R: RWAS: Rare-Variant Weighted Aggregate Statistic

RWAS {AssotesteR} | R Documentation

## RWAS: Rare-Variant Weighted Aggregate Statistic

### Description

The RWAS method has been proposed by Sul et al (2011) as a pooling method that groups variants and computes a weighted sum of differences between case and control mutation counts where weights are estimated from data. Under the null hypothesis the RWAS statistic has an asymptotic standard normal distribution, but a permutation procedure can also be applied to assess statistical significance

### Usage

      RWAS(y, X, maf = 0.05, perm = NULL)

### 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 (`ma f=0.05` by default)
`perm` | positive integer indicating the number of permutations (`NULL` 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:

`rwas.stat` | rwas statistic
`asym.pval` | asymptotic p-value
`perm.pval` | permuted p-value, only when `perm` is used
`args` | descriptive information with number of controls, cases, variants, rare variants, maf and permutations
`name` | name of the statistic

### Author(s)

Gaston Sanchez

### References

Sul JH, Han B, He D, Eskin E (2011) An Optimal Weighted Aggregated Association Test for Identification of Rare Variants Involved in Common Diseases. Genetics, 188: 181-188

### See Also

`CMC`

### 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 RWAS with maf=0.05 and 500 permutations
      myrwas = RWAS(phenotype, genotype, maf=0.05, perm=500)
      myrwas

    ## End(Not run)

[Package AssotesteR version 0.1-10 Index]