Seurat (version 5.0.3)

TopFeatures: Find features with highest scores for a given dimensional reduction technique

Description

Return a list of features with the strongest contribution to a set of components

Usage

TopFeatures(
  object,
  dim = 1,
  nfeatures = 20,
  projected = FALSE,
  balanced = FALSE,
  ...
)

Value

Returns a vector of features

Arguments

object

DimReduc object

dim

Dimension to use

nfeatures

Number of features to return

projected

Use the projected feature loadings

balanced

Return an equal number of features with both + and - scores.

...

Extra parameters passed to Loadings

Examples

data("pbmc_small")
pbmc_small
TopFeatures(object = pbmc_small[["pca"]], dim = 1)
# After projection:
TopFeatures(object = pbmc_small[["pca"]], dim = 1,  projected = TRUE)