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Quantifying compositional variability in microbial communities with FAVA.

Maike L MorrisonKatherine S XueNoah A Rosenberg
Published in: bioRxiv : the preprint server for biology (2024)
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 measure, FAVA, meets the need for a statistic summarizing compositional variability across many microbiome samples all at once.
Keyphrases
  • microbial community
  • healthcare
  • mental health
  • single cell
  • antibiotic resistance genes