https://github.com/satijalab/seurat
Tip revision: 49a1be0427f2f26a531eb468ba93eeb18d8a2edb authored by satijalab on 13 December 2019, 20:42:25 UTC
Merge pull request #2416 from satijalab/develop
Merge pull request #2416 from satijalab/develop
Tip revision: 49a1be0
TopFeatures.Rd
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/objects.R
\name{TopFeatures}
\alias{TopFeatures}
\title{Find features with highest scores for a given dimensional reduction technique}
\usage{
TopFeatures(
object,
dim = 1,
nfeatures = 20,
projected = FALSE,
balanced = FALSE,
...
)
}
\arguments{
\item{object}{DimReduc object}
\item{dim}{Dimension to use}
\item{nfeatures}{Number of features to return}
\item{projected}{Use the projected feature loadings}
\item{balanced}{Return an equal number of features with both + and - scores.}
\item{...}{Extra parameters passed to \code{\link{Loadings}}}
}
\value{
Returns a vector of features
}
\description{
Return a list of features with the strongest contribution to a set of components
}
\examples{
pbmc_small
TopFeatures(object = pbmc_small[["pca"]], dim = 1)
# After projection:
TopFeatures(object = pbmc_small[["pca"]], dim = 1, projected = TRUE)
}