation

Haplotype analysis for a binary trait

Description

haplo.bin performes a series of generalized linear models using a simulation-based approach to account for uncertainty in haplotype assignment when phase is unknown.

Usage

haplo.bin(formula1, formula2, pheno, haplo, sim, effect = "add", 
        sub = NULL)

Arguments

formula1 a symbolic description of the full model including haplotype parameters to be fit. The details of model specification are given below.
formula2 a symbolic description of the nested model excluding haplotype parameters, to be compared to formula1 in a likelihood ratio test.
pheno a phenotype data set.
haplo a haplo object made by make.haplo.rare.
sim the number of simulations from which to evaluate the results.
effect the genetic effect type: "add" for additive, "dom" for dominant and "rec" for recessive. Defaults to additive. See note.
sub an expression representing a subset of the data on which to perform the models.

Details

formula1 should be in the form outcome ~ predictor(s) + haplotype(s) and formula2 should be in the form outcome ~ predictor(s). A formula has an implied intercept term. See documentation for the formula function for more details of allowed formulae.

Value

haplo.bin returns an object of class hapBin.
The summary function can be used to obtain and print a summary of the results.
An object of class hapBin is a list containing the following components:

formula1 formula1 passed to haplo.bin.
formula1 formula2 passed to haplo.bin.
results a table containing the odds ratios, confidence intervals and p-values of the parameter estimates, averaged over the sim models performed.
empiricalResults a list containing the odds ratios, confidence intervals and p-values calculated at each simulation.
ANOD analysis of deviance table for the model fit using formula1, averaged over all simulations.
logLik the average log-likelihood for the generalized linear model fit using formula1.
LRT a likelihood ratio test, testing for significant improvement of the model when haplotypic parameters are included.
aic Akaike Information Criterion for the generalized linear model fit using formula1, averaged over all simulations.
aicPredicted Akaike Information Criteria calculated at each simulation.
effect the haplotypic effect modelled, `ADDITIVE', `DOMINANT' or `RECESSIVE'.

Note

To model a codominant haplotypic effect, define the desired haplotype as a factor in the formula1 argument. e.g. factor(h.AAA), and use the default option for effect.

Author(s)

Pamela A. McCaskie

References

Dobson, A.J. (1990) An Introduction to Generalized Linear Models. London: Chapman and Hall.

Hastie, T.J., Pregibon, D. (1992) Generalized linear models. Chapter 6 of Statistical Models in S, eds Chambers, J.M., Hastie, T.J., Wadsworth & Brooks/Cole.

Little, R.J.A., Rubin, D.B. (2002) Statistical Analysis with Missing Data. John Wiley and Sons, New Jersey.

McCaskie, P.A., Carter, K.W. Hazelton, M., Palmer, L.J. (2007) SimHap: A comprehensive modeling framework for epidemiological outcomes and a multiple-imputation approach to haplotypic analysis of population-based data, [online] www.genepi.org.au/simhap.

McCullagh, P., Nelder, J.A. (1989) Generalized Linear Models. London: Chapman and Hall.

Rubin, D.B. (1996) Multiple imputation after 18+ years (with discussion). Journal of the American Statistical Society, 91:473-489.

Venables, W.N., Ripley, D.B. (2002) Modern Applied Statistics with S. New York: Springer.

See Also

snp.bin, haplo.quant, haplo.quant, haplo.long

Examples


data(SNP.dat)

# convert SNP.dat to format required by infer.haplos
haplo.dat <- SNP2Haplo(SNP.dat)

data(pheno.dat)

# generate haplotype frequencies and haplotype design matrix
myinfer<-infer.haplos(haplo.dat) 

# print haplotype frequencies generated by infer.haplos
myinfer$hap.freq 

# generate haplo object where haplotypes with a frequency 
# below min.freq are grouped as a category called "rare"
myhaplo<-make.haplo.rare(myinfer,min.freq=0.05) 
mymodel <- haplo.bin(formula1=PLAQUE~AGE+SBP+h.N1AA, 
        formula2=PLAQUE~AGE+SBP, pheno=pheno.dat, haplo=myhaplo, sim=10)

# example with a subsetting variable, looking at males only
# and modelling a dominant haplotypic effect
mymodel <- haplo.bin(formula1=PLAQUE~AGE+SBP+h.N1AA, 
        formula2=PLAQUE~AGE+SBP, pheno=pheno.dat, haplo=myhaplo, 
        sim=10, effect="dom", sub=expression(SEX==1))


[Package SimHap version 1.0.0 Index]