aracne.wrap: aracne wrapper function

In netbenchmark: Benchmarking of several gene network inference methods

Description

Default wrapper function for the aracne network inference algorithm

Usage

    aracne.wrap(data)

Arguments

data	Numeric matrix with the microarray dataset to infer the network.Columns contain variables and rows contain samples.

Details

The motivation of the Algorithm for the Reconstruction of Accurate Cellular NEtworks (ARACNE) is that many similar measures between variables may be the result of indirect effects. In order to delete the indirect effect the algorithm relies on the “Data Processing Inequality”, this process removes the weakest link in every triplet of connected variables.

Value

aracne.wrapper returns a matrix which is the weighted adjacency matrix of the network inferred by aracne algorithm. The wrapper uses the "spearman" correlation (can be used with continuous data) to estimate the entropy - see build.mim

References

Margolin, Adam A., et al. "ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context." BMC Bioinformatics 7.Suppl 1 (2006): S7.

Meyer, Patrick E., Frederic Lafitte, and Gianluca Bontempi. "minet: AR/Bioconductor package for inferring large transcriptional networks using mutual information." BMC Bioinformatics 9.1 (2008): 461.

See Also

netbenchmark, evaluate, aracne

Examples

    # Data
    data <- runif(100)
    dim(data) <- c(10,10)
    # Inference
    net <- aracne.wrap(as.data.frame(data))

netbenchmark documentation built on May 2, 2019, 6:08 p.m.