Evidence map›Paper›PMID 32179734›Full record

ArticleScientific data2020

Gut microbiome diversity detected by high-coverage 16S and shotgun sequencing of paired stool and colon sample.

Joan Mas-Lloret, Mireia Obón-Santacana, Gemma Ibáñez-Sanz, Elisabet Guinó, Miguel L Pato, Francisco Rodriguez-Moranta, Alfredo Mata, Ana García-Rodríguez, Victor Moreno, Ville Nikolai Pimenoff

Abstract readDataset
In one paragraph

Article in Scientific data, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 4 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

43 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
  6. Article
  7. The microbiome and its impact on the epigenome in cancer.Frontiers in epigenetics and epigenomics · 2026
    Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Review
  15. Article
  16. Article
  17. KL-Biome (Postbiotic Formulation ofInternational journal of molecular sciences · 2024
    Article
  18. Article
  19. Compression algorithm for colored de Bruijn graphs.Algorithms for molecular biology : AMB · 2024
    Article
  20. 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

10 authors.

Joan Mas-LloretOncology Data Analytics Program, Catalan Institute of Oncology (ICO), Barcelona, Spain.ORCID http://orcid.org/0000-0001-6484-3937
Mireia Obón-SantacanaOncology Data Analytics Program, Catalan Institute of Oncology (ICO), Barcelona, Spain.
Gemma Ibáñez-SanzOncology Data Analytics Program, Catalan Institute of Oncology (ICO), Barcelona, Spain.ORCID http://orcid.org/0000-0001-6071-7343
Elisabet GuinóOncology Data Analytics Program, Catalan Institute of Oncology (ICO), Barcelona, Spain.
Miguel L PatoCancer Epigenetics and Biology Program (PEBC), Bellvitge Biomedical Biomedical Research Institute (IDIBELL), Barcelona, Catalonia, Spain.ORCID http://orcid.org/0000-0001-8840-7259
Francisco Rodriguez-MorantaGastroenterology Department, Bellvitge University Hospital-IDIBELL, Hospitalet de Llobregat, Barcelona, Spain.
Alfredo MataDigestive System Service, Moisés Broggi Hospital, Sant Joan Despí, Spain.
Ana García-RodríguezEndoscopy Unit, Digestive System Service, Viladecans Hospital-IDIBELL, Viladecans, Spain.
Victor MorenoOncology Data Analytics Program, Catalan Institute of Oncology (ICO), Barcelona, Spain. v.moreno@iconcologia.net.ORCID http://orcid.org/0000-0002-2818-5487
Ville Nikolai PimenoffOncology Data Analytics Program, Catalan Institute of Oncology (ICO), Barcelona, Spain. ville.pimenoff@ki.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The gut microbiome has a fundamental role in human health and disease. However, studying the complex structure and function of the gut microbiome using next generation sequencing is challenging and prone to reproducibility problems. Here, we obtained cross-sectional colon biopsies and faecal samples from nine participants in our COLSCREEN study and sequenced them in high coverage using Illumina pair-end shotgun (for faecal samples) and IonTorrent 16S (for paired feces and colon biopsies) technologies. The metagenomes consisted of between 47 and 92 million reads per sample and the targeted sequencing covered more than 300 k reads per sample across seven hypervariable regions of the 16S gene. Our data is freely available and coupled with code for the presented metagenomic analysis using up-to-date bioinformatics algorithms. These results will add up to the informed insights into designing comprehensive microbiome analysis and also provide data for further testing for unambiguous gut microbiome analysis.

Indexed as

ColonFecesCross-Sectional StudiesFemaleGastrointestinal MicrobiomeHigh-Throughput Nucleotide SequencingHumansMaleMetagenomicsRNA, Ribosomal, 16SRNA, Ribosomal, 16S

Identifiers

PMID32179734
PMCPMC7075950

What OpenQuestion 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 OpenQuestion graph.