View source: R/beta_div_test.R
| plot_ancombc_pq | R Documentation | 
Graphical representation of ANCOMBC2 result.
plot_ancombc_pq(
  physeq,
  ancombc_res,
  filter_passed = TRUE,
  filter_diff = TRUE,
  min_abs_lfc = 0,
  tax_col = "Genus",
  tax_label = "Species",
  add_marginal_vioplot = TRUE,
  add_label = TRUE,
  add_hline_cut_lfc = NULL
)
| physeq | (required): a  | 
| ancombc_res | (required) the result of the ancombc_pq function For the moment only bimodal factors are possible. | 
| filter_passed | (logical, default TRUE) Do we filter using the column passed_ss? The passed_ss value is TRUE if the taxon passed the sensitivity analysis, i.e., adding different pseudo-counts to 0s would not change the results. | 
| filter_diff | (logical, default TRUE) Do we filter using the column diff? The diff value is TRUE if the taxon is significant (has q less than alpha) | 
| min_abs_lfc | (integer, default 0) Minimum absolute value to filter results based on Log Fold Change. For ex. a value of 1 filter out taxa for which the abundance in a given level of the modalty is not at least the double of the abundance in the other level. | 
| tax_col | The taxonomic level (must be present in  | 
| tax_label | The taxonomic level (must be present in  | 
| add_marginal_vioplot | (logical, default TRUE) Do we add a marginal vioplot representing all the taxa lfc from ancombc_res. | 
| add_label | (logical, default TRUE) Do we add a label? | 
| add_hline_cut_lfc | (logical, default NULL) Do we add two horizontal lines when min_abs_lfc is set (different from zero)? | 
This function is mainly a wrapper of the work of others.
Please make a reference to ANCOMBC::ancombc2() if you
use this function.
A ggplot2 object. If add_marginal_vioplot is TRUE, this is a
patchworks of plot made using patchwork::plot_layout().
Adrien Taudière
## Not run: 
if (requireNamespace("mia")) {
  data_fungi_mini@tax_table <- phyloseq::tax_table(cbind(
    data_fungi_mini@tax_table,
    "taxon" = taxa_names(data_fungi_mini)
  ))
  res_time <- ancombc_pq(
    data_fungi_mini,
    fact = "Time",
    levels_fact = c("0", "15"),
    tax_level = "taxon",
    verbose = TRUE
  )
  plot_ancombc_pq(data_fungi_mini, res_time,
    filter_passed = FALSE,
    tax_label = "Genus", tax_col = "Order"
  )
  plot_ancombc_pq(data_fungi_mini, res_time, tax_col = "Genus")
  plot_ancombc_pq(data_fungi_mini, res_time,
    filter_passed = FALSE,
    filter_diff = FALSE, tax_col = "Family", add_label = FALSE
  )
}
## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.