benchmarkScores: Benchmark Miko scoring pipeline using cluster-specific...

In NMikolajewicz/scMiko: scRNAseq analysis functions. Developed using Seurat framework.

Benchmark Miko scoring pipeline using cluster-specific markers that had been variably contaminated with random genes.

Description

Differentially-expressed gene sets for each cluster are derived and variably contaminated with random genes prior to calculating cluster-specific miko scores for each gene set. The performance of miko scoring is then evaluated on cluster-specific and non-specific gene sets.

Usage

benchmarkScores(
  object,
  geneset.size = 15,
  group_by = "seurat_clusters",
  assay = DefaultAssay(object),
  deg.logFC.threshold = 0.5,
  deg.fdr.threshold = 0.05,
  miko.fdr.threshold = 0.05,
  verbose = T,
  nworkers = 1
)

Arguments

object	Seurat Object
geneset.size	size of differentially-expressed gene sets
group_by	Name of grouping variable in 'object' meta feature. Default is "seurat_clusters".
assay	Name of assay to use
deg.logFC.threshold	logFC threshold for differential-expression analysis. Default is 0.5.
deg.fdr.threshold	FDR threshold for differential-expression analysis. Default is 0.05.
miko.fdr.threshold	FDR threshold for Miko scores. Default is 0.05.
verbose	Print progress. Default is TRUE.
nworkers	Number of workers for parallel implementation. Default is 1.

Value

list of benchmark results.

Author(s)

Nicholas Mikolajewicz

See Also

AddSModuleScore for standardized module scoring, wilcoxauc for differential expression analysis

NMikolajewicz/scMiko documentation built on June 28, 2023, 1:41 p.m.