Perform KMeans clustering on a
SingleCellExperiment
object, with
kmeans
.
runKMeans(
inSCE,
useReducedDim = "PCA",
clusterName = "KMeans_cluster",
nCenters,
nIter = 10,
nStart = 1,
seed = 12345,
algorithm = c("Hartigan-Wong", "Lloyd", "MacQueen")
)
A SingleCellExperiment
object.
A single character
, specifying which
low-dimension representation to perform the clustering algorithm on. Default
"PCA"
.
A single character
, specifying the name to store
the cluster label in colData
. Default
"scranSNN_cluster"
.
An integer
, the number of centroids (clusters).
An integer
, the maximum number of iterations allowed.
Default 10
.
An integer
, the number of random sets to choose. Default
1
.
An integer
. The seed for the random number generator.
Default 12345
.
A single character
. Choose from
"Hartigan-Wong"
, "Lloyd"
, "MacQueen"
. May be
abbreviated. Default "Hartigan-Wong"
.
The input SingleCellExperiment
object with factor
cluster labeling updated in
colData(inSCE)[[clusterName]]
.
data("mouseBrainSubsetSCE")
mouseBrainSubsetSCE <- runKMeans(mouseBrainSubsetSCE,
useReducedDim = "PCA_logcounts",
nCenters = 2)
#> Thu Apr 28 11:28:33 2022 ... Running 'KMeans clustering'