Wrapper function for mutual information matrix estimators

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Description

Mutual information matrix estimation wrapper function for various mutual information estimators. Depends on infotheo package for mutual information estimators on discrete variables.

Usage

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  mimwrap(dataset, estimator="pearson", disc="equalwidth", bins = sqrt(ncol(dataset)))

Arguments

dataset

Data gene expression matrix where rows denote genes (features) and columns samples.

estimator

estimators for continuous variables "pearson" (default), "spearman", "kendall", "spearman"

estimators for discrete variables (infotheo package) "emp", "mm","sg","shrink"

disc

only required for discrete estimators (see infotheo package) "equalwidth" (default), "globalequalwidth" , "equalfreq"

bins

number of bins for the descretize function (infotheo), default sqrt(ncol(dataset))

Details

A mutual information matrix is estimated from a gene expression data set

Value

mimwrap returns a symmetric mutual information matrix for various mutual information estimators.

References

Patrick E Meyer, Frederic Lafitte and Gianluca Bontempi, minet: A R/Bioconductor Package for Inferring Large Transcriptional Networks Using Mutual Information, BMC Bioinformatics 2008, 9:461

Carsten O. Daub, Ralf Steuer, Joachim Selbig, and Sebastian Kloska, Estimating mutual information using B-spline functions - an improved similarity measure for analysing gene expression data, BMC Bioinformatics. 2004; 5: 118

de Matos Simoes R, Emmert-Streib F., Bagging statistical network inference from large-scale gene expression data., PLoS One. 2012;7(3):e33624. Epub 2012 Mar 30.

Examples

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data(expmat)
mim <- mimwrap(expmat)