R: RARECOVER Algorithm

RARECOVER {AssotesteR} | R Documentation

## RARECOVER Algorithm

### Description

RARECOVER is an algorithm proposed by Bhatia et al (2010) that determines the set of variants in a manner of forward variable selection: starting from a null model without any genetic variants, genetic variants are selected one by one based on their statistical significance and then added into the model

### Usage

      RARECOVER(y, X, maf = 0.05, dif = 0.5, 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)
`dif` | numeric value between 0 and 1 as a threshold for the decision criterion in the RARECOVER algorithm (default `dif=0.5`)
`perm` | positive integer indicating the number of permutations (100 by default)

### Details

The applied association test statistic (denoted as `XCORR` in Bhatia et al, 2010) is based on the Pearsons chi-square statistic

The argument `maf` is used to specify the threshold of the minor allele frequency for rare variants. By default, only variants below `maf=0.05` are taken into account in the analysis. However, if all variants in `X` are considered as rare variants, setting `maf=1` will consider them all for the analysis

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:

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

### Author(s)

Gaston Sanchez

### References

Bhatia G, Bansal V, Harismendy O, Schork NJ, Topol EJ, Frazer K, Bafna V (2010) A Covering Method for Detecting Genetic Associations between Rare Variants and Common Phenotypes. PLoS Computational Biology, 6(10): e1000954

### 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 RARECOVER with dif=0.05 and 500 permutations
      myrc = RARECOVER(phenotype, genotype, maf=0.05, perm=500)
      myrc

    ## End(Not run)

[Package AssotesteR version 0.1-10 Index]