Description Usage Arguments Details Value References See Also Examples
Default wrapper function for the C3net network inference algorithm
1 |
data |
Numeric matrix with the microarray dataset to infer the network. Columns contain variables and rows contain samples. |
The Conservative Causal Core NETwork (C3NET) consists of two main steps. The first step is the elimination of non-significant edges, and the second step selects for each gene the edge among the remaining ones with maximum mutual information value. C3NET does not aim at inferring the entire network underlying gene regulation but mainly tries to recover the core structure.
c3net.wrap
returns a matrix which is the weighted adjacency
matrix of the network inferred by c3net algorithm.
The Mutual Information threshold is set to 0
- see c3net
.
Altay, G\"okmen, and Frank Emmert-Streib. "Inferring the conservative causal core of gene regulatory networks." BMC Systems Biology 4.1 (2010): 132.
1 2 3 4 | # Data
data <- grndata::getData(datasource.name = "toy",FALSE)
# Inference
net <- c3net.wrap(data)
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