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Estimate diversity metrics from relative abundances

richness_from_abundances_gen.Rd

This function estimate diversity metrics (Observed, Shannon, Inverse Simpson) from the matrix of relative abundances (see get_microbiomes()). It uses multinomial sampling to simulate read counts from abundances, and computes diversity metrics across n_loop in order to obtain robust estimation. This function is particularly useful when selection is based on diversity.

Usage

richness_from_abundances_gen(
  microbiome_matrix,
  size_rmultinom = 10000,
  n_loop = 10,
  plot = T
)

Arguments

microbiome_matrix

A matrix of relative abundances (individuals in rows and OTUs in columns, see get_microbiomes() output).

size_rmultinom

Integer; specifying the total number of object for the multinomial sampling(default: 10000, according to DeruPop.rds dataset).

n_loop

Integer; number of multinomial resampling iterations to perform (default: 10).

plot

Logical; not currently implemented

Value

A data.frameof average diversity metrics (Observed, Shannon, Inverse Simpson) for each sample.

See also

get_microbiomes(), phyloseq::estimate_richness()

Examples

if (FALSE) { # \dontrun{
library(magrittr)
library(purrr)
data("Deru")
ToyData <- Deru
taxa_assign_g <- assign_taxa(founder_object = ToyData)
generations_simu <- holo_simu(h2 = 0.25, b2 = 0.25, founder_object = ToyData,
                               n_clust = taxa_assign_g, n_ind = 500,
                               verbose = FALSE, seed = 1234)
                               
# Extract microbiomes matrix for each generations
microbiomes <- generations_simu[-1] %>% map(get_microbiomes)
 
# Estimate diversity metrics
richness_from_abundances <- microbiomes %>% map(richness_from_abundances_gen, size_rmultinom = 10000) 
## size_rmultinom = 10000 according to DeruPops dataset
} # }