GeneNMF (version 0.8.0)

findVariableFeatures_wfilters: 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
)

Value

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

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

Examples

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