RunSingleR: Run SingleR For A Seurat Object

In bimberlabinternal/CellMembrane: A package with high-level wrappers and pipelines for single-cell RNA-seq tools

Run SingleR For A Seurat Object

Description

Compute SingleR classification on a Seurat object

Usage

RunSingleR(
  seuratObj = NULL,
  datasets = c("hpca", "blueprint", "dice", "monaco", "immgen"),
  assay = NULL,
  resultTableFile = NULL,
  rawDataFile = NULL,
  minFraction = 0.01,
  showHeatmap = TRUE,
  maxCellsForHeatmap = 20000,
  nThreads = NULL,
  createConsensus = TRUE
)

Arguments

seuratObj	A Seurat object
datasets	One or more datasets to use as a reference. Allowable values are: hpca, blueprint, dice, monaco, and immgen. See celldex package for available datasets.
assay	The assay in the seurat object to use
resultTableFile	If provided, a table of results will be saved here
rawDataFile	If provided, the complete SingleR results will be saved to this file
minFraction	If provided, any labels present with fraction of this or fewer across cells will be converted to Unknown
showHeatmap	If true, heatmaps will be generated showing the SingleR calls
maxCellsForHeatmap	The heatmap will only be plotted if the total cells is below this number
nThreads	If provided, this integer value is passed to SingleR's BPPARAM argument. On windows ths is passed to BiocParallel::SnowParam(). On other OS it is passed to BiocParallel::MulticoreParam()
createConsensus	If true, a pseudo-consensus field will be created from the course labels from all datasets. Labels will be simplified in an attempt to normalize into the categories of Bcells, NK/T_cells and Myeloid.

Value

The modified seurat object

bimberlabinternal/CellMembrane documentation built on Oct. 16, 2024, 6:53 a.m.