exprUMAP: Visualize gene expression on UMAP

In NMikolajewicz/scMiko: scRNAseq analysis functions. Developed using Seurat framework.

Visualize gene expression on UMAP

Description

Visualize gene expression on UMAP. Wrapper for Nebulosa::plot_density() and scMiko::scExpression.UMAP() functions.

Usage

exprUMAP(
  object,
  feature,
  plot.subtitle = NULL,
  do.neb = F,
  title.size = 10,
  slot = "data",
  assay = DefaultAssay(object),
  reduction = "umap",
  size = autoPointSize(ncol(object)),
  scale.color = "tomato",
  ...
)

Arguments

object	Seurat object.
feature	feature name.
plot.subtitle	Plot title.
do.neb	Logical to use Nebulosa::plot_density instead of scMiko::scExpression.UMAP. Default is F.
title.size	Size of plot title. Default is 10.
slot	which slot to pull from? Default is "data".
assay	assay to retrieve data from.
reduction	reduction name. Default is "umap".
size	point size for plots.
scale.color	color of scale. Default is "tomato".
...	additional parameters passed to scExpression.UMAP (do.neb = F) or plot_density (do.neb = T)

Value

ggplot handle

Examples

 gg.plot <-  exprUMAP(object = so, feature = "Prrx1")

NMikolajewicz/scMiko documentation built on June 28, 2023, 1:41 p.m.