AssotesteR (version 0.1-10)

UMINP: UMINP: Univariate minP (minimum p-value)

Description

UMINP is the Univariate minP that tests on each single genetic variant (e.g. SNP) one-by-one and then takes the minimum of their p-values, Its null distribution is based on numerical integration with respect to a multivariate normal distribution.

Usage

UMINP(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:

uminp.stat

uminp 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 Disease Association with Multiple SNPs. Human Heredity, 69: 120-130

See Also

SCORE, SUM

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 UMINP with 500 permutations
#   myuminp = UMINP(phenotype, genotype, perm=500)
#   myuminp
#   ## End(Not run)