Plot the alpha diversity using a violin plot. alpha_diversity_plots
generates plots for all alpha diversity measures.
alpha_diversity_plot(obj, measure = "Shannon", group = "TreatmentGroup", select_otu_table = NULL, title = NULL) alpha_diversity_plots(obj, measures = c("Shannon", "GiniSimpson", "InverseSimpson"), group = "TreatmentGroup")
obj | An object to be converted to a Taxmap object with |
---|---|
measure | Select an alpha diversity measure such as Shannon, Fisher, Coverage, GiniSimpson, and InverseSimpson, Default: 'Shannon' |
group | The "TreatmentGroup" or similar grouping or column from your metadata to denote sample groups, Default: 'TreatmentGroup' |
select_otu_table | DEPRECATED. Choose an otu table to analyze, Default: 'otu_proportions' |
title | The title of the plot, Default: NULL |
measures | A list of alpha diversity measures such as Shannon, Fisher, Coverage, GiniSimpson, and InverseSimpson, Default: 'c("Shannon", "GiniSimpson", "InverseSimpson")' |
Returns an alpha diversity plot.
Returns a melted dataframe.
Alpha diversity helps to determine the species richness (the number of different species in a sample) or evenness (similar abundance level).
We prefer to use Shannon
as it is better for data generated using the QIIME pipeline.
alpha_diversity_measures
, diversity
, ggviolin
Other Visualizations: correlation_data
,
correlation_plots
,
correlation_plot
,
heat_tree_parameters
,
heat_tree_plots
,
ordination_plots
,
ordination_plot
, plot_limits
,
save_alpha_diversity_plots
,
save_correlation_plots
,
save_heat_tree_plots
,
save_ordination_plots
,
save_stacked_barplots
,
stacked_barplots
,
stacked_barplot
,
top_coefficients_barplot
Other Visualizations: correlation_data
,
correlation_plots
,
correlation_plot
,
heat_tree_parameters
,
heat_tree_plots
,
ordination_plots
,
ordination_plot
, plot_limits
,
save_alpha_diversity_plots
,
save_correlation_plots
,
save_heat_tree_plots
,
save_ordination_plots
,
save_stacked_barplots
,
stacked_barplots
,
stacked_barplot
,
top_coefficients_barplot
# NOT RUN { if (interactive()) { library(MicrobiomeR) data <- analyzed_silva plot <- alpha_diversity_plot(obj = data, measure = "Shannon") plot } # }