AssotesteR (version 0.1-10)

SUM: SUM: Sum Test

Description

The SUM test has been proposed by Pan (2009) based on a modification of the Score. The idea behind the Sum Test is to test on only one parameter under the assumption of a common association strength between each of multiple genetic variants (e.g. SNPs) and the trait under analysis. The Sum test focuses on a scalar function of the multiple parameters with a resulting degree of freedom DF=1

Usage

SUM(y, X, 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

perm

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

Value

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

sum.stat

sum statistic

asym.pval

asymptotic p-value

perm.pval

permuted p-value

args

descriptive information with number of controls, cases, variants, and permutations

name

name of the statistic

Details

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

References

Pan W (2009) Asymptotic tests of association with multiple SNPs in linkage disequilibrium. Genetic Epidemiology, 33: 497-507

Pan W, Han F, Shen X (2010) Test Selection with Application to Detecting Association with Multiple SNPs. Human Heredity, 69: 120-130

See Also

SCORE, SSU, SSUW, WST

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(123)
#   genotype = matrix(rbinom(total*10, 2, 0.05), nrow=total, ncol=10)
# 
#   # apply SUM with 500 permutations
#   mysum = SUM(phenotype, genotype, perm=500)
#   mysum
#   ## End(Not run)