Cell state activity inference from single cell data

Calculate secreted protein signaling activity of cell states from single cell RNA-Sequencing data.

Usage

SecAct.activity.inference.scRNAseq(
  inputProfile,
  cellType_meta,
  sigMatrix = "SecAct",
  is.singleCellLevel = FALSE,
  is.group.sig = TRUE,
  is.group.cor = 0.9,
  lambda = 5e+05,
  nrand = 1000,
  sigFilter = FALSE
)

Arguments

inputProfile

A Seurat object.

cellType_meta

Column name in meta data that includes cell-type annotations.

sigMatrix

Secreted protein signature matrix.

is.singleCellLevel

A logical indicating whether to calculate for each single cell.

is.group.sig

A logical indicating whether to group similar signatures.

is.group.cor

Correlation cutoff of similar signatures.

lambda

Penalty factor in the ridge regression.

nrand

Number of randomization in the permutation test, with a default value 1000.

sigFilter

A logical indicating whether filter the secreted protein signatures with the genes from inputProfile.

Value

A Seurat object.