GetGroupGeneSet: Extract cluster/group gene sets from MCA

In cbl-imagine/cellID: Unbiased Extraction of Single Cell Identity using Multiple Correspondence Analysis

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")

cbl-imagine/cellID documentation built on July 24, 2020, 9:35 p.m.