plotSeuratGenes: Compute and plot visualizations for marker genes

In compbiomed/singleCellTK: Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data

Compute and plot visualizations for marker genes

Description

Compute and plot visualizations for marker genes

Usage

plotSeuratGenes(
  inSCE,
  useAssay = "seuratNormData",
  plotType,
  features,
  groupVariable,
  reducedDimName = "seuratUMAP",
  splitBy = NULL,
  cols = c("lightgrey", "blue"),
  ncol = 1,
  combine = FALSE
)

Arguments

inSCE	Input SingleCellExperiment object.
useAssay	Specify the name of the assay that will be scaled by this function.
plotType	Specify the type of the plot to compute. Options are limited to "ridge", "violin", "feature", "dot" and "heatmap".
features	Specify the features to compute the plot against.
groupVariable	Specify the column name from the colData slot that should be used as grouping variable.
reducedDimName	saved dimension reduction name in the SingleCellExperiment object. Default seuratUMAP.
splitBy	Specify the column name from the colData slot that should be used to split samples. Default is NULL.
cols	Specify two colors to form a gradient between. Default is c("lightgrey", "blue").
ncol	Visualizations will be adjusted in "ncol" number of columns. Default is 1.
combine	A logical value that indicates if the plots should be combined together into a single plot if TRUE, else if FALSE returns separate ggplot objects for each feature. Only works when plotType parameter is "feature", "violin" or "ridge". For "heatmap" and "dot", plots for all features are always combined into a single plot. Default FALSE.

Value

Plot object

compbiomed/singleCellTK documentation built on Oct. 27, 2024, 3:26 a.m.