Evidence map›Paper›PMID 38774631›Full record

ArticleFrontiers in cellular and infection microbiology2024

FAIR compliant database development for human microbiome data samples.

Mathieu Dorst, Nathan Zeevenhooven, Rory Wilding, Daniel Mende, Bernd W Brandt, Egija Zaura, Alfons Hoekstra, Vivek M Sheraton

Abstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Computational Metagenomics: State of the Art.International journal of molecular sciences · 2025
    Review
  4. Article
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.

Mathieu Dorst *Informatics Institute, University of Amsterdam, Amsterdam, Netherlands.
Nathan Zeevenhooven *Informatics Institute, University of Amsterdam, Amsterdam, Netherlands.
Rory WildingSupabase Limited Liability Company (LLC), San Francisco, CA, United States.
Daniel MendeAmsterdam Institute of Infection and Immunity, Amsterdam University Medical Center, Amsterdam, Netherlands.
Bernd W BrandtDepartment of Preventive Dentistry, Academic Centre for Dentistry Amsterdam, Vrije Universiteit Amsterdam and University of Amsterdam, Amsterdam, Netherlands.
Egija ZauraDepartment of Preventive Dentistry, Academic Centre for Dentistry Amsterdam, Vrije Universiteit Amsterdam and University of Amsterdam, Amsterdam, Netherlands.
Alfons HoekstraComputational Science Lab, Informatics Institute, University of Amsterdam, Amsterdam, Netherlands.
Vivek M SheratonComputational Science Lab, Informatics Institute, University of Amsterdam, Amsterdam, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Sharing microbiome data among researchers fosters new innovations and reduces cost for research. Practically, this means that the (meta)data will have to be standardized, transparent and readily available for researchers. The microbiome data and associated metadata will then be described with regards to composition and origin, in order to maximize the possibilities for application in various contexts of research. Here, we propose a set of tools and protocols to develop a real-time FAIR (Findable. Accessible, Interoperable and Reusable) compliant database for the handling and storage of human microbiome and host-associated data. Methods: The conflicts arising from privacy laws with respect to metadata, possible human genome sequences in the metagenome shotgun data and FAIR implementations are discussed. Alternate pathways for achieving compliance in such conflicts are analyzed. Sample traceable and sensitive microbiome data, such as DNA sequences or geolocalized metadata are identified, and the role of the GDPR (General Data Protection Regulation) data regulations are considered. For the construction of the database, procedures have been realized to make data FAIR compliant, while preserving privacy of the participants providing the data. Results and discussion: An open-source development platform, Supabase, was used to implement the microbiome database. Researchers can deploy this real-time database to access, upload, download and interact with human microbiome data in a FAIR complaint manner. In addition, a large language model (LLM) powered by ChatGPT is developed and deployed to enable knowledge dissemination and non-expert usage of the database.

Indexed as

MicrobiotaComputational BiologyDatabases, FactualDatabases, GeneticHumansInformation DisseminationMetadataMetagenomeMetagenomicsdatabasefair principlesgeneral data protection regulation (GDPR)(meta)datamicrobiomepseudonymizereal-time

Identifiers

PMID38774631
PMCPMC11106358

What Socratic holds

Textmetadata
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 Socratic graph.