What is alpha diversity?

Alpha diversity is a fundamental concept in microbiome analysis, measuring the variety of species within a single sample. 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.

Measures for evenness and 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.

CHAO1 index

This 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.

Shannon

This metric not only accounts for how many species are present but also for how evenly they are distributed. Imagine you have 10 different types of fruits, but if 9 of them are apples and only one is an orange. Therefore, your diversity is low. The Shannon Index balances richness (the number of species) with evenness (how evenly species are represented).

The Shannon index summarizes the diversity in the population while assuming all species are represented in a sample and they are randomly sampled. The Shannon index increases as both the richness and evenness of the community increase.

Simpson

The Simpson diversity index is used to calculate a measure of diversity taking into account the number of taxa as well as the abundance. It is similar to the Shannon Index, but this metric gives more weight to the most abundant species. If one type of microorganism dominates your sample, the Simpson Index will show lower diversity. It focuses more on how dominance affects overall diversity in the sample. This also means a few rare species with only a few representatives will not affect the diversity of the sample.

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

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Statistics: Wilcoxon rank sum test statistics

How does this test work and what do the results mean?

This nonparametric statistical test can be used to investigate whether two independent cohorts consist of samples that were selected from populations having the same alpha diversity distribution. The null hypothesis thereby is that the probability that a randomly selected value from one cohort is less than a randomly selected value from a second cohort is equal to the probability of being greater.

P-values below e.g. 0.05 suggest that the null hypothesis can be rejected, confirming that the samples of two cohorts are selected from populations with different alpha diversity distributions.

Test results are shown in table listing the test statistic and p-value for the different possible cohort combinations. A negative (positive) test statistic for a cohort pair Cohort 1 ↔︎ Cohort 2 thereby means that the median alpha diversity of Cohort 1 is lower (higher) than the median alpha diversity for Cohort

Viewing the test results

Above and to the right of the alpha diversity charts you can find a Result Switcher and a Cohort Menu.

The Result Switcher allows you to view test results/p-values of either "ALL" cohorts or "SIGNIFICANT" comparisons (p<0.05). NONE setting is selected by default.

The Cohort Menu to the right of the Result Switcher offers another way to filter the displayed cohort combinations. A pulldown menu lists all possible cohort combinations. Selecting checkboxes for the cohort pairs of interest will reduce the rows with test statistics and p-values in the table accordingly.
It is possible to export the test results to TSV.

Wilcoxon rank sum test can also be visualized on the boxplot by turning on the add wilcoxon overlay toggle