entropyTest: One-sided two-sample test for entropy comparison
In sigaR: Statistics for Integrative Genomics Analyses in R

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

A one-sided two-sample test compares the entropy of a (high-dimensional) multivariate random variable between two groups. The test is one-sided: one group is a priori suspected to have a larger entropy. The null distribution is obtained via an efficient permutation resampling algorithm.

1 2	entropyTest(Y, id, nPerm = 1000, method = "normal", k0 = 1, k1 = 1, center = TRUE, lowCiThres=0.10, ncpus=1, verbose=FALSE)

`Y`	(High-dimensional) matrix. Rows are assumed to represent the samples, and columns represent the samples' genes or traits.
`id`	An indicator variable for the two groups to be compared. The groups should be coded as `0` and `1`. There is an asymmetric interest in the groups: the group indicated by `1` is believed to exhibit a larger entropy.
`nPerm`	Number of permutations.
`method`	Distributional assumption under which entropy is to be estimated.
`k0`	k-nearest neighbor parameter for group comprising of samples indicated by a zero in the indicator variable `id`.
`k1`	k-nearest neighbor parameter for group comprising of samples indicated by a one in the indicator variable `id`.
`center`	Logical indicator: should the columns of Y be centered around zero?
`lowCiThres`	A value between 0 and 1. Determines speed of efficient p-value calculation. If the probability of a p-value being below `lowCiThres` is smaller than 0.001 (read: the test is unlikely to become significant), the permutation analysis is terminated and a p-value of 1.00 is reported.
`ncpus`	Number of cpus used for the permutations.
`verbose`	Logical indicator: should intermediate output be printed on the screen?

Object of entTest-class.

Wessel N. van Wieringen: w.vanwieringen@vumc.nl

Van Wieringen, W.N., Van der Vaart, A.W. (2011), "Statistical analysis of the cancer cell's molecular entropy using high-throughput data", Bioinformatics, 27(4), 556-563.

Van Wieringen, W.N., Van de Wiel, M.A., Van der Vaart, A.W. (2008), "A test for partial differential expression", Journal of the American Statistical Association, 103(483), 1039-1049.

hdEntropy

# load data
data(pollackGE16) 
Y <- exprs(pollackGE16) 

# assign samples to groups
id <- sample(c(0,1), 41, replace=TRUE) 

# perform testing and print test results
testRes <- entropyTest(t(Y), id, nPerm = 5, method="knn") 
summary(testRes)

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Loading required package: mvtnorm
Two-sample entropy test: 
Test statistic: -6.686,  p-value: 1 
Remarks: resampling terminated prematurely: unlikely significance