plotDiversityTest: Plot the results of diversity testing

In alakazam: Immunoglobulin Clonal Lineage and Diversity Analysis

Plot the results of diversity testing

Description

plotDiversityTest plots summary data for a DiversityCurve object with mean and a line range indicating plus/minus one standard deviation.

Usage

plotDiversityTest(
  data,
  q,
  colors = NULL,
  main_title = "Diversity",
  legend_title = "Group",
  log_d = FALSE,
  annotate = c("none", "depth"),
  silent = FALSE,
  ...
)

Arguments

data	DiversityCurve object returned by alphaDiversity.
q	diversity order to plot the test for.
colors	named character vector whose names are values in the group column of the data slot of data, and whose values are colors to assign to those group names.
main_title	string specifying the plot title.
legend_title	string specifying the legend title.
log_d	if TRUE then plot the diversity scores D on a log scale; if FALSE plot on a linear scale.
annotate	string defining whether to added values to the group labels of the legend. When "none" (default) is specified no annotations are added. Specifying ("depth") adds sequence counts to the labels.
silent	if TRUE do not draw the plot and just return the ggplot2 object; if FALSE draw the plot.
...	additional arguments to pass to ggplot2::theme.

Value

A ggplot object defining the plot.

See Also

See alphaDiversity for generating input. Plotting is performed with ggplot.

Examples

# Calculate diversity
div <- alphaDiversity(ExampleDb, group="sample_id", min_q=0, max_q=2, step_q=1, nboot=100)

# Plot results at q=0 (equivalent to species richness)
plotDiversityTest(div, 0, legend_title="Sample")

# Plot results at q=2 (equivalent to Simpson's index)
plotDiversityTest(div, q=2, legend_title="Sample")

alakazam documentation built on Sept. 30, 2023, 9:07 a.m.