Generate a Lollipop plot from random forest results

randomf_lollipop_plot(
  table,
  metadata,
  top_n = 15,
  size = 8,
  variable_to_predict,
  col_palette = NULL,
  legend_figure = NULL
)

Arguments

table: Data frame where columns are samples and rows are ASVs or taxa.
metadata: Data frame containing sample metadata.
top_n: Number of top features to plot (default = 15).
size: the size of the point of the lollipop.
variable_to_predict: Variable to predict from the metadata.
col_palette: Custom color palette (optional).
legend_figure: Main title for the figure.

Value

A lollipop plot showing top important features from random forest analysis.

Examples

 randomf_lollipop_plot(table= table_taxa3,
                                  metadata= metadata %>% drop_na(),
                                  variable_to_predict = "SITIO",
                                  col_palette = c("red", "blue", "green"),
                                  top_n = 20,
                                  size = 6)
#> Error: object 'table_taxa3' not found

randomf_lollipop_plot(table = otu_table, 
                     metadata = sample_metadata,
                     variable_to_predict = "season",
                     legend_figure = "Top important features (Random Forest)")
#> Error: object 'otu_table' not found