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, ... )
| object | An object |
|---|---|
| ... | Arguments passed to IRLBA irlba |
| assay | Name of Assay SLSI is being run on |
| n | Total Number of SLSI components to compute and store |
| reduction.key | dimensional reduction key, specifies the string before the number for the dimension names |
| graph | Graph used supervised by SLSI |
| verbose | Display messages |
| seed.use | Set a random seed. Setting NULL will not set a seed. |
| features | Features to compute SLSI on. If NULL, SLSI will be run using the variable features for the Assay. |
| reduction.name | dimensional reduction name |
Returns Seurat object with the SLSI calculation stored in the reductions slot