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The FAVA R package implements the statistic FAVA, an \(F_{ST}\)-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 et al. (2024).
The FAVA R package includes the following core functions:
fava: Quantify variability across many compositional
vectors in a single, normalized index, called FAVA
bootstrap_fava: Compare values of FAVA between pairs
of abundance matrices
window_fava: Compute FAVA in sliding windows along
the rows of a relative abundance matrix
plot_relabund: Visualize a relative abundance matrix
as a stacked bar plot
Install FAVA with:
install.packages("FAVA")You can install the development version of FAVA from GitHub with:
# First, install devtools if you haven't already:
# install.packages("devtools")
devtools::install_github("MaikeMorrison/FAVA")
# If you wish to access the tutorial (also accessible below) from within
# the package:
devtools::install_github("MaikeMorrison/FAVA", build_vignettes = TRUE)The package website, maikemorrison.github.io/FAVA/, contains documentation and examples for all package functions. It also contains a tutorial on the usage of FAVA for the analysis of microbiome data. The tutorial vignette is available at this link.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.