Train Celltypist — TrainCellTypist • RIRA

Train celltypist using the data in a seurat object and saves the resulting model

Usage

TrainCellTypist(
  seuratObj,
  labelField,
  modelFile,
  minCellsPerClass = 20,
  assayName = Seurat::DefaultAssay(seuratObj),
  tempFileLocation = NULL,
  dropAmbiguousLabelValues = TRUE,
  excludedClasses = NULL,
  featureInclusionList = NULL,
  featureExclusionList = NULL
)

Arguments

seuratObj: The seurat object
labelField: The field in seuratObj@meta.data holding the labels for training
modelFile: The path to save the model
minCellsPerClass: If provided, any classes (and corresponding cells) with fewer than this many cells will be dropped from the training data
assayName: The name of the assay to use
tempFileLocation: The location where temporary files (like the annData version of the seurat object), will be written.
dropAmbiguousLabelValues: If true, and label value with a comma will be dropped.
excludedClasses: A vector of labels to discard.
featureInclusionList: If provided, the input count matrix will be subset to just these features. If used, Seurat::NormalizeData will be re-run.
featureExclusionList: If provided, the input count matrix will be subset to remove these features. If used, Seurat::NormalizeData will be re-run.