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

In GeneGeneInteR: Tools for Testing Gene-Gene Interaction at the Gene Level

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

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

data(gene.pair)
CLD.test(Y=gene.pair$Y, G1=gene.pair$G1,G2=gene.pair$G2)

GeneGeneInteR documentation built on Nov. 8, 2020, 6:28 p.m.