Build a sample information tibble from physeq object

Hill numbers are the number of equiprobable species giving the same diversity value as the observed distribution.

Note that contrary to hill_pq(), this function does not take into account for difference in the number of sequences per samples/modalities. You may use rarefy_by_sample = TRUE if the mean number of sequences per samples differs among modalities.

Usage

psmelt_samples_pq(
  physeq,
  hill_scales = c(0, 1, 2),
  filter_zero = TRUE,
  rarefy_by_sample = FALSE,
  taxa_ranks = NULL
)

Arguments

physeq

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

hill_scales

(a vector of integer) The list of q values to compute the hill number H^q. If Null, no hill number are computed. Default value compute the Hill number 0 (Species richness), the Hill number 1 (exponential of Shannon Index) and the Hill number 2 (inverse of Simpson Index).

filter_zero

(logical, default TRUE) Do we filter non present OTU from samples ? For the moment, this has no effect on the result because the dataframe is grouped by samples with abundance summed across OTU.

rarefy_by_sample

(logical, default FALSE) If TRUE, rarefy samples using phyloseq::rarefy_even_depth() function.

taxa_ranks

A vector of taxonomic ranks. For examples c("Family","Genus"). If taxa ranks is not set (default value = NULL), taxonomic information are not present in the resulting tibble.

Value

A tibble with a row for each sample. Columns provide information from sam_data slot as well as hill numbers, Abundance (nb of sequences), and Abundance_log10 (log10(1+Abundance)).

Author

Adrien Taudière

Examples

if (requireNamespace("ggstatsplot")) {
  psm_tib <- psmelt_samples_pq(data_fungi_mini, hill_scales = c(0, 2, 7))
  ggstatsplot::ggbetweenstats(psm_tib, Height, Hill_0)
  ggstatsplot::ggbetweenstats(psm_tib, Height, Hill_7)

  psm_tib_tax <- psmelt_samples_pq(data_fungi_mini, taxa_ranks = c("Class", "Family"))
  ggplot(filter(psm_tib_tax, Abundance > 2000), aes(y = Family, x = Abundance, fill = Time)) +
    geom_bar(stat = "identity") +
    facet_wrap(~Height)
}
#> Joining with `by = join_by(Sample)`
#> Joining with `by = join_by(Sample)`