scapeForSeurat {scaper} | R Documentation |
Cytokine activity scores for a Seurat matrix.
Description
Computes cell-level estimates of cytokine activity for a scRNA-seq Seurat
count matrix using the scapeForSeurat method. SCAPE activity estimates are computed by scoring weighted gene
sets from the CytoSig or Reactome databases using the Variance-adjusted Mahalanobis (VAM) method
as implemented in the VAM::vamForSeurat()
function. Individual gene sets for subsequent scoring can be reconstructed using
the genesetCytoSig
and the genesetReactome
functions
for the CytoSig and the Reactome database, respectively.
Usage
scapeForSeurat(
seurat.object,
database = "cytosig",
cytokine = "all",
normalize = TRUE
)
Arguments
seurat.object |
Seurat counts matrix. |
database |
Database used for gene set construction and set scoring.
|
cytokine |
Vector of cytokine names to score for activity. The default value of "all"
will score all 41 cytokines supported by CytoSig or 31 supported by Reactome. Please see
function |
normalize |
Boolean indicator for whether normalization should be performed before performing gene set scoring. |
Value
Seurat object consisting of cell-level cytokine activity scores returned as a separate assay (scape for scoring via the CytoSig database and VAMcdf for scoring via the Reactome database).
See Also
genesetCytoSig
, genesetReactome
, scape
Examples
library(SeuratObject)
CytoSig.score.output.all <- scapeForSeurat(seurat.object = pbmc_small,
database = "cytosig", cytokine = "all", normalize=TRUE)
(as.data.frame(CytoSig.score.output.all@assays$scape@data))[1:6,1:3]
CytoSig.score.output.specific <- scapeForSeurat(seurat.object = pbmc_small,
database = "cytosig", cytokine = c("IL4", "IL13"), normalize=TRUE)
(as.data.frame(CytoSig.score.output.specific@assays$scape@data))[,1:3]