This function calculates a hiearchical consensus similarity of the input eigengenes, clusters the eigengenes according to the similarity and returns the input module eigengenes ordered by the order of resulting dendrogram.
orderMEsByHierarchicalConsensus(
MEs,
networkOptions,
consensusTree,
greyName = "ME0",
calibrate = FALSE)Module eigengenes, or more generally, vectors, to be ordered, in a multiData format: A vector of
lists, one per set. Each set must contain a component data that contains the module eigenegens or
general vectors, with
rows corresponding to samples and columns to genes or probes.
A single list of class NetworkOptions giving options for network calculation for all of the
networks, or a multiData structure containing one such list for each input data set.
A list specifying the consensus calculation. See newConsensusTree for details.
Specifies the column name of eigengene of the "module" that contains unassigned genes. This eigengene (column) will be excluded from the clustering and will be put last in the order.
Logical: should module eigengene similarities be calibrated? This setting overrides the calibration options
in consensusTree.
A multiData structure of the same format as the input MEs, with columns ordered
by the calculated dendrogram.
hierarchicalConsensusMEDissimilarity for calculating the consensus ME dissimilarity