scaper: Single Cell Transcriptomics-Level Cytokine Activity Prediction and Estimation

Description

Generates cell-level cytokine activity estimates using relevant information from gene sets constructed with the 'CytoSig' and the 'Reactome' databases and scored using the modified 'Variance-adjusted Mahalanobis (VAM)' framework for single-cell RNA-sequencing (scRNA-seq) data. 'CytoSig' database is described in: Jiang at al., (2021) doi:10.1038/s41592-021-01274-5. 'Reactome' database is described in: Gillespie et al., (2021) doi:10.1093/nar/gkab1028. The 'VAM' method is outlined in: Frost (2020) doi:10.1093/nar/gkaa582.

Author(s)

Maintainer: Azka Javaid azka.javaid.gr@dartmouth.edu

Authors:

• H. Robert Frost hildreth.r.frost@dartmouth.edu

Pipe operator

Description

See magrittr::%>% for details.

Usage

lhs %>% rhs

Arguments

Value

The result of calling rhs(lhs).

CytoSig gene set construction.

Description

Returns the gene set associated with input cytokine(s) from the CytoSig database given manually specified cytokine-specific output csv file(s) under the extdata directory with file name beginning with the specified cytokine (i.e., 'IL6_output.csv') as currently provided for the IL6 cytokine.

Usage

genesetCytoSig(cytokine.eval, file.name)

Arguments

Value

Dataframe consisting of genes and the associated log2 fold change values associated with the specific cytokine(s).

Examples

file.name.cytosig1 <- system.file("extdata", "IL6_output.csv", package = "scaper")
genesetCytoSig(cytokine.eval = "IL6", file.name = file.name.cytosig1) %>% head(10)

Reactome gene set construction.

Description

Returns the gene set consisting of genes on the Reactome pathway hierarchy given input cytokine(s) and specified list of pathway hierarchy xml file(s) with file name beginning with the specified cytokine (i.e., 'IL6_Interleukin6_signaling.xml') as currently provided for the IL6 cytokine.

Usage

genesetReactome(cytokine.eval, file.name)

Arguments

Value

Dataframe consisting of list of genes on the molecular pathway associated with the specified cytokine(s).

Examples

file.name.reactome1 <- system.file("extdata", "IL6_Interleukin6_signaling.xml", 
package = "scaper")
genesetReactome(cytokine.eval = "IL6", file.name = file.name.reactome1) %>% head(10)

Cytokine activity scores for a normalized matrix.

Description

Computes cell-level estimates of cytokine activity for a normalized scRNA-seq count matrix using the SCAPE method. SCAPE activity estimates are computed by scoring weighted genes sets from the CytoSig or Reactome databases using the VAM::vamForCollection() 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

scape(counts.matrix, database = "cytosig", cytokine = "all")

Arguments

Value

A m x p matrix consisting of the cell-level cytokine activity scores for p cytokines.

See Also

genesetCytoSig, genesetReactome

Examples

library(Seurat)
library(SeuratObject)
pbmc_small <- NormalizeData(pbmc_small)
counts.matrix <- as.data.frame(t(as.matrix(pbmc_small@assays$RNA@data)))
CytoSig.score.output <- scape(counts.matrix = counts.matrix, 
database = "cytosig")
head(CytoSig.score.output)[,1:3]
CytoSig.score.output.specific <- scape(counts.matrix = counts.matrix, 
database = "cytosig", cytokine = c("IL4", "IL13"))
head(CytoSig.score.output.specific)

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

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]

Gene set to score for the CytoSig or the Reactome databases.

Description

Returns the names of the cytokines supported by either the CytoSig or the Reactome databases.

Usage

supportedCytokines(database = "cytosig")

Arguments

Value

List of cytokines associated with the CytoSig or the Reactome databases.

Examples

supportedCytokines(database = "cytosig")
supportedCytokines(database = "reactome")