Genie3.wrap: Genie3 wrapper function

In netbenchmark: Benchmarking of several gene network inference methods

Description

Default wrapper function for the Genie3 network inference algorithm

Usage

    Genie3.wrap(data)

Arguments

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

Details

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.

Value

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.

References

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.

See Also

netbenchmark, evaluate

Examples

    # Data
    data <- runif(100)
    dim(data) <- c(10,10)
    # Inference
    net <- Genie3.wrap(as.data.frame(data))

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