LAUSR

Significance Studies of microbial community composition across time, space, or biological replicates often rely on summary statistics that analyze just one or two samples at a time. Although these statistics effectively summarize the diversity of one sample or the compositional dissimilarity between two samples, they are ill-suited for measuring variability across many samples at once. Measuring compositional variability among many samples is key to understanding the temporal stability of a community across multiple time points or the heterogeneity of microbiome composition across multiple experimental replicates or host individuals. Our proposed framework, FST-based Assessment of Variability across vectors of relative Abundances (FAVA), meets the need for a statistic summarizing compositional variability across many microbiome samples all at once.