Evidence map›Paper›PMID 24060131›Full record

ArticleMethods in enzymology2013

Advancing our understanding of the human microbiome using QIIME.

José A Navas-Molina, Juan M Peralta-Sánchez, Antonio González, Paul J McMurdie, Yoshiki Vázquez-Baeza, Zhenjiang Xu, Luke K Ursell, Christian Lauber, Hongwei Zhou, Se Jin Song and 6 more

Open access · greenAbstract read
In one paragraph

Article in Methods in enzymology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 331 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
331citing papers in PubMed, 1 pooled it
57.5field-weighted citation impact, top 1% of its field
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

331 citing papers in PubMed, 1 synthesis or guideline pooled it, 620 citations in OpenAlex.

  1. Pooled it
  2. Trial
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  6. Trial
  7. Article
  8. Metagenomic analysis of the intragastric and oral microbiome associated with gastric carcinogenesis after Helicobacter pylori eradication.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2026
    Article
  9. Impact of carbapenem-resistantMicrobiology spectrum · 2026
    Article
  10. Effect of a fructooligosaccharides fraction fromBioscience of microbiota, food and health · 2026
    Article
  11. Review
  12. Article
  13. World journal of gastroenterology · 2025
    Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Review
  19. Oral microbiota related to allergy in Norwegian adults.The journal of allergy and clinical immunology. Global · 2025
    Article
  20. Article

271 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

16 authors at 6 institutions in 2 countries.

José A Navas-MolinaDepartment of Computer Science, University of Colorado, Boulder, Colorado, USA.
Juan M Peralta-Sánchez
Antonio González
Paul J McMurdie
Yoshiki Vázquez-Baeza
Zhenjiang Xu
Luke K Ursell
Christian Lauber
Hongwei Zhou
Se Jin Song
James Huntley
Gail L Ackermann
Donna Berg-Lyons
Susan Holmes
J Gregory Caporaso
Rob Knight
University of Colorado Boulder · USStanford University · USCooperative Institute for Research in Environmental Sciences · USHoward Hughes Medical Institute · USNorthern Arizona University · USSouthern Medical University · CN

Funding

TRAINING IN SIGNAL TRANSDUCTION &CELL CYCLE REGULATIONT32GM008759 · NIGMS · UNIVERSITY OF COLORADO AT BOULDER · PI AHN, NATALIE G. · 2000 to 2020
$5.9M
Predoctoral Training Program in Signaling and Cellular Regulation INCLUDE Down Syndrome SupplementT32GM142607 · NIGMS · UNIVERSITY OF COLORADO · PI Sabrina Leigh Spencer, Tin Tin Su · 2021 to 2026
$3.6M
Heterogeneous in situ data: Kernals, Distances and TreesR01GM086884 · NIGMS · STANFORD UNIVERSITY · PI HOLMES, SUSAN P · 2008 to 2011
$895k
Howard Hughes Medical InstituteNIGMS NIH HHS R01 GM086884NIGMS NIH HHS R01GM086884NIGMS NIH HHS T32 GM008759NIGMS NIH HHS T32 GM142607
6 · The paper itself

Abstract

High-throughput DNA sequencing technologies, coupled with advanced bioinformatics tools, have enabled rapid advances in microbial ecology and our understanding of the human microbiome. QIIME (Quantitative Insights Into Microbial Ecology) is an open-source bioinformatics software package designed for microbial community analysis based on DNA sequence data, which provides a single analysis framework for analysis of raw sequence data through publication-quality statistical analyses and interactive visualizations. In this chapter, we demonstrate the use of the QIIME pipeline to analyze microbial communities obtained from several sites on the bodies of transgenic and wild-type mice, as assessed using 16S rRNA gene sequences generated on the Illumina MiSeq platform. We present our recommended pipeline for performing microbial community analysis and provide guidelines for making critical choices in the process. We present examples of some of the types of analyses that are enabled by QIIME and discuss how other tools, such as phyloseq and R, can be applied to expand upon these analyses.

Indexed as

AnimalsBacteriaComputational BiologyHigh-Throughput Nucleotide SequencingHumansMiceMicrobiotaPhylogenySoftwareHighthroughput sequencingMicrobial community analysesMicrobial ecologyMicrobiomeQIIME

Identifiers

PMID24060131
PMCPMC4517945
OpenAlexW30236741

What OpenQuestion holds

Textmetadata
LicenceTDM
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.