AssotesteR (version 0.1-10)

CMC: CMC: Combined Multivariate and Collapsing Method

Description

The CMC method is a pooling approach proposed by Li and Leal (2008) that uses allele frequencies to determine the partition of the variants into groups. After the rare variants are selected, they are collapsed into an indicator variable, and then a multivariate test such as Hotelling's T2 test is applied to the collection formed by the common variants and the collapsed super-variant.

Usage

CMC(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 (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:

cmc.stat

cmc statistic

asym.pval

asymptotic p-value

perm.pval

permuted p-value

args

descriptive information with number of controls, cases, variants, rare variants, maf threshold, and permutations

name

name of the statistic

Details

Those variants with minor allele frequency below the specified maf threshold are collapsed into a single super variant There is no imputation for the missing data. Missing values are simply ignored in the computations.

References

Li B, Leal SM (2008) Methods for Detecting Associations with Rare Variants for Common Diseases: Application to Analysis of Sequence Data. The American Journal of Human Genetics, 83: 311-321

See Also

WSS, CMAT, TTEST

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 CMC with maf=0.05 and 500 permutations
#   mycmc = CMC(phenotype, genotype, maf=0.05, perm=500)
#   mycmc
#   ## End(Not run)