simulateEigengeneNetwork: Simulate eigengene network from a causal model
In WGCNA: Weighted Correlation Network Analysis

simulateEigengeneNetwork

R Documentation

Simulate eigengene network from a causal model

Simulates a set of eigengenes (vectors) from a given set of causal anchors and a causal matrix.

simulateEigengeneNetwork(
  causeMat, 
  anchorIndex, anchorVectors, 
  noise = 1, 
  verbose = 0, indent = 0)

`causeMat`	causal matrix. The entry `[i,j]` is the influence (path coefficient) of vector `j` on vector `i`.
`anchorIndex`	specifies the indices of the anchor vectors.
`anchorVectors`	a matrix giving the actual anchor vectors as columns. Their number must equal the length of `anchorIndex`.
`noise`	standard deviation of the noise added to each simulated vector.
`verbose`	level of verbosity. 0 means silent.
`indent`	indentation for diagnostic messages. Zero means no indentation; each unit adds two spaces.

The algorithm starts with the anchor vectors and iteratively generates the rest from the path coefficients given in the matrix causeMat.

A list with the following components:

`eigengenes`	generated eigengenes.
`causeMat`	a copy of the input causal matrix
`levels`	useful for debugging. A vector with one entry for each eigengene giving the number of generations of parents of the eigengene. Anchors have level 0, their direct causal children have level 1 etc.
`anchorIndex`	a copy of the input `anchorIndex`.