runClara: runClara

In JhuangLab/flowSpy: A Toolkit for Flow And Mass Cytometry Data

Description

Clustering a data matrix into k clusters

Usage

runClara(
  object,
  k = 25,
  metric = c("euclidean", "manhattan", "jaccard"),
  stand = FALSE,
  samples = 5,
  scale = TRUE,
  trace = 0,
  verbose = FALSE,
  ...
)

Arguments

object	an FSPY object
k	numeric. The number of clusters. It is required that 0 < k < n where n is the number of observations (i.e., n = nrow(x)).
metric	character. string specifying the metric to be used for calculating dissimilarities between observations.
stand	logical. Indicating if the measurements in x are standardized before calculating the dissimilarities.
samples	numeric. Say N, the number of samples to be drawn from the dataset. The default is N = 5,
scale	logical. Whether to use scaled data in kmeans.
trace	numberic. Indicating a trace level for diagnostic output during the algorithm
verbose	logical. Whether to print calculation progress.
...	Parameters passing to clara function

Value

an FSPY object with clara.id in meta.data

See Also

clara

Examples

if (FALSE) {
fspy <- runClara(fspy, k = 25, verbose = TRUE)
}

JhuangLab/flowSpy documentation built on July 15, 2020, 8:31 a.m.