Models can be loaded into scGate using the syntax:

models.db <- get_scGateDB()
model.Tcell <- models.db$human$generic$Tcell

gated <- scGate(obj, model=model.Tcell)

To use scGate as a multi-classifier, load one of the collections from the DB:

models.db <- get_scGateDB()
models.TME <- models.db$human$TME_HiRes

gated <- scGate(obj, model=models.TME)
table(gated$scGate_multi)

Note: we will tag versions of this DB using the format 'vN.M' (e.g. v1.4). This format is understood by scGate to download specific versions of the DB

For common use cases, there are ready-made model collections available. For example, there is a model collection to classify immune cells in the tumor micro-environment at high resolution:

scGate_models_DB <- get_scGateDB()
scGate_models <- scGate_models_DB$human$TME_HiRes

Model collections available:

• HiTME
  Default model used in the HiTME package. Includes immune cells at high resolution and stromal cells (e.g. fibroblasts).

• PBMC
  Includes immune cells at high resolution, optimized for possible background contamination from lysed blood cells.

• TME_broad
  Classification of stromal cells and immune cells at a broad level.

Changelog for model collections:

• PBMC
• For all cells, monocytes negative levels replaced with MoMacDC negative levels due to better specificity
• Monocytes: Removed NK negative level because some Monocytes also express NKG7
• Monocytes: kept only "myeloid" markers, as SPI1 is most specific for Monocytes