predictClasses,ConsensusMetaclusteringModel,ANY-method {PDATK} | R Documentation |
Compute the Optimal Clustering Solution for a Trained
ConsensusMetaclusteringModel
Description
Compute the optimal clustering solution out of possibilities generated
with trainModel. Assigns the cluster labels to the MultiAssayExperiment
object.
Usage
## S4 method for signature 'ConsensusMetaclusteringModel,ANY'
predictClasses(object, ..., optimal_k_function = optimalKMinimizeAmbiguity)
Arguments
object |
A MutliAssayExperiment object
|
... |
Fall through arguments to optimal_k_function . For the default
optimal_k_function , you can specify subinterval argument which defines
the interval of the ECDF to minimize ambiguity over. Defaults to c(0.1, 0.9)
if not specified. See ?optimalKMinimizeAmbiguity for more details on
the subinterval parameter.
|
optimal_k_function |
A function which accepts as its input models(object)
of a trained ConsensusMetaclusteringModel object, and returns a vector
of optimal K values, one for each assay in rawdata(object) . The default
method is optimalKMinimizeAmbiguity , see ?optimalKMinimizeAmbiguity
for more details. Please note this argument must be named or it will not
work.
|
Value
A object
ConsensusMetaclusteringModel
, with class predictions
assigned to the colData of trianData
[Package
PDATK version 1.0.2
Index]