findVariableFeatures_wfilters {GeneNMF} | R Documentation |
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)