PerformCellInference: Performs SingleR inference

In j-andrews7/EZscRNA: Simple Convenience Functions for High-Level scRNA-Seq Analysis

Description

PerformCellInference performs correlation-based cell type inference using a reference dataset via SingleR.

Usage

PerformCellInference(scrna, sce, method, refset, labels, outdir,
  clusts.name = "NoClusters", clusts = NULL, singler.params = NULL)

Arguments

scrna	Seurat object.
sce	SingleCellExperiment object.
method	String or character vector specifying whether annotation should be applied to each single cell method = "single" or aggregated into cluster-level profiles method = "cluster" prior to annotation. If both are supplied, predictions will be performed for both methods.
refset	Reference dataset as SummarizedExperiment.
labels	String indicating whether to use broad lineage-based labels labels="label.main" for each reference sample or more fine-grained labels (labels="label.fine".
outdir	Path to output directory for annotation scores, distributions, and heatmap.
clusts.name	String indicating clusters column.
clusts	Vector of cluster assignments for each cell.
singler.params	List of arguments to be passed to SingleR.

Value

A Seurat object with inferred cell type information in the meta.data slot named in refset.labels format. If method = "cluster", the resulting meta.data column will be named in clusters.refset.labels format.

Author(s)

Jared Andrews

j-andrews7/EZscRNA documentation built on Feb. 24, 2020, 10:37 a.m.