Run scGate using Rhesus macaque models

Helper function to run scGate, iterating the provided models and generating a consensus field

Usage

RunScGateWithRhesusModels(
  seuratObj,
  min.cells = 30,
  assay = "RNA",
  pos.thr = 0.13,
  neg.thr = 0.13,
  ncores = 1,
  genes.blacklist = "default",
  dropAmbiguousConsensusValues = FALSE
)

Arguments

seuratObj

The seurat object

min.cells

Passed directly to scGate::scGate. Stop iterating if fewer than this number of cells is left

assay

Passed directly to scGate::scGate. Seurat assay to use

pos.thr

Passed directly to scGate::scGate. Minimum UCell score value for positive signatures

neg.thr

Passed directly to scGate::scGate. Maximum UCell score value for negative signatures

ncores

Passed directly to scGate::scGate. Number of processors for parallel processing (requires future.apply)

genes.blacklist

Passed directly to scGate::scGate. Genes blacklisted from variable features. The default loads the list of genes in scGate::genes.blacklist.default; you may deactivate blacklisting by setting genes.blacklist=NULL

dropAmbiguousConsensusValues

If true, any consensus calls that are ambiguous will be set to NA