R: Quantify Compositional Variability Across Relative Abundance Vectors

# Quantify Compositional Variability Across Relative Abundance Vectors

## Documentation for package ‘FAVA’ version 1.0.9

- DESCRIPTION file.
- Package NEWS.

## Help Pages

bootstrap_fava | Statistically compare FAVA values between pairs of relative abundance matrices.
fava | Compute the Fst of a matrix of compositional vectors
fava_norm | Compute the normalized Fst of a matrix of compositional vectors
gini_simpson | Compute the Gini-Simpson index of a compositional vector
gini_simpson_mean | Compute the mean Gini-Simpson index of the rows in a matrix of compositional vectors
gini_simpson_pooled | Compute the pooled Gini-Simpson index of the rows in a matrix of compositional vectors
plot_relabund | Visualize a relative abundance matrix as a stacked bar plot.
relab_phyloseq | Generate a relative abundance matrix with sample metadata and OTU abundances from a phyloseq object.
time_weights | Compute a normalized weighting vector based on a vector of sampling times.
window_fava | Compute FAVA in sliding windows.
window_list | Generate sliding windows of specified length given the maximum number of samples
window_plot | Generate a plot of FAVA in sliding windows.
xue_microbiome_sample | Temporal microbiome composition data
xue_species_info | Table of species information
xue_species_similarity | Species similarity matrix for the species included in xue_microbiome_sample
xue_species_tree | Phylogenetic tree for the species included in xue_microbiome_sample