Generates a violin plot of spatial metabolic intensity data

Usage

MZVlnPlot(
  seurat.obj,
  group.by = NULL,
  mzs = NULL,
  assay = "Spatial",
  slot = "counts",
  title = "VlnPlot",
  x.lab = "var",
  y.lab = "intensity",
  show.points = TRUE,
  bottom.cutoff = NULL,
  top.cutoff = NULL,
  log.data = FALSE,
  cols = NULL,
  verbose = FALSE
)

Arguments

seurat.obj: Seurat object containing the metabolomic intensity data.
group.by: Character string specifying the meta.data column to group by (default = NULL).
mzs: Vector of characters defining which features (m/z's) to label on the plot. If NULL no features will be labeled (default = NULL).
assay: Character string defining the name of the Seurat Object assay to pull the corresponding intensity data from (default = "Spatial").
slot: Character string defining the name of the slot within the Seurat Object assay to pull the corresponding intensity data from (default = "counts").
title: Character string of the plot title (default = "VlnPlot").
x.lab: Character string of the x-axis label (default = "var").
y.lab: Character string of the y-axis label (default = "intensity").
show.points: Boolean value describing whether to show each individual data point (default = TRUE).
bottom.cutoff: Numeric value defining the percent of data to exclude for the lower end of the distribution. A bottom.cutoff = 0.05 will remove the bottom 5% of data point (default = NULL).
top.cutoff: Numeric value defining the percent of data to exclude for the upper end of the distribution. A top.cutoff = 0.05 will remove the top 5% of data point (default = NULL).
log.data: Boolean value indicating whether to log transform the y-axis values (default = FALSE).
cols: Vector of strings defining the colours to use for plotting. This vector should match the length of unique groups (default = NULL).
verbose: Boolean indicating whether to show the message. If TRUE the message will be show, else the message will be suppressed (default = FALSE).

Examples

# MZVlnPlot(SeuratObj, group.by = "sample",  bottom.cutoff = 0.05)