Performing principal coordinate analysis (PCoA) in R and visualizing with ggplot2 (CC186)

Principal coordinate analysis (PCoA) and its relative, principal component analysis (PCA) are popular ordination techniques that you can use to reduce the dimensions of data in R. In this episode, Pat Schloss will show how to perform PCoA in R and visualize the ordination and companion scree plot. We'll use the cmdscale function from base R and tools from ggplot2 and the tidyverse package.

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).

#cmdscale #ggplot2 #R #Rstudio #Rstats

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0:00 Performing principal coordinates analysis in R
3:45 Running cmdscale to generate ordination
4:14 Plotting ordination data with ggplot2
6:36 Getting data for more than 2 axis
7:18 Determining percent of variation explained by each axis
15:53 Creating a scree plot