runScranSNN(
inSCE,
useAssay = NULL,
useReducedDim = NULL,
useAltExp = NULL,
altExpAssay = "counts",
altExpRedDim = NULL,
clusterName = "scranSNN_cluster",
k = 10,
nComp = 50,
weightType = c("rank", "number", "jaccard"),
algorithm = c("walktrap", "louvain", "infomap", "fastGreedy", "labelProp",
"leadingEigen")
)
Arguments
inSCE |
A SingleCellExperiment
object. |
useAssay |
A single character , specifying which
assay to perform the clustering algorithm
on. Default NULL . |
useReducedDim |
A single character , specifying which
low-dimension representation (reducedDim )
to perform the clustering algorithm on. Default NULL . |
useAltExp |
A single character , specifying the assay which
altExp to perform the clustering
algorithm on. Default NULL . |
altExpAssay |
A single character , specifying which
assay in the chosen
altExp to work on. Only used when
useAltExp is set. Default "counts" . |
altExpRedDim |
A single character , specifying which
reducedDim within the altExp specified by
useAltExp to use. Only used when useAltExp is set. Default
NULL . |
clusterName |
A single character , specifying the name to store
the cluster label in colData . Default
"scranSNN_cluster" . |
k |
An integer , the number of nearest neighbors used to construct
the graph. Smaller value indicates higher resolution and larger number of
clusters. Default 10 . |
nComp |
An integer , the number of components to use when
useAssay or useAltExp is specified. WON'T work with
useReducedDim . Default 50 . |
weightType |
A single character , that specifies the edge weighing
scheme when constructing the Shared Nearest-Neighbor (SNN) graph. Choose from
"rank" , "number" , "jaccard" . Default "rank" . |
algorithm |
A single character , that specifies the community
detection algorithm to work on the SNN graph. Choose from "walktrap" ,
"louvain" , "infomap" , "fastGreedy" , "labelProp" ,
"leadingEigen" . Default "walktrap" . |
Value
The input SingleCellExperiment
object with factor
cluster labeling updated in
colData(inSCE)[[clusterName]]
.
References
Aaron Lun and et. al., 2016
Examples
#> Thu Oct 28 15:47:28 2021 ... Running 'scran SNN clustering'