aracne.m: Algorithm for the Reconstruction of Accurate Cellular...

In parmigene: Parallel Mutual Information Estimation for Gene Network Reconstruction

Algorithm for the Reconstruction of Accurate Cellular Networks

Description

A function that implements the ARACNE algorithm for the reconstruction of gene interaction networks (multiplicative model).

Usage

aracne.m(mi, tau=0.15)

Arguments

mi	matrix of the mutual information.
tau	a positive numeric value used to remove the weakest edge of each triple of nodes.

Details

This algorithm considers each triple of edges independently and removes the weakest one if

MI(i;j) < MI(j;k) * (1 - \tau

and

MI(i;j) < MI(i;k) * (1 - \tau)

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.

Value

A square weighted adjacency matrix of the inferred network.

References

Adam A. Margolin, Ilya Nemenman, Katia Basso, Chris Wiggins, Gustavo Stolovitzky, Riccardo Dalla Favera, and Andrea Califano. Aracne : An algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformatics, 2006.

See Also

aracne.a

clr

mrnet

Examples

mat <- matrix(rnorm(1000), nrow=10)
mi  <- knnmi.all(mat)
grn <- aracne.m(mi, 0.15)

parmigene documentation built on Oct. 30, 2024, 9:12 a.m.