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[Experimental]

An alternative to phyloseq::plot_bar() function.

Usage

plot_tax_pq(
  physeq,
  fact = NULL,
  merge_sample_by = NULL,
  type = "nb_seq",
  taxa_fill = "Order",
  print_values = TRUE,
  color_border = "lightgrey",
  linewidth = 0.1,
  prop_print_value = 0.01,
  nb_print_value = NULL,
  add_info = TRUE,
  na_remove = TRUE,
  clean_pq = TRUE
)

Arguments

physeq

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

fact

(required) Name of the factor to cluster samples by modalities. Need to be in physeq@sam_data.

merge_sample_by

a vector to determine which samples to merge using the merge_samples2() function. Need to be in physeq@sam_data

type

If "nb_seq" (default), the number of sequences is used in plot. If "nb_asv", the number of ASV is plotted. If both, return a list of two plots, one for nbSeq and one for ASV.

taxa_fill

(default: 'Order'): Name of the taxonomic rank of interest

print_values

(logical, default TRUE): Do we print some values on plot?

color_border

color for the border

linewidth

The line width of geom_bar

prop_print_value

minimal proportion to print value (default 0.01)

nb_print_value

number of higher values to print (replace prop_print_value if both are set).

add_info

(logical, default TRUE) Do we add title and subtitle with information about the total number of sequences and the number of samples per modality.

na_remove

(logical, default TRUE) if TRUE remove all the samples with NA in the split_by variable of the physeq@sam_data slot

clean_pq

(logical) If set to TRUE, empty samples are discarded after subsetting ASV

Value

A ggplot2 graphic

Author

Adrien Taudière

Examples

data(data_fungi_sp_known)
plot_tax_pq(data_fungi_sp_known,
  "Time",
  merge_sample_by = "Time",
  taxa_fill = "Class"
)
#> 23 were discarded due to NA in variables present in formula.
#> Cleaning suppress 3 taxa and 1 samples.

# \donttest{
plot_tax_pq(data_fungi_sp_known,
  "Height",
  merge_sample_by = "Height",
  taxa_fill = "Class",
  na_remove = TRUE,
  color_border = rgb(0, 0, 0, 0)
)
#> 54 were discarded due to NA in variables present in formula.
#> Cleaning suppress 52 taxa and 1 samples.


plot_tax_pq(data_fungi_sp_known,
  "Height",
  merge_sample_by = "Height",
  taxa_fill = "Class",
  na_remove = FALSE,
  clean_pq = FALSE
)
#> Warning: `group` has missing values; corresponding samples will be dropped

# }