Deconvolve malignant fraction with customized scRNAseq data — SpaCET.deconvolution.malignant.customized.scRNAseq • SpaCET

Explore different malignant cell states in tumor ST dataset.

Usage

SpaCET.deconvolution.malignant.customized.scRNAseq(
  SpaCET_obj,
  Malignant = "Malignant",
  sc_counts,
  sc_annotation,
  sc_lineageTree,
  sc_nCellEachLineage = 100,
  coreNo = 6
)

Arguments

SpaCET_obj: A SpaCET object.
Malignant: Indicates the name of malignant cell type in the major lineage layer from the deconvolution results. Default: "Malignant".
sc_counts: Single cell count matrix with gene name (row) x cell ID (column).
sc_annotation: Single cell annotation matrix. This matrix should include two columns, i,e., cellID and cellType. Each row represents a single cell.
sc_lineageTree: Cell lineage tree. This should be organized by using a list, and the name of each element are major lineages while the value of elements are the corresponding sublineages. If a major lineage does not have any sublineages, the value of this major lineage should be itself.
sc_nCellEachLineage: Cell count each lineage. Default: 100. If a cell type is comprised of >100 cells, only 100 cells per cell identity are randomly selected to generate cell type reference.
coreNo: Core number in parallel.

Value

A SpaCET object

Examples

SpaCET_obj <- SpaCET.deconvolution.malignant.customized.scRNAseq(SpaCET_obj, Malignant="Malignant", sc_counts, sc_annotation, sc_lineageTree, sc_nCellEachLineage=100, coreNo=6)