Partition the Variation of a phyloseq object with rarefaction permutations

This is an extension of the function var_par_pq(). The main addition is the computation of nperm permutations with rarefaction even depth by sample. The return object

Usage

var_par_rarperm_pq(
  physeq,
  list_component,
  dist_method = "bray",
  nperm = 99,
  quantile_prob = 0.975,
  dbrda_computation = FALSE,
  dbrda_signif_pval = 0.05,
  sample.size = min(sample_sums(physeq)),
  verbose = FALSE,
  progress_bar = TRUE
)

Arguments

physeq: (required): a phyloseq-class object obtained using the phyloseq package.
list_component: (required) A named list of 2, 3 or four vectors with names from the @sam_data slot.
dist_method: (default "bray") the distance used. See phyloseq::distance() for all available distances or run phyloseq::distanceMethodList(). For aitchison and robust.aitchison distance, vegan::vegdist() function is directly used.#' @param fill_bg
nperm: (int) The number of permutations to perform.
quantile_prob: (float, [0:1]) the value to compute the quantile. Minimum quantile is compute using 1-quantile_prob.
dbrda_computation: (logical) Do dbrda computations are runned for each individual component (each name of the list component) ?
dbrda_signif_pval: (float, [0:1]) The value under which the dbrda is considered significant.
sample.size: (int) A single integer value equal to the number of reads being simulated, also known as the depth. See phyloseq::rarefy_even_depth().
verbose: (logical). If TRUE, print additional informations.
progress_bar: (logical, default TRUE) Do we print progress during the calculation?

Value

A list of class varpart with additional information in the $part$indfract part. Adj.R.square is the mean across permutation. Adj.R.squared_quantil_min and Adj.R.squared_quantil_max represent the quantile values of adjuste R squared

Details

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

Author

Adrien Taudière

Examples

# \donttest{
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
  )
}
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# }