median.heatmap: Heatmap from median expression values

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

Heatmap from median expression values

Description

This function draws a heatmap with median values for each FCS file or for identified cluster with FlowCT::fsom.clustering()

Usage

## S3 method for class 'heatmap'
median(
  fcs.SCE,
  assay.i = "normalized",
  cell.clusters = NULL,
  markers.to.use = "all",
  not.metadata = "filename",
  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().
markers.to.use	Vector with markers to use. Default = "all".
not.metadata	Vector with variable names (from colData(fcs.SCE)) for not including in the heatmap annotation. Default = "filename".
colors	Vector with colors for plotting (if provided, it must be as long as the number of unique elements in the longer metadata field). Default = NULL (i.e., it will choose automatically a vector of colors according to FlowCT::div.colors()).

Examples

## Not run: 
# option 1: general heatmap (by FCS file)
median.heatmap(fcs, not.metadata = c("sample_id", "file_name"))

# option 2: heatmap by SOM-identified clusters
median.heatmap(fcs.SCE = fcs, assay.i = "normalized", cell.clusters = "SOM")

## End(Not run)

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