barplot.cell.pops: Stacked barplot with cell clusters

In jgarces02/FlowCT: A semi-automated workflow for deconvolution of immunophenotypic data and objective reporting on large datasets

Stacked barplot with cell clusters

Description

This function calculates cluster proportions (or raw counts) for each identified cluster and plot them on a stacked barplot.

Usage

## S3 method for class 'cell.pops'
barplot(
  fcs.SCE,
  assay.i = "normalized",
  cell.clusters,
  plot = T,
  count.by,
  facet.by = NULL,
  return.mode,
  colors = NULL
)

Arguments

fcs.SCE	A fcs.SCE object generated through FlowCT::fcs.SCE().
assay.i	Name of matrix stored in the fcs.SCE object from which calculate correlation. Default = "normalized".
cell.clusters	Name of column containing clusters identified through FlowCT::clustering.flow().
plot	Logical indicating whether plotting stacked barplot. Default = TRUE.
count.by	Variable name (from colData(fcs.SCE)) for calculating proportions (or counts) and drawing the x-axis in the stacked bar plotting.
facet.by	Variable name (from colData(fcs.SCE)) for splitting the stacked bar plotting. Default = NULL.
return.mode	String for specifying if final resuls should be proportions ("percentage") or raw counts ("counts"). Default = NULL.
colors	Vector with colors for plotting. Default = NULL (i.e., it will choose automatically a vector of colors according to FlowCT::div.colors()).

Examples

## Not run: 
prop_table <- barplot.cell.pops(fcs.SCE = fcs, cell.clusters = "SOM_named", 
    count.by = "sample_id", facet.by = "condition", 
    return.mode = "percentage")
counts_table <- barplot.cell.pops(fcs.SCE = fcs, cell.clusters = "SOM_named", 
    count.by = "condition", return.mode = "counts")

## End(Not run)

jgarces02/FlowCT documentation built on March 28, 2023, 12:42 p.m.