Phylogenetically informed analysis of microbiome data using adaptive gPCA in R
When analyzing microbiome data, biologists often use exploratory methods that take into account the relatedness of the bacterial species present in the data. This helps in the interpretability and stability of the analysis because phylogenetically related bacteria often have similar functions. However, we believe (and will demonstrate), that the methods currently in use put too much emphasis on the phylogeny when making the ordinations. To address this, we have developed a framework we call adaptive gPCA, which allows the user to specify the amount of weight given to the tree and which will automatically select an amount of weight to give to the tree. We have implemented this method in R and have made it easy to use with phyloseq, a popular R package for microbiome data storage and manipulation. Additionally, we have developed a shiny app that allows for interactive data visualization and comparison of the ordinations resulting from different weightings of the tree.