Evidence map›Paper›PMID 38605417›Full record

ArticleGenome biology2024

Scoary2: rapid association of phenotypic multi-omics data with microbial pan-genomes.

Thomas Roder, Grégory Pimentel, Pascal Fuchsmann, Mireille Tena Stern, Ueli von Ah, Guy Vergères, Stephan Peischl, Ola Brynildsrud, Rémy Bruggmann, Cornelia Bär

Abstract read
In one paragraph

Article in Genome biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
  2. A community-based One Health approach to the pandemic dynamics ofAntimicrobial agents and chemotherapy · 2026
    Article
  3. Article
  4. Convergent evolution of ST2 and ST164 mediates dissemination of the blaAnnals of clinical microbiology and antimicrobials · 2026
    Article
  5. Exploring clonality ofMicrobiology spectrum · 2026
    Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Towards a holistic epidemiology ofFrontiers in bioinformatics · 2026
    Article
  12. Article
  13. Discovery and genomics of HISME communications · 2026
    Article
  14. Review
  15. Pangenome-GWAS analysis ofCanadian journal of microbiology · 2026
    Article
  16. Genomic Insights intoPathogens (Basel, Switzerland) · 2025
    Article
  17. Review
  18. bioRxiv : the preprint server for biology · 2025
    Article
  19. Review
  20. Applied and environmental microbiology · 2025
    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.

Thomas RoderInterfaculty Bioinformatics Unit and Swiss Institute of Bioinformatics, University of Bern, Bern, CH-3012, Switzerland.
Grégory PimentelMethods development and analytics, Agroscope, Schwarzenburgstrasse 161, Bern, CH-3003, Switzerland.
Pascal FuchsmannFood microbial systems, Agroscope, Schwarzenburgstrasse 161, Bern, CH-3003, Switzerland.
Mireille Tena SternFood microbial systems, Agroscope, Schwarzenburgstrasse 161, Bern, CH-3003, Switzerland.
Ueli von AhFood microbial systems, Agroscope, Schwarzenburgstrasse 161, Bern, CH-3003, Switzerland.
Guy VergèresFood microbial systems, Agroscope, Schwarzenburgstrasse 161, Bern, CH-3003, Switzerland.
Stephan PeischlInterfaculty Bioinformatics Unit and Swiss Institute of Bioinformatics, University of Bern, Bern, CH-3012, Switzerland.
Ola BrynildsrudNorwegian Institute of Public Health, Oslo and Norwegian University of Life Science, Ås, Norway.
Rémy Bruggmann *Interfaculty Bioinformatics Unit and Swiss Institute of Bioinformatics, University of Bern, Bern, CH-3012, Switzerland. remy.bruggmann@unibe.ch.ORCID 0000-0001-5629-6363
Cornelia Bär *Methods development and analytics, Agroscope, Schwarzenburgstrasse 161, Bern, CH-3003, Switzerland.

Funding

Gebert Rüf Stiftung GRS-070/17
6 · The paper itself

Abstract

Unraveling bacterial gene function drives progress in various areas, such as food production, pharmacology, and ecology. While omics technologies capture high-dimensional phenotypic data, linking them to genomic data is challenging, leaving 40-60% of bacterial genes undescribed. To address this bottleneck, we introduce Scoary2, an ultra-fast microbial genome-wide association studies (mGWAS) software. With its data exploration app and improved performance, Scoary2 is the first tool to enable the study of large phenotypic datasets using mGWAS. As proof of concept, we explore the metabolome of yogurts, each produced with a different Propionibacterium reichii strain and discover two genes affecting carnitine metabolism.

Indexed as

Genome-Wide Association StudyMultiomicsGenes, BacterialGenomicsPhenotypeBacteriaBGWAFermented foodGenotype-phenotype associationGWASMetaboliteMicrobial genome-wide association studiesOmicsPan-genomeProkaryote

Identifiers

PMID38605417
PMCPMC11007987

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.