plot_var_part_pq {MiscMetabar}

Plot the partition the variation of a phyloseq object

Description

Usage

plot_var_part_pq(
  res_varpart,
  cutoff = 0,
  digits = 1,
  digits_quantile = 2,
  fill_bg = c("seagreen3", "mediumpurple", "blue", "orange"),
  show_quantiles = FALSE,
  filter_quantile_zero = TRUE,
  show_dbrda_signif = FALSE,
  show_dbrda_signif_pval = 0.05,
  alpha = 63,
  id.size = 1.2,
  min_prop_pval_signif_dbrda = 0.95
)

Arguments

res_varpart

(required) the result of the functions var_par_pq() or var_par_rarperm_pq()

cutoff

The values below cutoff will not be displayed.

digits

The number of significant digits.

digits_quantile

The number of significant digits for quantile.

fill_bg

Fill colours of ellipses.

show_quantiles

Do quantiles are printed ?

filter_quantile_zero

Do we filter out value with quantile encompassing the zero value?

show_dbrda_signif

Do dbrda significance for each component is printed using *?

show_dbrda_signif_pval

(float, ⁠[0:1]⁠) The value under which the dbrda is considered significant.

alpha

(int, ⁠[0:255]⁠) Transparency of the fill colour.

id.size

A numerical value giving the character expansion factor for the names of circles or ellipses.

min_prop_pval_signif_dbrda

(float, ⁠[0:1]⁠) Only used if using the result of var_par_rarperm_pq() function. The * for dbrda_signif is only add if at least min_prop_pval_signif_dbrda of permutations show significance.

Details

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

Value

A plot

Author(s)

Adrien Taudière

See Also

var_par_rarperm_pq(), var_par_pq()

Examples

if (requireNamespace("vegan")) {
  data_fungi_woNA <- subset_samples(data_fungi, !is.na(Time) & !is.na(Height))
  res_var_9 <- var_par_rarperm_pq(
    data_fungi_woNA,
    list_component = list(
      "Time" = c("Time"),
      "Size" = c("Height", "Diameter")
    ),
    nperm = 9,
    dbrda_computation = TRUE
  )
  res_var_2 <- var_par_rarperm_pq(
    data_fungi_woNA,
    list_component = list(
      "Time" = c("Time"),
      "Size" = c("Height", "Diameter")
    ),
    nperm = 2,
    dbrda_computation = TRUE
  )
  res_var0 <- var_par_pq(data_fungi_woNA,
    list_component = list(
      "Time" = c("Time"),
      "Size" = c("Height", "Diameter")
    ),
    dbrda_computation = TRUE
  )
  plot_var_part_pq(res_var0, digits_quantile = 2, show_dbrda_signif = TRUE)
  plot_var_part_pq(res_var_9,
    digits_quantile = 2, show_quantiles = TRUE,
    show_dbrda_signif = TRUE
  )
  plot_var_part_pq(
    res_var_2,
    digits = 5,
    digits_quantile = 2,
    cutoff = 0,
    show_quantiles = TRUE
  )
}