Default wrapper function for the Genie3 network inference algorithm
Numeric matrix with the microarray dataset to infer the network. Columns contain variables and rows contain samples.
GEne Network Inference with Ensemble of trees (Genie3) algorithm uses the Random Forests feature selection technique to solve a regression problem for each of the genes in the network. In each of the regression problems, the expression pattern of the target gene should be predicted from the expression patterns of all transcription factors. The importance of each transcription factor in the prediction of the target gene is taken as an indication of an apparent regulatory link. Then these candidate regulatory links are aggregated over all genes to generate a ranking for the whole network.
Genie3.wrap returns a matrix which is the weighted adjacency
matrix of the network inferred by Genie3 algorithm. 500 trees are used
in ensemble for each target gene.
Irrthum, Alexandre, Louis Wehenkel, and Pierre Geurts. "Inferring regulatory networks from expression data using tree-based methods." PloS one 5.9 (2010): e12776.
Breiman, Leo. "Random forests." Machine learning 45.1 (2001): 5-32.
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