How to calculate the Aitchison distance in R using two center logratio transformations (CC194)

The Aitchison distance is the Euclidean distance calculated on species counts subjected to a center logratio transformation (clr). There are several papers that claim whether this distance is invariant or insensitive to differences in sampling depth. Is that true? In this episode, Pat tests Aitchison distances calculated using the robust clr as well as the traditional clr calculated on a count matrix where zero values are imputed using functions from the zComparisons package. He'll compare it to non-rarefied, non-transformed Euclidean distances and to rarefied, non-transformed Euclidean distances. Which approach do you think is most sensitive to uneven sampling effort? 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). #zCompositions #vegan #R #Rstudio #Rstats Want more practice on the concepts covered in Code Club? You can sign up for my weekly newsletter at https://shop.riffomonas.org/youtube to get practice problems, tips, and insights. If you're interested in taking an upcoming 3 day R workshop be sure to check out our schedule at https://riffomonas.org/workshops/ You can also find complete tutorials for learning R with the tidyverse using... Microbial ecology data: https://www.riffomonas.org/minimalR/ General data: https://www.riffomonas.org/generalR/ 0:00 Effects of center logratio transformations on ecological distances 6:09 Calculating non-rarefied and rarefied Euclidean distances 8:47 Calculating the geometric mean 11:51 Calculating Atchison distances with robust clr 13:54 Calculating Atchison distances with imputed zeroes 17:52 Comparing sensitivity of difference in number of sequences on distances