Usage
progenyClust(data, FUNclust = kmeans, method = "gap", score.invert = F, ncluster = 2:10,
size = 10, iteration = 100, repeats = 1, nrandom = 10, ...)## S3 method for class 'progenyClust':
summary(object,...)
Arguments
data
data matrix or data frame for clustering: each row correpsonds to a sample or observation, whereas each column corresponds to a feature or variable.
FUNclust
clustering function: accepts data as its first argument and the number for clustering as the second argument; returns a list containing a component called 'cluster' which is a vector of integers recording the clustering assignment for all samples. The def
method
character string indicating the criterion used to pick the optimal cluster number.
'gap': the default value, selecting the cluster number that has the biggest or smallest (when score.invert=TRUE) gap from its neighboring numbrs. The optimal cluster number
score.invert
logical flag: specifies whether the score should be inverted. The default score is the ratio of true classification probabilities over false classification probilities. The inverted score is the ratio of false classification over true classification probi
ncluster
sequence of integers specifying candidate cluster numbers for evaluation: ncluster needs to be continuous if the method 'gap' is chosen.
size
integer specifying the number of progenies generated from each cluster. Default value is 10.
iteration
integer specifying the number of times the algorithm samples progenies and evalutes similarity among progenies. Default value is 100.
repeats
integer specifying the number of times the algorithm should be run: needs to be greater than 0. Values greater than 1 output standard deviations of the scores, which are plotted as error bars in print(...,errorbar=T,...) function. Default value is 1.
nrandom
integer specifying the number of random datasets used to generate reference scores when using method 'score'. Default value is 10.
object
the S3 object of class "progenyClust".
...
additional arguments for FUNclust in progenyClust(...).