RBT: Replication Based Test

Description

The Replication-Based Test has been proposed by Ionita-Laza et al (2011). RBT is based on a weighted-sum statistic that is similar to a pooled association test but purposefully designed to deal with possibly different association directions. The significance of the statistic has to be calculated by permutations.

Usage

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  RBT(y, X, 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

perm

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

Details

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:

rbt.stat

rbt statistic

perm.pval

permuted p-value

args

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

name

name of the statistic

Author(s)

Gaston Sanchez

References

Ionita-Laza I, Buxbaum JD, Laird NM, Lange C (2011) A New Testing Strategy to Identify Rare Variants with Either risk or Protective Effects on Disease. PLoS Genetics, 7(2): e1001289

See Also

WSS, CMC

Examples

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  ## 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(123)
  genotype = matrix(rbinom(total*10, 2, 0.05), nrow=total, ncol=10)

  # apply RBT with 500 permutations
  myrbt = RBT(phenotype, genotype, perm=500)
  myrbt
  
## End(Not run)