GetCellGeneRanking: Ranking Extraction

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

Description

Intermediate function for ranking extraction feom Cell Gene Distance Matrix

Usage

GetCellGeneRanking(X, reduction, dims, features, cells)

## S3 method for class 'Seurat'
GetCellGeneRanking(X, reduction = "mca",
  dims = seq(50), features = NULL, cells = NULL)

## S3 method for class 'SingleCellExperiment'
GetCellGeneRanking(X, reduction = "MCA",
  dims = seq(50), features = NULL, cells = NULL)

Arguments

X	Seurat or SingleCell Experiment Object
reduction	Which dimensionality reduction to use, must be based on MCA.
dims	A vector of integers indicating which dimensions to use with reduction embeddings and loadings for distance calculation.
features	Character vector of feature names to subset feature coordinates. If not specified will take all features available from specified reduction Loadings
cells	Character vector of cell names to subset cell coordinates. If not specified will take all features available from specified reduction Embeddigns.

Value

A cell named list of gene rankings ordererd by distances from shortest (most specfic) to farthest (less specific)

Examples

## Not run: 
seuratPbmc <- RunMCA(seuratPbmc, nmcs = 5)

## End(Not run)

cbl-imagine/CellID documentation built on July 22, 2020, 7:18 p.m.