RedeR (version 1.20.0)

cea: Co-expression analysis.

Description

Simple function for correlation analysis. This function computes a null distribution via permutation and returns the significant correlation values.

Usage

cea(x, sig=0.01, p.adj.method="fdr", cor.method="spearman", nper=1000, plotcea=TRUE, ...)

Arguments

x

A matrix or data frame.

sig

Significance threshold.

p.adj.method

Correction method passed to "p.adjust" function.

cor.method

Correlation method passed to "cor" function.

nper

Number of permutations.

plotcea

Logical value, option to plot density and the null distributions.

...

Additional arguments passed to plotcea option.

Value

An adjacency matrix with significant correlation values.

Details

Additional arguments:

n.breaks

If plotcea=TRUE, 'n.breaks' sets the number of histogram breaks (Default=100 ).

plotnull

If plotcea=TRUE, 'plotnull' sets whether to plot the null distribution (Default=TRUE ).

avnull

If plotcea=TRUE, 'avnull' takes the average null distribution (Default=TRUE ).

nullcol

If plotcea=TRUE, 'nullcol' sets the color of the null distribution (Default="black" ).

See Also

cor p.adjust

Examples

data(ER.deg)
#--- a gene expression matrix
exp <- ER.deg$exp
#--- a sample from gx!! 
idx <- sample(1:nrow(exp))[1:100] 
exp <- exp[idx,]

## Not run: 
# 
# res <- cea(x=exp, nper=100) #ps set 'nper' for at least 1000
# ## End(Not run)