plot_ra: Create an ordered relative abundance plot
In cb-42/cbmbtools: R Functions for Facilitating Microbiome Analyses

Description Usage Arguments Value Examples

Create an ordered relative abundance plot

plot_ra(
  df,
  df_obs = NULL,
  taxon = "OTU",
  yvar = "Mean_Perc",
  title = "",
  error_bar = FALSE,
  facet_var = NULL,
  fill = NULL,
  phy_vec = NULL,
  fill_pal = NULL,
  gtxt = FALSE,
  seed = 123
)

`df`	Dataframe containing metadata and taxon (Phylum, Otu, etc) abundance data in 'long' format, e.g. using `gather`. This dataframe is typically the result of processing via `taxon_sort_gather`.
`df_obs`	An optional dataframe containing individual observations, when `df` contains summarized samples. `df_obs` will be used to add a points layer with `geom_jitter`.
`taxon`	Which taxonomic level within `df` (and optionally, `df_obs`) should be plotted? OTU by default.
`yvar`	Variable to use on the y-axis. Defaults to `Mean_Perc`.
`title`	String to use as plot title. Defaults to an empty string.
`error_bar`	Boolean for whether to include an errorbar. If so, `df` should contain a column named SEM with this information.
`facet_var`	Variable to use for faceted plots. By default, no faceting will be used.
`fill`	Optional variable to use for fill color. Common use cases include filling by Phylum, Sample_name, or Sample_type.
`phy_vec`	Optional vector containing the unique Phyla resulting from `load_tax`, likely following trimming. Combined with `fill_pal` this allows for a consistent color scheme across RA plots.
`fill_pal`	An optional user-defined palette for maintaining consistent fill colors across RA plots. Best when combined with `phy_vec`.
`gtxt`	Boolean for whether to include a `geom_text` layer in the plot which will display actual percentages. Not included by default.
`seed`	Integer to be used as a random seed to ensure reproducibility. For example, this would come into play if using `df_obs` which will create a `geom_jitter` layer that adds random noise to points.

A ggplot created based on df and the specified parameters. It can be further modified with additional layers.

plot_ra(mock_df, title = "Cross-Comparison of Mock Control Replicates", yvar = "Percentage",
   facet_var = "Sample", fill = "Phylum", gtxt = T)

plot_ra(samp_df, title = "Exp1 & 2 Stomachs by Treatment, Ordered by Untreated",
   facet_var = "Group", fill = "Phylum", error_bar = T)

plot_ra(df = otu_agg, df_obs = otu_obs, title = "Feces Samples, Ordered by Day 0",
   facet_var = "Day", fill = "Phylum")

plot_ra(df = phy_agg, df_obs = phy_obs, taxon = "Phylum",
   title = "Feces Samples, Aggregated by Phylum, Ordered by Day 0",
   facet_var = "Day", fill = "Phylum", phy_vec = phy_rank$Phylum, fill_pal = phy_pal)