Run scMalignantFinder cancer cell state scoring — RunscMalignantStates • scop

Score cancer cell state gene sets with scMalignantFinder AUCell utilities and append the resulting activity scores to Seurat metadata.

Usage

RunscMalignantStates(
  srt = NULL,
  adata = NULL,
  h5ad = NULL,
  assay = "RNA",
  layer = "counts",
  cells = NULL,
  gene_sets,
  norm_type = NULL,
  prefix = "scMalignantState_",
  return_seurat = !is.null(srt),
  verbose = TRUE
)

Arguments

srt: A Seurat object.
adata: Optional Python AnnData object.
h5ad: Optional path to an .h5ad file.
assay: Assay used when srt is supplied. Default is "RNA".
layer: Layer used when srt is supplied. Default is "counts".
cells: Optional cells to run. If supplied with srt, results are appended to these cells and other cells receive NA.
gene_sets: Path to a .gmt file containing cancer cell state gene sets, such as Malignant_MPs.Gavish_2023.gmt from the scMalignantFinder resources.
norm_type: Passed to scMalignantFinder. Use TRUE for raw counts that should be library-size normalized; use FALSE for already normalized input. If NULL, defaults to TRUE only for Seurat counts input.
prefix: Optional prefix for output metadata columns. Default preserves the original scMalignantFinder column names.
return_seurat: Whether to return a Seurat object when srt is supplied. If FALSE, returns a data frame of predictions.
verbose: Whether to print the message. Default is TRUE.

Value

A Seurat object with cancer-state AUCell scores, or a data frame when return_seurat = FALSE.

Examples

if (FALSE) {
srt <- RunscMalignantStates(
  srt,
  gene_sets = "path/to/Malignant_MPs.Gavish_2023.gmt"
)
}