Evidence map›Paper›PMID 38716863›Full record

ArticleNucleic acids research2024

Mibianto: ultra-efficient online microbiome analysis through k-mer based metagenomics.

Pascal Hirsch, Leidy-Alejandra G Molano, Annika Engel, Jens Zentgraf, Sven Rahmann, Matthias Hannig, Rolf Müller, Fabian Kern, Andreas Keller, Georges P Schmartz

Abstract read
In one paragraph

Article in Nucleic acids research, 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. Article
  3. Article
  4. Swiftly identifying strongly unique k-mers.Algorithms for molecular biology : AMB · 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.

Pascal HirschChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.ORCID 0000-0003-4152-9931
Leidy-Alejandra G MolanoChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.
Annika EngelChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.ORCID 0000-0001-5570-3115
Jens ZentgrafAlgorithmic Bioinformatics, Center for Bioinformatics Saar and Saarland University, Saarland Informatics Campus, 66123 Saarbrücken, Germany.
Sven RahmannAlgorithmic Bioinformatics, Center for Bioinformatics Saar and Saarland University, Saarland Informatics Campus, 66123 Saarbrücken, Germany.
Matthias HannigClinic of Operative Dentistry, Periodontology and Preventive Dentistry, Saarland University Hospital, Saarland University, Kirrberger Str. 100, Building 73, 66421 Homburg, Saar, Germany.
Rolf MüllerHelmholtz Institute for Pharmaceutical Research Saarland (HIPS), Helmholtz Centre for Infection Research, 66123 Saarbrücken, Germany.
Fabian KernChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.ORCID 0000-0002-8223-3750
Andreas KellerChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.ORCID 0000-0002-5361-0895
Georges P SchmartzChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.ORCID 0000-0002-9627-9223

Funding

DFG 469073465European Health and Digital Executive Agency 101057548-EPIVINFMarie Skłodowska-Curie COFUND-Action of the European Commission
6 · The paper itself

Abstract

Quantifying microbiome species and composition from metagenomic assays is often challenging due to its time-consuming nature and computational complexity. In Bioinformatics, k-mer-based approaches were long established to expedite the analysis of large sequencing data and are now widely used to annotate metagenomic data. We make use of k-mer counting techniques for efficient and accurate compositional analysis of microbiota from whole metagenome sequencing. Mibianto solves this problem by operating directly on read files, without manual preprocessing or complete data exchange. It handles diverse sequencing platforms, including short single-end, paired-end, and long read technologies. Our sketch-based workflow significantly reduces the data volume transferred from the user to the server (up to 99.59% size reduction) to subsequently perform taxonomic profiling with enhanced efficiency and privacy. Mibianto offers functionality beyond k-mer quantification; it supports advanced community composition estimation, including diversity, ordination, and differential abundance analysis. Our tool aids in the standardization of computational workflows, thus supporting reproducibility of scientific sequencing studies. It is adaptable to small- and large-scale experimental designs and offers a user-friendly interface, thus making it an invaluable tool for both clinical and research-oriented metagenomic studies. Mibianto is freely available without the need for a login at: https://www.ccb.uni-saarland.de/mibianto.

Indexed as

MetagenomicsMicrobiotaSoftwareComputational BiologyHigh-Throughput Nucleotide SequencingHumansInternetMetagenomeSequence Analysis, DNAWorkflow

Identifiers

PMID38716863
PMCPMC11223814

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.