ArticleJournal of mathematical biology2018
EMDUniFrac: exact linear time computation of the UniFrac metric and identification of differentially abundant organisms.
Article in Journal of mathematical biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Megascale microbiome analysis with DartUniFrac.Nature biotechnology · 2026Article
- Integrating taxonomic signals from MAGs and contigs improves read annotation and taxonomic profiling of metagenomes.Nature communications · 2024Article
- Finding phylogeny-aware and biologically meaningful averages of metagenomic samples: L2UniFrac.Bioinformatics (Oxford, England) · 2023Article
- A social niche breadth score reveals niche range strategies of generalists and specialists.Nature ecology & evolution · 2023Article
- Finding phylogeny-aware and biologically meaningful averages of metagenomic samples:bioRxiv : the preprint server for biology · 2023Article
- A network perspective on the ecology of gut microbiota and progression of type 2 diabetes: Linkages to keystone taxa in a Mexican cohort.Frontiers in endocrinology · 2023Article
- TAMPA: interpretable analysis and visualization of metagenomics-based taxon abundance profiles.GigaScience · 2022Article
- Crowdsourced benchmarking of taxonomic metagenome profilers: lessons learned from the sbv IMPROVER Microbiomics challenge.BMC genomics · 2022Article
- Critical Assessment of Metagenome Interpretation: the second round of challenges.Nature methods · 2022Article
- Toward interpretable digital biomarkers of walking and reaching in Parkinson's disease.Wearable technologies · 2022Article
- Personalized Biometrics of Physical Pain Agree with Psychophysics by Participants with Sensory over Responsivity.Journal of personalized medicine · 2021Article
- Digitized Autism Observation Diagnostic Schedule: Social Interactions beyond the Limits of the Naked Eye.Journal of personalized medicine · 2020Article
- Evaluation of haplotype callers for next-generation sequencing of viruses.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2020Article
- The Autonomic Nervous System Differentiates between Levels of Motor Intent and End Effector.Journal of personalized medicine · 2020Article
- Aging with Autism Departs Greatly from Typical Aging.Sensors (Basel, Switzerland) · 2020Article
- Assessing taxonomic metagenome profilers with OPAL.Genome biology · 2019Article
- A Commentary on Diversity Measures UniFrac in Very Small Sample Size.Evolutionary bioinformatics online · 2019Article
- Visibiome: an efficient microbiome search engine based on a scalable, distributed architecture.BMC bioinformatics · 2017Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Both the weighted and unweighted UniFrac distances have been very successfully employed to assess if two communities differ, but do not give any information about how two communities differ. We take advantage of recent observations that the UniFrac metric is equivalent to the so-called earth mover's distance (also known as the Kantorovich-Rubinstein metric) to develop an algorithm that not only computes the UniFrac distance in linear time and space, but also simultaneously finds which operational taxonomic units are responsible for the observed differences between samples. This allows the algorithm, called EMDUniFrac, to determine why given samples are different, not just if they are different, and with no added computational burden. EMDUniFrac can be utilized on any distribution on a tree, and so is particularly suitable to analyzing both operational taxonomic units derived from amplicon sequencing, as well as community profiles resulting from classifying whole genome shotgun metagenomes. The EMDUniFrac source code (written in python) is freely available at: https://github.com/dkoslicki/EMDUniFrac .
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29691633What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.