AssotesteR (version 0.1-10)

RVT1: RVT1: Rare Variant Test 1 for dichotomous traits

Description

RVT1 has been proposed by Morris and Zeggini (2010) as a collapsing method based on a regression framework that models the phenotype as a function of a collapsed summary of the variants. More specifically, the considered summary in RVT1 is the proportion of rare variants that carry at least one copy of the minor allele. In this sense, RVT1 is an accumulation approach that regresses phenotype on a genetic score, defined as the proportion of sites within the gene that harbor mutations.

Usage

RVT1(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 the 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:

rvt1.stat

rvt1 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

RVT2

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 RVT1 with maf=0.05 and 500 permutations
#   myrvt1 = RVT1(phenotype, genotype, maf=0.05, perm=500)
#   myrvt1
#   ## End(Not run)