Finding phylogeny-aware and biologically meaningful averages of metagenomic samples: L2UniFrac
Abstract
Metagenomic samples have high spatiotemporal variability. Hence, it is useful to summarize and characterize the microbial makeup of a given environment in a way that is biologically reasonable and interpretable. The UniFrac metric has been a robust and widely-used metric for measuring the variability between metagenomic samples. We propose that the characterization of metagenomic environments can be achieved by finding the average, a.k.a. the barycenter, among the samples with respect to the UniFrac distance. However, it is possible that such a UniFrac-average includes negative entries, making it no longer a valid representation of a metagenomic community. To overcome this intrinsic issue, we propose a special version of the UniFrac metric, termed L2UniFrac, which inherits the phylogenetic nature of the traditional UniFrac and with respect to which one can easily compute the average, producing biologically meaningful environment-specific "representative samples". We demonstrate the usefulness of such representative samples as well as the extended usage of L2UniFrac in efficient clustering of metagenomic samples, and provide mathematical characterizations and proofs to the desired properties of L2UniFrac. A prototype implementation is provided at: https://github.com/KoslickiLab/L2-UniFrac.git.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 1
- FWCI
- 0.09
- Field percentile
- 31th percentile
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Scalable methods for analyzing and visualizing phylogenetic placement of metagenomic samples
Lucas Czech, Alexandros Stamatakis·PLoS ONEPeer-reviewed·May 28, 2019
- Using the UniFrac metric on Whole Genome Shotgun data
Wei Wei, David Koslicki·bioRxiv·Jan 17, 2022
- On branch lengths assignment methods for trees with fixed topology and related biological applications
Wei Wei, David Koslicki·bioRxiv·Jul 29, 2024
- EMDUnifrac: Exact linear time computation of the Unifrac metric and identification of differentially abundant organisms
J. McClelland, D. Koslicki·bioRxiv·Nov 14, 2016
- Interpreting UniFrac with Absolute Abundance: A Conceptual and Practical Guide
Augustus Pendleton, Marian L. Schmidt·ISME CommunicationsPeer-reviewed·Jan 1, 2026
- BinSanity: Unsupervised Clustering of Environmental Microbial Assemblies Using Coverage and Affinity Propagation
Elaina Graham, John Heidelberg, Benjamin Tully·bioRxiv·Aug 16, 2016