Classify_ImmuneCells: Classify Bulk Immune cells

In bimberlabinternal/RIRA_classification: A package for the Rhesus Immune Reference Atlas (RIRA): A multi-tissue single-cell landscape of immune cells

Classify Bulk Immune cells

Description

Runs celltypist using the RIRA bulk immune model to score cells using CellTypist with optimized parameters.

Usage

Classify_ImmuneCells(
  seuratObj,
  assayName = Seurat::DefaultAssay(seuratObj),
  columnPrefix = "RIRA_Immune_v2.",
  maxAllowableClasses = 6,
  minFractionToInclude = 0.01,
  minCellsToRun = 200,
  maxBatchSize = 6e+05,
  retainProbabilityMatrix = FALSE,
  filterDisallowedClasses = TRUE
)

Arguments

seuratObj	The seurat object
assayName	The name of the assay to use. Others will be dropped
columnPrefix	A prefix that will be added to the beginning of the resulting columns, added the [e-mail]
maxAllowableClasses	Celltypist can assign a cell to many classes, creating extremely long labels. Any cell with more than this number of labels will be set to NA
minFractionToInclude	If non-null, any labels with fewer than this fraction of cells will be set to NA.
minCellsToRun	If the input seurat object has fewer than this many cells, NAs will be added for all expected columns and celltypist will not be run.
maxBatchSize	If more than this many cells are in the object, it will be split into batches of this size and run in serial.
retainProbabilityMatrix	If true, the celltypist probability_matrix with per-class probabilities will be stored in meta.data
filterDisallowedClasses	If true, this will run FilterDisallowedClasses() on the output.

bimberlabinternal/RIRA_classification documentation built on April 14, 2025, 5:59 p.m.