Evidence map›Paper›PMID 29795328›Full record

ReviewNature reviews. Microbiology2018

Best practices for analysing microbiomes.

Rob Knight, Alison Vrbanac, Bryn C Taylor, Alexander Aksenov, Chris Callewaert, Justine Debelius, Antonio Gonzalez, Tomasz Kosciolek, Laura-Isobel McCall, Daniel McDonald and 13 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Microbiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 994 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
994citing papers in PubMed, 8 pooled it
–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

994 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

23 authors.

Rob KnightCenter for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA. robknight@ucsd.edu.ORCID http://orcid.org/0000-0002-0975-9019
Alison VrbanacBiomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA.
Bryn C TaylorBiomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA.
Alexander AksenovSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA.
Chris CallewaertDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA.
Justine DebeliusDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA.
Antonio GonzalezDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA.
Tomasz KosciolekDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA.ORCID http://orcid.org/0000-0002-9915-7387
Laura-Isobel McCallSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA.
Daniel McDonaldDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA.
Alexey V MelnikSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA.
James T MortonDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA.
Jose NavasDepartment of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA.
Robert A QuinnSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA.
Jon G SandersDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA.ORCID http://orcid.org/0000-0001-6077-4014
Austin D SwaffordCenter for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA.
Luke R ThompsonDepartment of Biological Sciences and Northern Gulf Institute, University of Southern Mississippi, Hattiesburg, MS, USA.ORCID http://orcid.org/0000-0002-3911-1280
Anupriya TripathiDivision of Biological Sciences, University of California, San Diego, La Jolla, CA, USA.
Zhenjiang Z XuDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA.
Jesse R ZaneveldDivision of Biological Sciences, School of Science Technology Engineering and Math, University of Washington Bothell, Bothell, WA, USA.
Qiyun ZhuDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA.ORCID http://orcid.org/0000-0002-3568-6271
J Gregory CaporasoPathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ, USA.
Pieter C DorresteinCenter for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Complex microbial communities shape the dynamics of various environments, ranging from the mammalian gastrointestinal tract to the soil. Advances in DNA sequencing technologies and data analysis have provided drastic improvements in microbiome analyses, for example, in taxonomic resolution, false discovery rate control and other properties, over earlier methods. In this Review, we discuss the best practices for performing a microbiome study, including experimental design, choice of molecular analysis technology, methods for data analysis and the integration of multiple omics data sets. We focus on recent findings that suggest that operational taxonomic unit-based analyses should be replaced with new methods that are based on exact sequence variants, methods for integrating metagenomic and metabolomic data, and issues surrounding compositional data analysis, where advances have been particularly rapid. We note that although some of these approaches are new, it is important to keep sight of the classic issues that arise during experimental design and relate to research reproducibility. We describe how keeping these issues in mind allows researchers to obtain more insight from their microbiome data sets.

Indexed as

AnimalsBacteriaEnvironmental MicrobiologyHumansMetagenomicsMicrobiotaReproducibility of Results

Identifiers

PMID29795328

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.