Evidence map›Paper›PMID 39333850›Full record

ArticleBMC bioinformatics2024

SpeciateIT and vSpeciateDB: novel, fast, and accurate per sequence 16S rRNA gene taxonomic classification of vaginal microbiota.

Johanna B Holm, Pawel Gajer, Jacques Ravel

Abstract read
In one paragraph

Article in BMC bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Cervicovaginal microbial features predictInfection and immunity · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Observational
  14. Article
  15. Article
  16. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Johanna B HolmDepartment of Microbiology and Immunology, Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
Pawel GajerDepartment of Microbiology and Immunology, Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
Jacques RavelDepartment of Microbiology and Immunology, Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, 21201, USA. jravel@som.umaryland.edu.

Funding

The Effects of Sex Hormones on Chlamydia InfectionU19AI158930 · NIAID · UNIVERSITY OF MARYLAND BALTIMORE · PI CRISS, ALISON K · 2021 to 2025
$7.7M
Integrating multi-omics data: Modeling biomarkers and mechanisms to reduce bacterial vaginosis recurrenceK01AI163413 · NIAID · UNIVERSITY OF MARYLAND BALTIMORE · PI HOLM, JOHANNA B. · 2021 to 2025
$464k
Host-Microbe Interactions and Incident InfectionF32AI136400 · NIAID · UNIVERSITY OF MARYLAND BALTIMORE · PI HOLM, JOHANNA B. · 2018 to 2020
$192k
National Institute of Allergy and Infectious Diseases K01-AI163413National Institute of Allergy and Infectious Diseases U19-AI158930NIAID NIH HHS F32 AI136400NIAID NIH HHS K01 AI163413NIAID NIH HHS U19 AI158930NIH National Institute of Allergy and Infectious Diseases F32-AI136400
6 · The paper itself

Abstract

backgroundClustering of sequences into operational taxonomic units (OTUs) and denoising methods are a mainstream stopgap to taxonomically classifying large numbers of 16S rRNA gene sequences. Environment-specific reference databases generally yield optimal taxonomic assignment.

resultsWe developed SpeciateIT, a novel taxonomic classification tool which rapidly and accurately classifies individual amplicon sequences ( https://github.com/Ravel-Laboratory/speciateIT ). We also present vSpeciateDB, a custom reference database for the taxonomic classification of 16S rRNA gene amplicon sequences from vaginal microbiota. We show that SpeciateIT requires minimal computational resources relative to other algorithms and, when combined with vSpeciateDB, affords accurate species level classification in an environment-specific manner.

conclusionsHerein, two resources with new and practical importance are described. The novel classification algorithm, SpeciateIT, is based on 7th order Markov chain models and allows for fast and accurate per-sequence taxonomic assignments (as little as 10 min for 10

Indexed as

AlgorithmsMicrobiotaRNA, Ribosomal, 16SVaginaDatabases, GeneticFemaleHumansSoftwareRNA, Ribosomal, 16S16S rRNA geneAmplicon sequencingTaxonomic classificationVaginal microbiota

Identifiers

PMID39333850
PMCPMC11437924

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.