Find and store highly variable genes (HVGs)

Computes per-feature variance on normalized(object), ranks genes by decreasing variance, and stores the top nfeatures gene IDs into the HVGs slot. Returns the updated object.

Usage

FindVariableFeatures(object, nfeatures)

Arguments

object

A geneda object

nfeatures

Number of HVGs to store

Value

Updated geneda object

Examples

data(Snail1KO)
counts <- as.matrix(Snail1KO$rawCounts)
counts <- counts[rowSums(counts >= 10) >= 3, ]
meta <- Snail1KO$metadata
rownames(meta) <- meta$Sample
norm <- log2(t(t(counts) / colSums(counts)) * 1e6 + 1)
obj <- GenEDA(normalized = norm, metadata = meta, counts = counts)
obj <- FindVariableFeatures(obj, nfeatures = 1000)
length(HVGs(obj))
#> [1] 1000