When investigating the composition of microbial communities, researchers often need to calculate and visualize the diversity within and between samples, often referred to respectively as the alpha and beta diversity of samples. Based on feedback from our users, we have added several new data visualization options for microbial diversity in the latest release of CLC Microbial Genomics Module (version 4.5), which are described in more detail below.
With QIAGEN’s CLC Microbial Genomics Module, we provide a number of different metrics for estimating the alpha diversity, including Total Number of OTUs, Chao 1, Simpson’s index, Shannon entropy, and the phylogenetic diversity. The choice of index for an analysis often depends on the underlying experiments and the dataset itself, but often a resulting alpha diversity estimate for a single or multiple samples is visualized with line graph similar to a receiver operator curve. Based on feedback from our users, we have included in the latest release of CLC Microbial Genomics Module (version 4.5) the ability to also represent alpha diversity of a sample using box plots. This new functionality has been integrated into the existing tool for calculating alpha diversity, and the box plots will be generated automatically when running the tool Alpha Diversity.
In the examples below, we used the same data from our recent white paper on the microbial diversity in a polar desert in Antarctica. Alpha diversity, estimated as the total number of OTUs at the taxonomic level of Order, is displayed in a line graph on the left and as a box plot on the right. In the left figure all samples are shown and colored by location, but any desired metadata parameter could have been chosen. In the box plot on the right, samples have been grouped by location. Individual data points and outliers can be displayed, as well as indicators for mean and median. Groups can be compared with a Kruskal-Wallis test and the p-values for any pairwise comparison displayed above the plot (as shown). In the example of the Antarctica microbiomes, the microbial diversity was significantly higher in the Dry Valleys soil as compared to the saline water in Ace Lake (p = 0.03), and the microbial diversity was significantly lower in the Dry Valleys soil as compared to the marine sediment at Adelie Basin (p = 0.03).
CLC Microbial Genomics Module also provides several different metrics for estimating the beta diversity in a set of samples, including Bray-Curtis, Jaccard, Euclidean, and UniFrac. The latest release now enables users to display beta diversity in either a 2D or 3D PCoA plot. Below is shown the beta diversity among samples from different locations in Antarctica. On the left, the beta diversity is visualized in the existing 3D PCoA plot, and on the right, the diversity is visualized in the new 2D PCoA plot. The new 2D PCoA plot will be generated automatically when running the tool Beta Diversity. The data can be sorted and displayed with any user defined metadata. In the example below, data points are colored by location. As evident from both graphical representations, the microbial communities in Antarctica are clearly separated by geographic location.
There are several new features in the latest release of CLC Microbial Genomics Module. If you haven’t already done so, upgrade your installation today to take advantage of these new visualizations simply by opening. If you are new to CLC Genomics Workbench or the CLC Microbial Genomics Module, you can download the software with a free 14-day trial license here.