R: CMAT: Cumulative Minor Allele Test

CMAT {AssotesteR} | R Documentation

## CMAT: Cumulative Minor Allele Test

### Description

CMAT is a pooling method proposed by Zawistowski et al (2010). CMAT works by comparing weighted minor-allele counts (for cases and controls) against the weighted major-allele counts (for cases and controls). Although the CMAT test statistic is based on a chi-square statistic, it does not follow a known distribution and its significance has to be determined by a permutation procedure.

### Usage

      CMAT(y, X, maf = NULL, weights = NULL, 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` | optional numeric value to specify a threshold for the minor allele frequency of rare variants (`NULL` by default)
`weights` | optional vector of weights for the variants (`NULL` by default)
`perm` | positive integer indicating the number of permutations (100 by default)

### Details

By default, argument `maf=NULL` meaning that no rare variants are selected

By default, argument `weights=NULL` but different values for the variants can be provided

Statistical significance is determined by permutation procedure

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

### Value

An object of class `"assoctest"`, basically a list with the following elements:

`cmat.stat` | cmat statistic
`perm.pval` | permuted p-value
`args` | descriptive information with number of controls, cases, variants, rare variants, maf, and permutations
`name` | name of the statistic

### Author(s)

Gaston Sanchez

### References

Zawistowski M, Gopalahrishnan S, Ding J, Li Y, Grimm S, Zollner S (2010) The American Journal of Human Genetics, 87: 604-617

### See Also

`CMC`, `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 CMAT with 500 permutations
      mycmat1 = CMAT(phenotype, genotype, perm=500)
      mycmat1

      # apply CMAT with maf=0.05 and 500 permutations
      mycmat2 = CMAT(phenotype, genotype, maf=0.05, perm=500)
      mycmat2

    ## End(Not run)

[Package AssotesteR version 0.1-10 Index]