Evidence map›Paper›PMID 27454739›Full record

ArticleNature biotechnology2016

Systematic improvement of amplicon marker gene methods for increased accuracy in microbiome studies.

Daryl M Gohl, Pajau Vangay, John Garbe, Allison MacLean, Adam Hauge, Aaron Becker, Trevor J Gould, Jonathan B Clayton, Timothy J Johnson, Ryan Hunter and 2 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature biotechnology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 427 papers.

0numbers the graph read from it
0cells of the map it votes in
427citing 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

427 citing papers in PubMed.

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  20. Wavyleaf basketgrass (mSphere · 2026
    Article

367 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

12 authors.

Daryl M GohlUniversity of Minnesota Genomics Center, Minneapolis, Minnesota, USA.ORCID 0000-0002-4434-2788
Pajau VangayBiomedical Informatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota, USA.
John GarbeMinnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota, USA.
Allison MacLeanUniversity of Minnesota Genomics Center, Minneapolis, Minnesota, USA.
Adam HaugeUniversity of Minnesota Genomics Center, Minneapolis, Minnesota, USA.
Aaron BeckerUniversity of Minnesota Genomics Center, Minneapolis, Minnesota, USA.
Trevor J GouldUniversity of Minnesota Informatics Institute, Minneapolis, Minnesota, USA.
Jonathan B ClaytonDepartment of Veterinary and Biomedical Sciences, University of Minnesota, St. Paul, Minnesota, USA.
Timothy J JohnsonDepartment of Veterinary and Biomedical Sciences, University of Minnesota, St. Paul, Minnesota, USA.
Ryan HunterDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA.
Dan KnightsBiotechnology Institute, University of Minnesota, St. Paul, Minnesota, USA.
Kenneth B BeckmanUniversity of Minnesota Genomics Center, Minneapolis, Minnesota, USA.

Funding

Training in PharmacoNeuroImmune Substance Abuse ResearchT32DA007097 · NIDA · UNIVERSITY OF MINNESOTA TWIN CITIES · PI MOLITOR, THOMAS WILLIAM · 1985 to 2021
$13.1M
NIDA NIH HHS T32 DA007097
6 · The paper itself

Abstract

Amplicon-based marker gene surveys form the basis of most microbiome and other microbial community studies. Such PCR-based methods have multiple steps, each of which is susceptible to error and bias. Variance in results has also arisen through the use of multiple methods of next-generation sequencing (NGS) amplicon library preparation. Here we formally characterized errors and biases by comparing different methods of amplicon-based NGS library preparation. Using mock community standards, we analyzed the amplification process to reveal insights into sources of experimental error and bias in amplicon-based microbial community and microbiome experiments. We present a method that improves on the current best practices and enables the detection of taxonomic groups that often go undetected with existing methods.

Indexed as

Gene LibraryDNA ReplicationGenetic MarkersHigh-Throughput Nucleotide SequencingMicrobiotaPolymerase Chain ReactionPractice Guidelines as TopicReproducibility of ResultsSensitivity and SpecificityGenetic Markers

Identifiers

PMID27454739

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.