controlled.mean.score: Compute Controlled Activation Score

In asmagen/robustSingleCell: Robust Clustering of Single Cell RNA-Seq Data

Compute Controlled Activation Score

Description

Compute mean gene signatures activation scores while controlling for technically similar genes.

Usage

controlled.mean.score(environment, genes, knn = 10,
  exclude.missing.genes = T, constrain.cell.universe = NA)

Arguments

environment	environment object
genes	gene list upon which to calculate gene signature activate
knn	number of nearest neighbors
exclude.missing.genes	whether to exclude genes with missing values
constrain.cell.universe	binary vector indicating in which subset of cells to calculate the gene signature activation. Default is all cells.

Value

gene signature activation scores per cell

Examples

LCMV1 <- setup_LCMV_example()
exhaustion_markers <- c('Pdcd1', 'Cd244', 'Havcr2', 'Ctla4', 'Cd160', 'Lag3',
'Tigit', 'Cd96')
Exhaustion <- controlled.mean.score(LCMV1, exhaustion_markers)

asmagen/robustSingleCell documentation built on July 30, 2023, 6:48 a.m.