SNPassoc (version 1.0-2)

haplo.interaction: Haplotype interaction with a covariate

Description

This function computes the ORs (or mean differences if a quantitative trait is analyzed) and their 95% confidence intervals corresponding to an interaction between the haplotypes and a categorical covariate

Usage

haplo.interaction(formula, data, SNPs.sel, quantitative = 
  is.quantitative(formula, data), haplo.freq.min = 0.05, sep="/", ...)

Arguments

formula

a symbolic description of the model to be fitted (a formula object). It might have either a continuous variable (quantitative traits) or a factor variable (case-control studies) as the response on the left of the

data

an optional data frame containing the variables in the model and the SNPs that will be used to estimate the haplotypes. If not found in 'data', the variables are taken from 'environment(formula)', typically the environment

SNPs.sel

a vector indicating the names of SNPs that are used to estimate the haplotypes

quantitative

logical value indicating whether the phenotype (which is on the left of the operator ~ in 'formula' argument) is quantitative. The function 'is.quantitative' returns FALSE when the phenotype

haplo.freq.min

control parameter for haplo.glm included in 'haplo.glm.control'. This parameter corresponds to the minimum haplotype frequency for a haplotype to be included in the regression model as its own effect. The

sep

character separator used to divide alleles. See snp function for details.

...

additional parameters for 'haplo.glm.control'.

Value

• Three different tables are given. The first one corresponds to the full interaction matrix where the ORs (or mean differences if a quantitative trait is analyzed) are expressed with respect to the most frequent haplotype and the first category of the covariate. The other two tables show the ORs (or mean differences if a quantitative trait is analyzed) and their 95% confidence intervals for both marginal models. P values for interaction are also showed in the output.

Details

The function estimates the haplotypes for the SNPs indicated in the 'SNPs.sel' argument. Then, usign 'haplo.glm' function (from 'haplo.stats' library) estimates the interaction between these haplotypes and the covariate indicated in the formula by means of 'interaction' function.

Examples

# not run
# data(SNPs)
# res<-haplo.interaction(log(protein)~int(sex), data=SNPs,
#  SNPs.sel=c("snp100019","snp10001","snp100029"),sep="")
# res