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.
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
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.
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.