RARECOVER: RARECOVER Algorithm

In AssotesteR: Statistical Tests for Genetic Association Studies

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)

Example output

Loading required package: mvtnorm

 	 RARECOVER Algorithm 

Info: 
   cases  controls  variants   rarevar       maf    varsel   n.perms  
     500       500        10         5      0.05         3       500  

  rc.stat   perm.pval   
 2.791792    0.488000   

AssotesteR documentation built on May 2, 2019, 3:55 a.m.