Plot ANCOMBC2 result for phyloseq object

Graphical representation of ANCOMBC2 result.

Usage

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
)

Arguments

physeq

(required): a phyloseq-class object obtained using the phyloseq package.

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_table slot) to color the points

tax_label

The taxonomic level (must be present in tax_table slot) to add label

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)?

Value

A ggplot2 object. If add_marginal_vioplot is TRUE, this is a patchworks of plot made using patchwork::plot_layout().

Details

This function is mainly a wrapper of the work of others. Please make a reference to ANCOMBC::ancombc2() if you use this function.

Author

Adrien Taudière

Examples

# \donttest{
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
  )
}
#> Warning: The group variable has < 3 categories 
#> The multi-group comparisons (global/pairwise/dunnet/trend) will be deactivated
#> Warning: The number of taxa used for estimating sample-specific biases is: 9
#> A large number of taxa (>50) is required for the consistent estimation of biases
#> Obtaining initial estimates ...
#> Estimating sample-specific biases ...
#> Warning: Estimation of sampling fractions failed for the following samples:
#> BT-006-M_S55_MERGED.fastq.gz, C21-NV1-B_S62_MERGED.fastq.gz, CB8-019-H_S70_MERGED.fastq.gz, DY5-004-B_S96_MERGED.fastq.gz, DY5-004-H_S97_MERGED.fastq.gz, J18-004-M_S116_MERGED.fastq.gz, W26-001-B_S165_MERGED.fastq.gz, X24-009-B_S170_MERGED.fastq.gz
#> These samples may have an excessive number of zero values
#> Sensitivity analysis for pseudo-count addition to 0s: ...
#> ANCOM-BC2 primary results ...

# }