HTOHeatmap.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/visualization.R
\name{HTOHeatmap}
\alias{HTOHeatmap}
\title{Hashtag oligo heatmap}
\usage{
HTOHeatmap(
  object,
  assay = "HTO",
  classification = paste0(assay, "_classification"),
  global.classification = paste0(assay, "_classification.global"),
  ncells = 5000,
  singlet.names = NULL,
  raster = TRUE
)
}
\arguments{
\item{object}{Seurat object. Assumes that the hash tag oligo (HTO) data has been added and normalized, and demultiplexing has been run with HTODemux().}

\item{assay}{Hashtag assay name.}

\item{classification}{The naming for metadata column with classification result from HTODemux().}

\item{global.classification}{The slot for metadata column specifying a cell as singlet/doublet/negative.}

\item{ncells}{Number of cells to plot. Default is to choose 5000 cells by random subsampling, to avoid having to draw exceptionally large heatmaps.}

\item{singlet.names}{Namings for the singlets. Default is to use the same names as HTOs.}

\item{raster}{If true, plot with geom_raster, else use geom_tile. geom_raster may look blurry on
some viewing applications such as Preview due to how the raster is interpolated. Set this to FALSE
if you are encountering that issue (note that plots may take longer to produce/render).}
}
\value{
Returns a ggplot2 plot object.
}
\description{
Draws a heatmap of hashtag oligo signals across singlets/doublets/negative cells. Allows for the visualization of HTO demultiplexing results.
}
\examples{
\dontrun{
object <- HTODemux(object)
HTOHeatmap(object)
}

}
\seealso{
\code{\link{HTODemux}}
}