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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

The CHAO1 Index is an estimator of species richness, which corrects for species that might be present but not detected in your sample due to low abundance. It considers rare species—those observed only once or twice—to estimate the actual total number of species. Think of it as trying to estimate how many different items could be in your grocery basket, even if some are hidden underneath others.

CHAO1 assumes that the number of organisms identified for a sample has a normal (or “Poisson”) distribution and corrects for variance. It is useful for data sets skewed toward low-abundance calls, as is often the case with microbiome data.

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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 Results

Above 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