SNPassoc (version 2.0-11)

Bonferroni.sig: Bonferroni correction of p values

Description

This function shows the SNPs that are statistically significant after correcting for the number of tests performed (Bonferroni correction) for an object of class "WGassociation"

Usage

Bonferroni.sig(x, model = "codominant", alpha = 0.05, 
      include.all.SNPs=FALSE)

Value

A data frame with the SNPs and the p values for those SNPs that are statistically significant after Bonferroni correction

Arguments

x

an object of class 'WGassociation'.

model

a character string specifying the type of genetic model (mode of inheritance). This indicantes how the genotypes should be collapsed when 'plot.summary' is TRUE. Possible values are "codominant", "dominant", "recessive", "overdominant", or "log-additive". The default is "codominant". Only the first words are required, e.g "co", "do", ... .

alpha

nominal level of significance. Default is 0.05

include.all.SNPs

logical value indicating whether all SNPs are considered in the Bonferroni correction. That is, the number of performed tests is equal to the number of SNPs or equal to the number of SNPs where a p value may be computed. The default value is FALSE indicating that the number of tests is equal to the number of SNPs that are non Monomorphic and the rate of genotyping is greater than the percentage indicated in the GeneticModel.pval function.

Details

After deciding the genetic model, the function shows the SNPs that are statistically significant at alpha level corrected by the number of performed tests.

See Also

WGassociation

Examples

data(SNPs)
datSNP<-setupSNP(SNPs,6:40,sep="")
ans<-WGassociation(protein~1,data=datSNP,model="all")
Bonferroni.sig(ans, model="codominant", alpha=0.05, include.all.SNPs=FALSE)