Evidence map›Paper›PMID 28398290›Full record

ArticleScientific data2017

A geographically-diverse collection of 418 human gut microbiome pathway genome databases.

Aria S Hahn, Tomer Altman, Kishori M Konwar, Niels W Hanson, Dongjae Kim, David A Relman, David L Dill, Steven J Hallam

Abstract readDataset
In one paragraph

Article in Scientific data, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
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

8 authors.

Aria S HahnDepartment of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada.
Tomer AltmanBiomedical Informatics, Stanford University School of Medicine, Stanford, California 94305, USA.ORCID 0000-0002-6521-5454
Kishori M KonwarDepartment of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada.
Niels W HansonDepartment of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada.
Dongjae KimDepartment of Computer Science, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada.
David A RelmanDepartment of Microbiology and Immunology, Stanford University School of Medicine, 299 Campus Drive, Stanford, California 94305, USA.
David L DillDepartment of Computer Science, Stanford University, Stanford, California 94305, USA.
Steven J HallamDepartment of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada.

Funding

Graduate Training Program in BiotechnologyT32GM008412 · NIGMS · STANFORD UNIVERSITY · PI COCHRAN, JENNIFER R · 1991 to 2020
$5.5M
Antibiotics and Human Microbial Community DynamicsR01GM099534 · NIGMS · PALO ALTO VETERANS INSTIT FOR RESEARCH · PI RELMAN, DAVID A. · 2013 to 2016
$1.1M
NIGMS NIH HHS R01 GM099534NIGMS NIH HHS T32 GM008412
6 · The paper itself

Abstract

Advances in high-throughput sequencing are reshaping how we perceive microbial communities inhabiting the human body, with implications for therapeutic interventions. Several large-scale datasets derived from hundreds of human microbiome samples sourced from multiple studies are now publicly available. However, idiosyncratic data processing methods between studies introduce systematic differences that confound comparative analyses. To overcome these challenges, we developed GutCyc, a compendium of environmental pathway genome databases (ePGDBs) constructed from 418 assembled human microbiome datasets using MetaPathways, enabling reproducible functional metagenomic annotation. We also generated metabolic network reconstructions for each metagenome using the Pathway Tools software, empowering researchers and clinicians interested in visualizing and interpreting metabolic pathways encoded by the human gut microbiome. For the first time, GutCyc provides consistent annotations and metabolic pathway predictions, making possible comparative community analyses between health and disease states in inflammatory bowel disease, Crohn's disease, and type 2 diabetes. GutCyc data products are searchable online, or may be downloaded and explored locally using MetaPathways and Pathway Tools.

Indexed as

Databases, GeneticGastrointestinal MicrobiomeMetabolic Networks and PathwaysCrohn DiseaseDiabetes Mellitus, Type 2Geography, MedicalHumansInflammatory Bowel DiseasesMetagenomeMetagenomics

Identifiers

PMID28398290
PMCPMC5387927

What OpenQuestion holds

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LicenceCC BY
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.