Consensus Cluster Plus without Plots
consensusClusterNoPlots is a wrapper function for ConsensusClusterPlusthat suppresses the creation of the plots that are created automatically.
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