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

Description Usage Arguments Details Value Author(s) References See Also Examples

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

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  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)

Details

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:

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

Author(s)

Gaston Sanchez

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

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  ## 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)


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