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 } # }