AssotesteR (version 0.1-10)

VT: VT: Variable Threshold

Description

The Variable Threshold (VT) test has been proposed by Price et al (2010) based on the assumption that the minor allele frequencies of the causal rare variants may be different from those nonfunctional rare variants, which, if true, can be utilized to improve the power of the corresponding pooled association tests. The idea behind this approach is that there exists some (unknown) threshold T for which variants with a minor allele frequency (MAF) below T are more likely to be functional than are variants with an MAF above T. VT works by finding the maximum z-score across all possible values for the threshold T.

Usage

VT(y, X, maf = 0.05, perm = 100)

Arguments

y

numeric vector with phenotype status: 0=controls, 1=cases. No missing data allowed

X

numeric matrix or data frame with genotype data coded as 0, 1, 2. Missing data is allowed

maf

numeric value indicating the minor allele frequency threshold for rare variants (must be a positive number between 0 and 1, maf=0.05 by default)

perm

positive integer indicating the number of permutations (100 by default)

Value

"assoctest", basically a list with the following elements:

vt.stat

vt statistic

perm.pval

permuted p-value

args

descriptive information with number of controls, cases, variants, and permutations

name

name of the statistic

Details

There is no imputation for the missing data. Missing values are simply ignored in the computations.

References

Price AL, Kryukov GV, de Bakker PIW, Purcell SM, Staples J, Wei LJ, Sunyaev SR (2010) Pooled Association Tests for Rare Variants in Exon-Sequencing Studies. The American Journal of Human Genetics, 86: 832-838

See Also

WSS

Examples

  ## Not run: 
#   
#   # number of cases
#   cases = 500
# 
#   # number of controls
#   controls = 500
# 
#   # total (cases + controls)
#   total = cases + controls
# 
#   #  phenotype vector
#   phenotype = c(rep(1, cases), rep(0, controls))
# 
#   # genotype matrix with 10 variants (random data)
#   set.seed(1234)  
#   genotype = matrix(rbinom(total*10, 2, 0.051), nrow=total, ncol=10)
# 
#   # apply VT with maf=0.05 and 500 permutations
#   myvt = VT(phenotype, genotype, maf=0.05, perm=500)
#   myvt
#   ## End(Not run)