findVariableFeatures_wfilters: Find variable features

In GeneNMF: Non-Negative Matrix Factorization for Single-Cell Omics

Find variable features

Description

Select highly variable genes (HVG) from an expression matrix. Genes from a blocklist (e.g. cell cycling genes, mitochondrial genes) can be excluded from the list of variable genes, as well as genes with very low or very high average expression

Usage

findVariableFeatures_wfilters(
  obj,
  nfeatures = 2000,
  genesBlockList = NULL,
  min.exp = 0.01,
  max.exp = 3
)

Arguments

obj	A Seurat object containing an expression matrix
nfeatures	Number of top HVG to be returned
genesBlockList	Optionally takes a vector or list of vectors of gene names. These genes will be ignored for HVG detection. This is useful to mitigate effect of genes associated with technical artifacts or batch effects (e.g. mitochondrial, heat-shock response). If set to 'NULL' no genes will be excluded
min.exp	Minimum average normalized expression for HVG. If lower, the gene will be excluded
max.exp	Maximum average normalized expression for HVG. If higher, the gene will be excluded

Value

Returns the input Seurat object obj with the calculated highly variable features accessible through VariableFeatures(obj)

Examples

data(sampleObj)
sampleObj <- findVariableFeatures_wfilters(sampleObj, nfeatures=100)

GeneNMF documentation built on April 4, 2025, 4:39 a.m.