dominance | R Documentation |
Calculates the community dominance index.
dominance(x, index = "all", rank = 1, relative = TRUE, aggregate = TRUE)
x |
A species abundance vector, or matrix (taxa/features x samples)
with the absolute count data (no relative abundances), or
|
index |
If the index is given, it will override the other parameters. See the details below for description and references of the standard dominance indices. By default, this function returns the Berger-Parker index, ie relative dominance at rank 1. |
rank |
Optional. The rank of the dominant taxa to consider. |
relative |
Use relative abundances (default: TRUE) |
aggregate |
Aggregate (TRUE; default) the top members or not. If aggregate=TRUE, then the sum of relative abundances is returned. Otherwise the relative abundance is returned for the single taxa with the indicated rank. |
The dominance index gives the abundance of the most abundant species. This has been used also in microbiomics context (Locey & Lennon (2016)). The following indices are provided:
'absolute' This is the most simple variant, giving the absolute abundance of the most abundant species (Magurran & McGill 2011). By default, this refers to the single most dominant species (rank=1) but it is possible to calculate the absolute dominance with rank n based on the abundances of top-n species by tuning the rank argument.
'relative' Relative abundance of the most abundant species. This is with rank=1 by default but can be calculated for other ranks.
'DBP' Berger–Parker index, a special case of relative dominance with rank 1; This also equals the inverse of true diversity of the infinite order.
'DMN' McNaughton’s dominance. This is the sum of the relative abundance of the two most abundant taxa, or a special case of relative dominance with rank 2
'simpson' Simpson's index ($sum(p^2)$) where p are relative abundances has an interpretation as a dominance measure. Also the version ($sum(q * (q-1)) / S(S-1)$) based on absolute abundances q has been proposed by Simpson (1949) but not included here as it is not within [0,1] range, and it is highly correlated with the simpler Simpson dominance. Finally, it is also possible to calculated dominances up to an arbitrary rank by setting the rank argument
'core_abundance' Relative proportion of the core species that exceed detection level 0.2% in over 50% of the samples
'gini' Gini index is calculated with the function
inequality
.
By setting aggregate=FALSE, the abundance for the single n'th most dominant taxa (n=rank) is returned instead the sum of abundances up to that rank (the default).
A vector of dominance indices
Contact: Leo Lahti microbiome-admin@googlegroups.com
Kenneth J. Locey and Jay T. Lennon. Scaling laws predict global microbial diversity. PNAS 2016 113 (21) 5970-5975; doi:10.1073/pnas.1521291113.
Magurran AE, McGill BJ, eds (2011) Biological Diversity: Frontiers in Measurement and Assessment (Oxford Univ Press, Oxford), Vol 12
coverage, core_abundance, rarity, alpha
data(dietswap)
# vector
d <- dominance(abundances(dietswap)[,1], rank=1, relative=TRUE)
# matrix
# d <- dominance(abundances(dietswap), rank=1, relative=TRUE)
# Phyloseq object
# d <- dominance(dietswap, rank=1, relative=TRUE)
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