Using vegan to calculate alpha diversity metrics within the tidyverse in R (CC196)

Among the useful tools in the vegan R package are functions for calculating alpha diversity metrics and indices. In this episode of Code Club, Pat shows how to create our own versions of these functions and how we can implement either version in a group_by / summarize pipeline using dplyr. We'll also take a look at whether there is an effect of sampling effort on the observed richness, shannon diversity, and simpson diversity. He'll show how to synthesize and visualize the data using tools from vegan, dplyr, ggplot2 and other tidyverse packages.

You can find my blog post for this episode at https://www.riffomonas.org/code_club/.... The data were generated in our Kozich et al. 2013 paper (http://doi.org/10.1128/AEM.01043-13) using samples from the Schloss et al. 2012 paper (http://doi.org/10.4161/gmic.21008).

#rarefaction #vegan #R #Rstudio #Rstats

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0:00 Difference between alpha and beta diversity
3:22 Writing our own functions to calculate alpha diversity
10:20 Plotting alpha diversity as a function of sampling effort
11:42 Is there an influence of sampling effect?
14:03 Implementing and comparing vegan version of functions