Evidence map›Paper›PMID 35369727›Full record

ArticlemSystems2022

Phylogeny-Aware Analysis of Metagenome Community Ecology Based on Matched Reference Genomes while Bypassing Taxonomy.

Qiyun Zhu, Shi Huang, Antonio Gonzalez, Imran McGrath, Daniel McDonald, Niina Haiminen, George Armstrong, Yoshiki Vázquez-Baeza, Julian Yu, Justin Kuczynski and 16 more

Erratum issuedAbstract read
In one paragraph

Article in mSystems, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 84 papers.

0numbers the graph read from it
0cells of the map it votes in
84citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

84 citing papers in PubMed.

  1. Trial
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  16. Comparative Analysis of Rhizosphere Bacteria ofPolish journal of microbiology · 2026
    Article
  17. Article
  18. SCiMS: Sex Calling in Metagenomic Sequences.bioRxiv : the preprint server for biology · 2026
    Article
  19. Deconvolving Phylogenetic Distance Mixtures.bioRxiv : the preprint server for biology · 2026
    Article
  20. Article

24 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

26 authors.

Qiyun Zhu *School of Life Sciences, Arizona State Universitygrid.215654.1, Tempe, Arizona, USA.ORCID 0000-0002-3568-6271
Shi Huang *Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA.ORCID 0000-0002-7529-2269
Antonio GonzalezDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA.
Imran McGrathCenter for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA.ORCID 0000-0001-8791-4398
Daniel McDonaldDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA.ORCID 0000-0003-0876-9060
Niina HaiminenIBM T. J. Watson Research Center, Yorktown Heights, New York, USA.ORCID 0000-0002-8663-1019
George ArmstrongDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA.ORCID 0000-0002-1061-3295
Yoshiki Vázquez-BaezaCenter for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA.ORCID 0000-0001-6014-2009
Julian YuSchool of Life Sciences, Arizona State Universitygrid.215654.1, Tempe, Arizona, USA.
Justin KuczynskiGoogle, Mountain View, California, USA.
Gregory D Sepich-PooreDepartment of Bioengineering, University of California San Diego, La Jolla, California, USA.ORCID 0000-0002-3443-3715
Austin D SwaffordCenter for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA.ORCID 0000-0001-5655-8300
Promi DasDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA.ORCID 0000-0001-6733-2059
Justin P ShafferDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA.ORCID 0000-0002-9371-6336
Franck LejzerowiczDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA.ORCID 0000-0002-3195-032X
Pedro Belda-FerreDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA.ORCID 0000-0001-6532-1161
Aki S HavulinnaDepartment of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland.ORCID 0000-0002-4787-8959
Guillaume MéricCambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.ORCID 0000-0001-6288-9958
Teemu NiiranenDepartment of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland.ORCID 0000-0002-7394-7487
Leo LahtiDepartment of Computing, University of Turku, Turku, Finland.ORCID 0000-0001-5537-637X
Veikko SalomaaDepartment of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland.ORCID 0000-0001-7563-5324
Ho-Cheol KimIBM Almaden Research Center, San Jose, California, USA.ORCID 0000-0003-0464-4340
Mohit JainDepartment of Medicine, University of California San Diego, La Jolla, California, USA.ORCID 0000-0001-8628-2069
Michael InouyeCambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.ORCID 0000-0001-9413-6520
Jack A GilbertDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA.ORCID 0000-0001-7920-7001
Rob KnightDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA.ORCID 0000-0002-0975-9019

Funding

Project 4 - Mechanistic studies on the role of the gut microbiome in models for Alzheimer's diseaseU19AG063744 · NIA · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ROB KNIGHT, Rima F Kaddurah-Daouk · 2019 to 2026
$54.1M
UCSD/SDSU IRACDAK12GM068524 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI TREJO, JOANN · 2003 to 2025
$24.4M
San Diego Digestive Diseases Research CenterP30DK120515 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LARS ECKMANN, Bernd G. Schnabl · 2019 to 2026
$10.8M
Mapping host-microbe-metabolite interactions in 3D to find diet-derived enhancers of immunityDP1AT010885 · NCCIH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KNIGHT, ROB · 2019 to 2023
$5.5M
Advanced Development of Informatics Technologies for Cancer Research and Management (U24 Clinical Trial Optional)U24CA248454 · NCI · NORTHERN ARIZONA UNIVERSITY · PI CAPORASO, JAMES GREGORY · 2020 to 2024
$3.7M
Comprehensive characterization of the cancer microbiome and its immuno-oncology interfaceF30CA243480 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI POORE, GREGORY DERRICK · 2020 to 2021
$73k
British Heart Foundation CH/12/2/29428British Heart Foundation RG/13/13/30194British Heart Foundation RG/18/13/33946NCCIH NIH HHS DP1 AT010885NCI NIH HHS F30 CA243480NCI NIH HHS U24 CA248454NIA NIH HHS U19 AG063744NIDDK NIH HHS P30 DK120515NIGMS NIH HHS K12 GM068524
6 · The paper itself

Abstract

We introduce the operational genomic unit (OGU) method, a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent of taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance, and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldom applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome data sets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project data set and more accurate prediction of human age by the gut microbiomes of Finnish individuals included in the FINRISK 2002 cohort. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate adoption of the OGU method in future metagenomics studies.

Indexed as

MetagenomeMicrobiotaEcologyHumansPhylogenyRNA, Ribosomal, 16SRNA, Ribosomal, 16Smetagenomicsoperational genomic unitreference phylogenysupervised learningtaxonomy independentUniFrac

Identifiers

PMID35369727
PMCPMC9040630

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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.