AssotesteR (version 0.1-10)

RVT2: RVT2: Rare Variant Test 2 for dichotomous traits

Description

RVT2 is a collapsing method developed by Morris and Zeggini (2010) based on a regression framework that models the phenotype as a function of a collapsed summary of the variants. In the case of RVT@, the collapsed summary consists of the presence or absence of at least one minor allele at any rare variant. In this sense, RVT2 is an accumulation approach that regresses phenotype on a genetic score, defined as the presence of at least one minor allele at any rare variant

Usage

RVT2(y, X, maf = 0.05, 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 minor allele frequency threshold for rare variants (maf=0.05 by default)

perm

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

Value

"assoctest", basically a list with the following elements:

rvt2.stat

rvt2 statistic

asym.pval

asymptotic p-value

perm.pval

permuted p-value

args

descriptive information with number of controls, cases, variants, rare variants, maf threshold, and permutations

name

name of the statistic

Details

If no variants are below the specified maf threshold, the function will stop and return an error message

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

References

Morris AP, Zeggini E (2010) An Evaluation of Statistical Approaches to Rare Variants Analysis in Genetic Association Studies. Genetic Epidemiology, 34: 188-193

Asimit J, Zeggini E (2010) Rare Variant Association Analysis Methods for Complex Traits. Annual Review of Genetics, 44: 293-308

See Also

RVT1

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 RVT2 with maf=0.05 and 500 permutations
#   myrvt2 = RVT2(phenotype, genotype, maf=0.05)
#   myrvt2 
#   ## End(Not run)