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MiBiOmics: an interactive web application for multi-omics data exploration and integration

Authors
  • Zoppi, Johanna1
  • Guillaume, Jean-François2
  • Neunlist, Michel1
  • Chaffron, Samuel2, 3
  • 1 Université de Nantes, Nantes, France , Nantes (France)
  • 2 Université de Nantes, Nantes, 44000, France , Nantes (France)
  • 3 Research Federation (FR2022) Tara Oceans GO-SEE, Paris, France , Paris (France)
Type
Published Article
Journal
BMC Bioinformatics
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Jan 06, 2021
Volume
22
Issue
1
Identifiers
DOI: 10.1186/s12859-020-03921-8
Source
Springer Nature
Keywords
License
Green

Abstract

BackgroundMulti-omics experimental approaches are becoming common practice in biological and medical sciences underlining the need to design new integrative techniques and applications to enable the multi-scale characterization of biological systems. The integrative analysis of heterogeneous datasets generally allows to acquire additional insights and generate novel hypotheses about a given biological system. However, it can become challenging given the often-large size of omics datasets and the diversity of existing techniques. Moreover, visualization tools for interpretation are usually non-accessible to biologists without programming skills.ResultsHere, we present MiBiOmics, a web-based and standalone application that facilitates multi-omics data visualization, exploration, integration, and analysis by providing easy access to dedicated and interactive protocols. It implements classical ordination techniques and the inference of omics-based (multilayer) networks to mine complex biological systems, and identify robust biomarkers linked to specific contextual parameters or biological states.ConclusionsMiBiOmics provides easy-access to exploratory ordination techniques and to a network-based approach for integrative multi-omics analyses through an intuitive and interactive interface. MiBiOmics is currently available as a Shiny app at https://shiny-bird.univ-nantes.fr/app/Mibiomics and as a standalone application at https://gitlab.univ-nantes.fr/combi-ls2n/mibiomics.

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