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

Author:

Hirsch Pascal1ORCID,Molano Leidy-Alejandra G1,Engel Annika1ORCID,Zentgraf Jens23,Rahmann Sven2,Hannig Matthias4,Müller Rolf567,Kern Fabian15ORCID,Keller Andreas157ORCID,Schmartz Georges P1ORCID

Affiliation:

1. Chair for Clinical Bioinformatics, Saarland University , 66123 Saarbrücken, Germany

2. Algorithmic Bioinformatics, Center for Bioinformatics Saar and Saarland University, Saarland Informatics Campus , 66123 Saarbrücken, Germany

3. Saarbrücken Graduate School of Computer Science, Saarland Informatics Campus , 66123 Saarbrücken, Germany

4. Clinic of Operative Dentistry, Periodontology and Preventive Dentistry, Saarland University Hospital, Saarland University , Kirrberger Str. 100 , Building 73, 66421  Homburg , Saar, Germany

5. Helmholtz Institute for Pharmaceutical Research Saarland (HIPS), Helmholtz Centre for Infection Research , 66123 Saarbrücken, Germany

6. Deutsches Zentrum für Infektionsforschung (DZIF) , Standort Hannover-Braunschweig, 38124  Braunschweig , Germany

7. PharmaScienceHub , 66123 Saarbrücken, Germany

Abstract

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.

Funder

DFG

European Health and Digital Executive Agency

Marie Skłodowska-Curie COFUND-Action of the European Commission

Publisher

Oxford University Press (OUP)

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