projectReduction: Project dimensionally-reduced features onto UMAP

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

Project dimensionally-reduced features onto UMAP

Description

Project dimensionally-reduced features (e.g., PC, IC) onto UMAP

Usage

projectReduction(
  object,
  reduction = "pca",
  n.components = NA,
  show.n.features = 50,
  pca.min.var.exp = 0.05,
  pca.cum.pca.thresh = 0.8,
  umap.reduction = "umap",
  rel.width = c(2.5, 1),
  size = autoPointSize(ncol(object)),
  ...
)

Arguments

object	Seurat Object
reduction	Character specifying reduction key. Default: "pca"
n.components	Numeric. Number of top components to project.
show.n.features	Numeric. Show top n features alongside projection. Default is 50.
pca.min.var.exp	Threshold for minimum variance explained by principal component.
pca.cum.pca.thresh	Threshold for maximum cumulative variance explained by principal component.
umap.reduction	Character specifying reduction key for umap coordinates.
rel.width	Relative widths of umap and top feature plots. Default: c(2.5,1)
...	additional parameters passed to geom_point(). Generally used to specify point size.

Value

list of ggplot handles

Author(s)

Nicholas Mikolajewicz

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