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What is alpha diversity and how is it calculated?

It’s crucial for understanding how diverse or rich your microbiome sample is in terms of different microorganisms. When talking about alpha diversity, we are looking at two things:
  • Species richness - a count of the number of different species present in a sample. It does not take into account the abundance of the species or their relative distributions.
  • Species evenness - a measure of relative abundance of different species that make up the richness.
The input metric for Alpha Diversity is Normalized Reads Frequency, which is the genome-normalized number of reads that reflects the underlying microbiome composition of the community. The aggregation level of the input data for Comparative Analysis has been set to species level.

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Metrics for Alpha Diversity

New to ecology statistics?Read our page on Alpha Diversity Metrics: How to Chose the Right One
The CHAO1 Index is an estimator of species richness that estimates the true number of species in a community based on the abundance pattern of rare species in your sample. Unlike simple species counts, CHAO1 accounts for species that are likely present but were not detected due to insufficient sampling depth.How CHAO1 WorksCHAO1 operates on the capture-recapture principle and specifically uses Singletons (f₁, species observed exactly once in the sample) and Doubletons (f₂, species observed exactly twice in the sample).The estimator assumes that if many species are observed only once or twice, there are likely additional species present that were not captured at all. The more singletons relative to doubletons, the higher the estimated number of unobserved species.

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Mathematical Formula

The CHAO1 estimate is calculated as CHAO1 = S_observed + (f₁²)/(2 × f₂)Where: S_observed = number of species actually observed in the sample, f₁= number of species represented by exactly one read (singletons), and f₂ = number of species represented by exactly two reads (doubletons).

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Why CHAO1 is Valuable for Microbiome Data

CHAO1 is particularly useful for microbiome datasets because sequencing often undersamples rare species due to sequencing depth limitations. Many microbiome samples contain a number of low-abundance species, and CHAO1 provides a more accurate estimate of true community diversity than observed richness alone. It also helps compare samples with different sequencing depths.This estimator does not assume any particular statistical distribution for the total number of organisms in the sample, but rather relies on the empirical pattern of rare species detection to infer total richness.

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Alpha Diversity Statistics: Wilcoxon rank-sum test

How does this test work and what do the results mean?This non-parametric statistical test investigates whether two independent cohorts have significantly different alpha diversity distributions. The null hypothesis is that a randomly selected value from one cohort has an equal chance of being greater or less than a value from another cohort.P-values below 0.05 indicate a significant difference, meaning the cohorts have distinct alpha diversity distributions. A negative test statistic indicates that Cohort 1 has a lower median alpha diversity compared to Cohort 2, while a positive statistic indicates the opposite.Viewing the Test ResultsAbove the alpha diversity charts, the Result Switcher allows viewing results for “ALL” cohorts or only those with “SIGNIFICANT” differences (p<0.05). The default is “NONE.”The Cohort Menu offers additional filtering, enabling selection of specific cohort combinations to display test statistics and p-values. Results can be exported as TSV.Statistical P-values can also be visualized on the boxplot by turning on the add wilcoxon overlay toggle

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Box plots

Users have the option to visualize the alpha diversity distribution using box plot for each sample cohort selected using labels when creating comparative analysis: Wilcoxon rank sum test can also be overlayed on the boxplot chart by turning on the add wilcoxon overlay toggle