This function accepts a matrix, dataframe or a SingleCellExperiment object. For matrices and dataframes, it is assumed that markers are the columns and samples rows.
Usage
runFuseSOM(
data,
markers = NULL,
numClusters = NULL,
assay = NULL,
clusterCol = "clusters",
size = NULL,
verbose = FALSE
)Arguments
- data
a matrix, dataframe, SingleCellExperiment or SpatialExperiment object.
- markers
the markers of interest. If this is not provided, all columns will be used
- numClusters
the number of clusters to be generated from the data
- assay
the assay of interest if SingleCellExperiment object is used
- clusterCol
the name of the column to store the clusters in
- size
the size of the square grid. eg for a 10X10 grid, size = 10
- verbose
should the generation of the Self Organising Map be printed
Value
A list containing the SOM model and the cluster labels if a dataframe or matrix is provided
A SingleCellExperiment object with labels in coldata, and SOM model in metadata if a SingleCellExperiment or SpatialExperiment object is provided
Author
Elijah WIllie ewil3501@uni.sydney.edu.au
Examples
data("risom_dat")
risomMarkers <- c(
"CD45", "SMA", "CK7", "CK5", "VIM", "CD31", "PanKRT", "ECAD"
)
res <- runFuseSOM(
risom_dat,
markers = risomMarkers, numClusters = 23, size = 8
)
#> You have provided a dataset of class data.frame
#> Everything looks good. Now running the FuseSOM algorithm
#> Now Generating the Self Organizing Map Grid
#> You have provided a grid size of:64
#> Now Running the Self Organizing Map Model
#> Now Clustering the Prototypes
#> Now Mapping Clusters to the Original Data
#> The Prototypes have been Clustered and Mapped Successfully
#> The FuseSOM algorithm has completed successfully