cca: A modified CCA approach for spectral clustering.
In norbertbin/rCASC: Covariate assisted spectral clustering package

Uses the eigenvectors of adjMat

1 2	cca(adjMat, covMat, nBlocks, method = "regLaplacian", rowNorm = F, center = F, verbose = F, randStarts = 10)

`adjMat`	An adjacency matrix
`covMat`	A covariate matrix
`nBlocks`	The number of clusters
`method`	The form of the adjacency matrix to be used.
`rowNorm`	True if row normalization should be done before running kmeans.
`center`	A boolean indicating if the covariate matrix columns should be centered.
`verbose`	A boolean indicating if casc output should include eigendecomposition.
`randStarts`	Number of random restarts for kmeans.