plotCCA: Plot RDA or CCA object

In microbiome/miaViz: Microbiome Analysis Plotting and Visualization

Plot RDA or CCA object

Description

plotRDA and plotCCA create an RDA/CCA plot starting from the output of CCA and RDA functions, two common methods for supervised ordination of microbiome data.

Usage

plotCCA(object, ...)

## S4 method for signature 'SingleCellExperiment'
plotCCA(object, dimred, ...)

## S4 method for signature 'matrix'
plotCCA(object, ...)

plotRDA(object, ...)

## S4 method for signature 'SingleCellExperiment'
plotRDA(
  object,
  dimred,
  add.ellipse = TRUE,
  ellipse.alpha = 0.2,
  ellipse.linewidth = 0.1,
  ellipse.linetype = 1,
  vec.size = 0.5,
  vec.color = vec.colour,
  vec.colour = "black",
  vec.linetype = 1,
  arrow.size = 0.25,
  label.color = label.colour,
  label.colour = "black",
  label.size = 4,
  vec.text = TRUE,
  repel.labels = TRUE,
  sep.group = "—",
  repl.underscore = " ",
  add.significance = TRUE,
  add.expl.var = TRUE,
  add.vectors = TRUE,
  parse.labels = TRUE,
  ...
)

## S4 method for signature 'matrix'
plotRDA(object, ...)

Arguments

object	a TreeSummarizedExperiment or a matrix of weights. The latter is returned as output from calculateRDA.
...	additional parameters for plotting, inherited from plotReducedDim, geom_label and geom_label_repel.
dimred	A string or integer scalar indicating the reduced dimension to plot. This is the output of runRDA and resides in reducedDim(tse, dimred).
add.ellipse	One of c(TRUE, FALSE, "fill", "colour", "color"), indicating whether ellipses should be present, absent, filled or colored. (default: ellipse.fill = TRUE)
ellipse.alpha	Number between 0 and 1 to adjust the opacity of ellipses. (default: ellipse.alpha = 0.2)
ellipse.linewidth	Number specifying the size of ellipses. (default: ellipse.linewidth = 0.1)
ellipse.linetype	Discrete number specifying the style of ellipses. (default: ellipse.linetype = 1)
vec.size	Number specifying the size of vectors. (default: vec.size = 0.5)
vec.color	Alias for vec.colour.
vec.colour	String specifying the colour of vectors. (default: vec.color = "black")
vec.linetype	Discrete number specifying the style of vector lines. (default: vec.linetype = 1)
arrow.size	Number specifying the size of arrows. (defaults: arrow.size = 0.25)
label.color	Alias for label.colour.
label.colour	String specifying the colour of text and labels. (default: label.color = "black")
label.size	Number specifying the size of text and labels. (default: label.size = 4)
vec.text	TRUE or FALSE, should text instead of labels be used to label vectors. (default: vec.text = TRUE)
repel.labels	TRUE or FALSE, should labels be repelled. (default: repel.labels = TRUE)
sep.group	String specifying the separator used in the labels. (default: sep.group = "\U2014")
repl.underscore	String used to replace underscores in the labels. (default: repl.underscore = " ")
add.significance	TRUE or FALSE, should explained variance and p-value appear in the labels. (default: add.significance = TRUE)
add.expl.var	TRUE or FALSE, should explained variance appear on the coordinate axes. (default: add.expl.var = TRUE)
add.vectors	TRUE or FALSE, should vectors appear in the plot. (default: add.vectors = TRUE)
parse.labels	TRUE or FALSE, should labels be parsed. (default: parse.labels = TRUE)

Details

plotRDA and plotCCA create an RDA/CCA plot starting from the output of CCA and RDA functions, two common methods for supervised ordination of microbiome data. Either a TreeSummarizedExperiment or a matrix object is supported as input. When the input is a TreeSummarizedExperiment, this should contain the output of runRDA in the reducedDim slot and the argument dimred needs to be defined. When the input is a matrix, this should be returned as output from calculateRDA. However, the first method is recommended because it provides the option to adjust aesthetics to the colData variables through the arguments inherited from plotReducedDim.

Value

A ggplot2 object

Examples

# Load dataset
library(miaViz)
data("enterotype", package = "mia")
tse <- enterotype
 
# Run RDA and store results into TreeSE
tse <- runRDA(tse,
              formula = assay ~ ClinicalStatus + Gender + Age,
              FUN = vegan::vegdist,
              distance = "bray",
              na.action = na.exclude)
               
# Create RDA plot coloured by variable
plotRDA(tse, "RDA",
        colour_by = "ClinicalStatus")
 
# Create RDA plot with empty ellipses
plotRDA(tse, "RDA",
        colour_by = "ClinicalStatus",
        add.ellipse = "colour")
 
# Create RDA plot with text encased in labels
plotRDA(tse, "RDA",
        colour_by = "ClinicalStatus",
        vec.text = FALSE)
 
# Create RDA plot without repelling text
plotRDA(tse, "RDA",
        colour_by = "ClinicalStatus",
        repel.labels = FALSE)
 
# Create RDA plot without vectors
plotRDA(tse, "RDA",
        colour_by = "ClinicalStatus",
        add.vectors = FALSE)
 
# Calculate RDA as a separate object
rda_mat <- calculateRDA(tse,
                        formula = assay ~ ClinicalStatus + Gender + Age,
                        FUN = vegan::vegdist,
                        distance = "bray",
                        na.action = na.exclude)
 
# Create RDA plot from RDA matrix
plotRDA(rda_mat)

microbiome/miaViz documentation built on April 21, 2024, 8:45 a.m.