CLR wrapper function

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Description

Default wrapper function for the CLR network inference algorithm

Usage

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Arguments

data

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

Details

The Context Likelihood or Relatedness network (CLR) method derives a score that is associated to the empirical distribution of the mutual information values, in practice the score between gene Xi and gene Xj is defined as follows z_{ij}=√{z^2_i+z^2_j}, where:

z_i=max( 0,(I(Xi;Xj)-μ_i)/σ_i )

μ_i and σ_i are respectively the mean and standard deviation of the empirical distribution of the mutual information between both genes.

Value

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

References

Faith, Jeremiah J., et al. "Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles." PLoS biology 5.1 (2007): e8.

See Also

netbenchmark, evaluate, clr

Examples

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    # Data
    data <- grndata::getData(datasource.name = "toy",FALSE)
    # Inference
    net <- clr.wrap(data)