parmigene (version 1.1.0)

clr: Context Likelihood or Relatedness Network

Description

A function that infers the interaction network using the CLR algorithm.

Usage

clr(mi)

Arguments

mi

matrix of the mutual information.

Value

A square weighted adjacency matrix of the inferred network.

Details

CLR computes the score

$$sqrt(z_i^2 + z_j^2)$$

for each pair of variables \(i, j\), where

$$z_i = max(0, ( I(X_i;X_j)-mean(X_i) ) / sd(X_i))$$

and \(mean(X_i)\) and \(sd(X_i)\) are the mean and the standard deviation of the mutual information values \(I(X_i;X_k)\) for all \(k=1,\ldots,n\).

By default, the function uses all the available cores. You can set the actual number of threads used to N by exporting the environment variable OMP_NUM_THREADS=N.

References

Jeremiah J. Faith, Boris Hayete, Joshua T. Thaden, Ilaria Mogno, Jamey Wierzbowski, Guillaume Cottarel, Simon Kasif, James J. Collins, and Timothy S. Gardner. Large-scale mapping and validation of escherichia coli transcriptional regulation from a compendium of expression profiles. PLoS Biology, 2007.

See Also

aracne.a

aracne.m

mrnet

Examples

# NOT RUN {
mat <- matrix(rnorm(1000), nrow=10)
mi  <- knnmi.all(mat)
grn <- clr(mi)
# }