Run a supervised LSI (SLSI) dimensionality reduction supervised by a cell-cell kernel. SLSI is used to capture a linear transformation of peaks that maximizes its dependency to the given cell-cell kernel.
RunSLSI(object, ...)
# S3 method for default
RunSLSI(
object,
assay = NULL,
n = 50,
reduction.key = "SLSI_",
graph = NULL,
verbose = TRUE,
seed.use = 42,
...
)
# S3 method for Assay
RunSLSI(
object,
assay = NULL,
features = NULL,
n = 50,
reduction.key = "SLSI_",
graph = NULL,
verbose = TRUE,
seed.use = 42,
...
)
# S3 method for Seurat
RunSLSI(
object,
assay = NULL,
features = NULL,
n = 50,
reduction.name = "slsi",
reduction.key = "SLSI_",
graph = NULL,
verbose = TRUE,
seed.use = 42,
...
)An object
Arguments passed to IRLBA irlba
Name of Assay SLSI is being run on
Total Number of SLSI components to compute and store
dimensional reduction key, specifies the string before the number for the dimension names
Graph used supervised by SLSI
Display messages
Set a random seed. Setting NULL will not set a seed.
Features to compute SLSI on. If NULL, SLSI will be run using the variable features for the Assay.
dimensional reduction name
Returns Seurat object with the SLSI calculation stored in the reductions slot