permutest: Permutation Test P-value for Multivaraite Correlation

In CORREP: Multivariate Correlation Estimator and Statistical Inference Procedures.

Description

This function calculates p-values of the multivariate correlation estimator by enumerating all permutations. We recommend using Likehood Ratio Test implemented in function cor.LRtest if your data has moderate to large sample size (>5) The procedure is same as those permutation tests for Pearson correlation coefficient or other parameters. Since the approximation of null distribution requires enumerating all permutations. The computational burden increases in $n^2$.

Usage

permutest(x, y=NULL, m, G)

Arguments

x	data matrix, column represents samples (conditions), and row represents variables (genes), see example below for format information
y	optional, used when x and y are vectors
m	number of replicates
G	number of genes

Details

See manuscript.

Value

PV	P-values of permutation tests

Author(s)

Dongxiao Zhu and Youjuan Li

References

Zhu, D and Li Y. 2007. Multivariate Correlation Estimator for Inferring Functional Relationships from Replicated 'OMICS' data. Submitted.

See Also

cor.LRtest, cor.LRtest.std, cor.test

Examples

library("CORREP")
library("e1071")
d0 <- NULL
## sample size is set to 5, it takes about a min to finish 
for(l in 1:5)
d0 <- rbind(d0, rnorm(100))
## data must have row variance of 1 
d0.std <- apply(d0, 2, function(x) x/sd(x))
M <- cor.balance(t(d0.std), m = 4, G= 25)
M.pv <- permutest(t(d0.std), m = 4, G= 25)

Example output

CORREP documentation built on Nov. 8, 2020, 5:09 p.m.