This function prunes (hierarchical) consensus modules by removing genes with low eigengene-based intramodular connectivity (KME) and by removing modules that do not have a certain minimum number of genes with a required minimum KME.
pruneConsensusModules( multiExpr,
multiWeights = NULL,
multiExpr.imputed = NULL,
MEs = NULL,
labels, unassignedLabel = if (is.numeric(labels)) 0 else "grey",
networkOptions,
consensusTree,
minModuleSize,
minCoreKMESize = minModuleSize/3,
minCoreKME = 0.5,
minKMEtoStay = 0.2,
# Module eigengene calculation options
impute = TRUE,
collectGarbage = FALSE,
checkWeights = TRUE,
verbose = 1, indent=0)
Expression data in the multi-set format (see checkSets). A vector of
lists, one per set. Each set must contain a component data that contains the expression data, with
rows corresponding to samples and columns to genes or probes.
optional observation weights in the same format (and dimensions) as multiExpr.
These weights are used for correlation calculations with data in multiExpr.
If multiExpr contain missing data, this argument can be used to supply the
expression data with missing data imputed. If not given, the impute.knn function will
be used to impute the missing data.
Optional consensus module eigengenes, in multi-set format analogous to that of multiExpr.
A vector (numeric, character or a factor) giving module labels for each variable (gene) in multiExpr.
The label (value in labels)
that represents unassigned genes. Module of this label will
not enter the module eigengene clustering and will not be merged with other modules.
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 of class ConsensusTree specifying the consensus calculation.
Minimum number of genes in a module. Modules that have fewer genes (after trimming) will be removed (i.e., their genes will be given the unassigned label).
a number between 0 and 1. If a detected module does not have at least
minModuleKMESize genes with consensus eigengene connectivity at least minCoreKME, the module is
disbanded (its genes are unlabeled).
see minCoreKME above.
genes whose consensus eigengene connectivity to their module eigengene is lower than
minKMEtoStay are removed from the module.
logical: should imputation be used for module eigengene calculation? See
moduleEigengenes for more details.
Logical: should garbage be collected after some of the memory-intensive steps?
Logical: should multiWeights be checked to make sure their dimensions are
concordant with multiExpr and the weights are valid?
integer level of verbosity. Zero means silent, higher values make the output progressively more and more verbose.
indentation for diagnostic messages. Zero means no indentation, each unit adds two spaces.
The pruned module labels: a vector of the same form as the input labels.