consensusClusterNoPlots: Consensus Cluster Plus without Plots
In neatmaps: Heatmaps for Multiple Network Data

consensusClusterNoPlots is a wrapper function for ConsensusClusterPlusthat suppresses the creation of the plots that are created automatically.

1 2	consensusClusterNoPlots(df, link_method, dist_method, max_k, reps, p_var, p_net, cc_seed)

`df`	A dataframe of network attributes containing only numeric values. The columns of the dataframe should likely be normalized.
`link_method`	The agglomeration method to be used for hierarchical clustering. Defaults to the average linkage method. See other methods in `hclust`.
`dist_method`	The distance measure to be used between columns and between rows of the dataframe. Distance is used as a measure of similarity. Defaults to euclidean distance. See other options in `dist`.
`max_k`	The maximum number of clusters to consider in the consensus clustering step. Consensus clustering will be performed for max_k-1 iterations, i.e. for 2, 3, ..., max_k clusters. Defaults to 10.
`reps`	The number of subsamples taken at each iteration of the consensus cluster algorithm. Defaults to 1000.
`p_var`	The proportion of network variables to be subsampled during consensus clustering. Defaults to 1.
`p_net`	The proportion of networks to be subsampled during consensus clustering. Defaults to 0.8.
`cc_seed`	The seed used to ensure the reproducibility of the consensus clustering. Defaults to 1. @author Philippe Boileau , philippe_boileau@berkeley.edu @importFrom ConsensusClusterPlus ConsensusClusterPlus @importFrom grDevices png dev.off