TopFeatures: Find features with highest scores for a given dimensional...

In satijalab/seurat: Tools for Single Cell Genomics

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,
  ...
)

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

Value

Returns a vector of features

Examples

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

satijalab/seurat documentation built on May 11, 2024, 4:04 a.m.