Community structure
Alpha and beta diversity
Diversity metrics are cheap to compute and easy to report, which is exactly why they are so often reported without a question attached. Each metric answers something specific. Two of them are dominated by sequencing depth. And the standard test for group separation cannot, by itself, tell a real difference from a difference in variability.
Alpha diversity — within a sample
| Metric | What it measures | Depth sensitivity | Needs a tree |
|---|---|---|---|
| Observed features | How many distinct ASVs are present. Pure richness | Extreme — sequence deeper, observe more, essentially without limit | no |
| Chao1 | Richness, extrapolated using the count of rare features | High, and the extrapolation is unstable at low depth | no |
| Shannon | Richness weighted by evenness; dominated by mid-abundance taxa | Moderate — saturates far earlier than richness | no |
| Simpson / inverse Simpson | Probability two reads come from different taxa; driven by the dominant few | Low | no |
| Pielou's evenness | Evenness alone, with richness divided out | Low–moderate | no |
| Faith's PD | Total branch length spanned. Richness that counts how different the taxa are | High, like richness | yes |
Report at least one richness-type and one evenness-weighted metric, and say which question each is answering. "Alpha diversity was higher in the treated group" is not a finding until you say whether that means more taxa, or a less dominated community — those have different biology behind them and can move in opposite directions.
The depth problem, and the argument about it
Choosing a depth is choosing how many samples to keep
The real 50-sample run: final depths run from 66,144 to 173,626 reads, median 125,757. Every candidate rarefaction depth trades reads against samples, and the trade is steep in the middle.
Samples retained by rarefaction depth
50 samples, non-chimeric reads. Hover any bar for the exact count.
Reading it: anywhere up to 90,000 costs you three samples. Past 100,000 the curve falls off a cliff — 120,000 costs you nearly two in five. The defensible choice here is around 90,000, and the defensible method is to look at this curve and say why, rather than to accept whatever the tutorial used. Two further points worth making explicit: the samples you drop are not a random subset — they are the ones that sequenced badly, which often correlates with biomass or inhibitor content and therefore with your groups; and a rarefaction depth chosen after seeing which depth gives a significant result is a researcher degree of freedom like any other.
Beta diversity — between samples
| Metric | Uses | Most sensitive to | Pick it when |
|---|---|---|---|
| Jaccard | presence / absence | rare taxa; sequencing depth | you care about membership, not amounts |
| Bray–Curtis | abundances | abundant taxa | the default abundance-weighted choice, no tree needed |
| Unweighted UniFrac | presence / absence + tree | rare and deep-branching lineages | you expect whole clades to be gained or lost |
| Weighted UniFrac | abundances + tree | abundant taxa, discounted by relatedness | you expect shifts in the dominant members |
| Aitchison | CLR-transformed abundances | ratios between taxa | you want a distance that treats the data as compositional |
| Robust Aitchison | CLR with zeros handled by matrix completion | as above, tolerant of sparsity | the table is very sparse, which it usually is |
Running all six and reporting the one that separated is the most common way to get a false positive out of a beta diversity analysis. Pick the metric from the hypothesis — presence-based if you expect taxa to appear or vanish, abundance-based if you expect them to shift — and if you show more than one, show all of them, including the ones that did not separate.