Exprmclust {DIscBIO} | R Documentation |
Performing Model-based clustering on expression values
Description
this function first uses principal component analysis (PCA) to reduce dimensionality of original data. It then performs model-based clustering on the transformed expression values.
Usage
Exprmclust(
object,
K = 3,
modelNames = "VVV",
reduce = TRUE,
cluster = NULL,
quiet = FALSE
)
## S4 method for signature 'DISCBIO'
Exprmclust(
object,
K = 3,
modelNames = "VVV",
reduce = TRUE,
cluster = NULL,
quiet = FALSE
)
## S4 method for signature 'data.frame'
Exprmclust(
object,
K = 3,
modelNames = "VVV",
reduce = TRUE,
cluster = NULL,
quiet = FALSE
)
Arguments
object |
|
K |
An integer vector specifying all possible cluster numbers. Default is 3. |
modelNames |
model to be used in model-based clustering. By default "ellipsoidal, varying volume, shape, and orientation" is used. |
reduce |
A logical vector that allows performing the PCA on the expression data. Default is TRUE. |
cluster |
A vector showing the ID of cells in the clusters. |
quiet |
if 'TRUE', suppresses intermediary output |
Value
If 'object' is of class DISCBIO, the output is the same object with the MBclusters slot filled. If the 'object' is a data frame, the function returns a named list containing the four objects that together correspond to the contents of the MBclusters slot.