Bonferroni.sig {SNPassoc} | R Documentation |
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)
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 |
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.
Value
A data frame with the SNPs and the p values for those SNPs that are statistically significant after Bonferroni correction
See Also
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)