CLD.test: CLD (Composite Linkage Desequilibrium) based GGI analysis.

Description Usage Arguments Details Value References See Also Examples

View source: R/CLD.R

Description

CLD.test performs a Gene-Gene Interaction (GGI) analysis based on the difference between the Composite Linkage Disequilibrium measured in cases and controls respectively.

Usage

1
CLD.test(Y, G1, G2, n.perm = 1000)

Arguments

Y

numeric or factor vector with exactly two different values. Y is the response variable and should be of length equal to the number of rows of G1 and G2 arguments (number of individuals).

G1

SnpMatrix object. Must have a number of rows equal to the length of Y.

G2

SnpMatrix object. Must have a number of rows equal to the length of Y.

n.perm

positive integer. n.perm is the number of permutations performed to compute the pvalue. By default, n.perm is fixed to 1000.

Details

The test statistic is based on Nagao normalized Quadratic Distance (NQD), as described in Rajapakse et al. (2012). The pvalue is calculated using n.perm permutations of Y.

Value

A list with class "htest" containing the following components:

statistic

The value of the statistic CLD.

p.value

The p-value for the test.

estimate

The estimation of CLD

parameter

The number of permutations used to estimate the p-value.

null.value

The value of CLD under the null hypothesis.

alternative

a character string describing the alternative.

method

a character string indicating the method used.

data.name

a character string giving the names of the data.

References

Indika Rajapakse, Michael D. Perlman, Paul J. Martin, John A. Hansen, and Charles Kooperberg. Multivariate detection of gene-gene interactions. Genetic Epidemiology, 36(6) :622-630, 2012.

See Also

GGI

Examples

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2

GeneGeneInteR documentation built on May 2, 2018, 4:26 a.m.