Quantify Compositional Variability Across Relative Abundance Vectors
Statistically compare FAVA values between pairs of relative abundance ...
Compute the normalized Fst of a matrix of compositional vectors
Compute the Fst of a matrix of compositional vectors
Compute the mean Gini-Simpson index of the rows in a matrix of composi...
Compute the pooled Gini-Simpson index of the rows in a matrix of compo...
Compute the Gini-Simpson index of a compositional vector
Visualize a relative abundance matrix as a stacked bar plot.
Generate a relative abundance matrix with sample metadata and OTU abun...
Compute a normalized weighting vector based on a vector of sampling ti...
Compute FAVA in sliding windows.
Generate sliding windows of specified length given the maximum number ...
Generate a plot of FAVA in sliding windows.
Implements the statistic FAVA, an Fst-based Assessment of Variability across vectors of relative Abundances, as well as a suite of helper functions which enable the visualization and statistical analysis of relative abundance data. The 'FAVA' R package accompanies the paper, “Quantifying compositional variability in microbial communities with FAVA” by Morrison, Xue, and Rosenberg (2025) <doi:10.1073/pnas.2413211122>.
Useful links