INetTool (version 0.1.1)

consensusNet: consensusNet

Description

This function computes the INet Algorithm for the construction of a **Consensus Network**.

Usage

consensusNet(
  adjL,
  threshold = 0.5,
  tolerance = 0.1,
  theta = 0.04,
  nitermax = 50,
  ncores = 2,
  verbose = TRUE
)

Value

a list of 3 types: $graphConsensus the Consensus Network, $Comparison the Jaccard weighted distances between the graphs calculated in each iteration, $similarGraphs the similar graphs before the Thresholding

Arguments

adjL

list of weighted adjacency matrix with the same name in rows and columns for all the matrices.

threshold

threshold for the construction of the Consensus (default 0.5). Used in the last step on the similar graphs.

tolerance

the tolerance of differences between similar graphs for the construction of the Consensus (default 0.1).

theta

importance to give to the neighbourhood part of the weight (default 0.04).

nitermax

maximum number of iteration before stopping the algorithm (default 50).

ncores

number of CPU cores to use (default is 2). We suggest to use ncores equal to the number of graphs to integrate.

verbose

flag for verbose output (default as TRUE).

Examples

data("adjL_data")
consensusNet(adjL_data)