GetGroupGeneSet: Extract cluster/group gene sets from MCA

In RausellLab/CelliD: Unbiased Extraction of Single Cell gene signatures using Multiple Correspondence Analysis

Extract cluster/group gene sets from MCA

Description

Extract cluster/group gene sets from MCA

Usage

GetGroupGeneSet(X, group.by, reduction, dims, features, n.features)

## S3 method for class 'Seurat'
GetGroupGeneSet(
  X,
  group.by = NULL,
  reduction = "mca",
  dims = seq(50),
  features = NULL,
  n.features = 200
)

## S3 method for class 'SingleCellExperiment'
GetGroupGeneSet(
  X,
  group.by = NULL,
  reduction = "MCA",
  dims = seq(50),
  features = NULL,
  n.features = 200
)

Arguments

X	Seurat or SingleCellExperiment object, alternatively a matrix.
group.by	column name of meta.data (Seurat) or ColData (SingleCellExperiment).
reduction	Which dimensionality reduction to use, must be based on MCA.
dims	A vector of integers indicating which dimensions to use with reduction for distance calculation.
features	A character vector of features name to subset feature coordinates for distance calculation.
n.features	A single integer specifying how many top features will be extracted from ranking.

Value

Distance Matrix between groups (column) and genes (row)

Examples

seuratPbmc <- RunMCA(seuratPbmc, nmcs = 5)
GroupGeneSet <- GetGroupGeneSet(seuratPbmc, dims = 1:5, group.by = "seurat_clusters")

RausellLab/CelliD documentation built on Jan. 12, 2024, 3:44 a.m.