Diversity
vignette-diversity.Rmd
Alpha and beta diversity are performed using the phyloseq package (McMurdie and Holmes, 2013).
- Because of the time and resources that are used for these computations, the maximum number of samples possible is 1000. If you have more samples, you will need to deselect some datasets or groups of samples.
- Number of reads not rarefield or normalized.
- For alpha diversity, smoothing is done with “gam” (general additive model). Samples with diversity of 0 are removed.
- If you increase the minimum number of reads an ASV must have (left menu) computation will be faster.
- We do not recommend to use these analyses if you only select a small number of ASVs (e.g. at the genus or species level) or small number of samples.
In order to start the computation, press on the button which will build the phyloseq file from the selected data.
BE PATIENT, computation takes some time especially for beta diversity…
Alpha diversity
You can:
- compute different indices and display as violin plot when using a discrete variable for y-axis.
- Change the y axis. If you choose a continuous variable (depth, latitude, temperature, salinity), you can choose to discretize it in intervals.
- Change the color of points (continuous variables)
- Change the shape of points (discrete variables)
![Fig. 1A: Alpha diversity: continuous y axis](img/alpha_01.png)
Fig. 1A: Alpha diversity: continuous y axis
![Fig. 1B: Alpha diversity: discrete y-axis](img/alpha_02.png)
Fig. 1B: Alpha diversity: discrete y-axis
Beta diversity
You can:
- Use different methods and distances
- Change the x axis
- Change the color of points (continuous variables)
- Change the shape of points (discrete variables)
![Fig. 2: Beta diversity samples.](img/beta_01.png)
Fig. 2: Beta diversity samples.
![Fig. 3: Bata diversity taxa and phyloseq object structure.](img/beta_02.png)
Fig. 3: Bata diversity taxa and phyloseq object structure.
References
- McMurdie, P.J., Holmes, S., 2013. Phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLoS ONE 8, e61217. https://doi.org/10.1371/journal.pone.0061217