Beta diversity metrics
Beta diversity compares two sample. Usually, this is done by calculating a
number that indicates the similarity or difference between the samples.
Often, but not always, the number is in the range zero to one.
The pair-wise comparisons for a set of samples can be presented in a
In usearch, beta
diversities are always differences measures, not similarity measures, so
increasing values indicate lower similarity and increasing distance. For
distance measures D that ranges between zero and one there is
always an equivalant similarity measure S defined by S = 1 –
D, for example (Jaccard similarity) = 1 – (Jaccard distance).
You can easily convert between distance and similarity measures in a
spreadsheet program such as Excel.
Samples can be clustered to bring
similar samples together, producing a tree, as shown in the figure above. In
usearch, this can be done using the beta_div
command, which automatically generates sample trees, or by using the
cluster_aggd command to cluster a
distance matrix generated by beta_div or by third-party software.