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Vertical and horizontal integration of multi-omics data with miodin
University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre. (Translationell Bioinformatik)ORCID iD: 0000-0001-9242-4852
2019 (English)In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 20, no 649Article in journal (Refereed) Published
Abstract [en]

Background: Studies on multiple modalities of omics data such as transcriptomics, genomics and proteomics are growing in popularity, since they allow us to investigate complex mechanisms across molecular layers. It is widely recognized that integrative omics analysis holds the promise to unlock novel and actionable biological insights into health and disease. Integration of multi-omics data remains challenging, however, and requires combination of several software tools and extensive technical expertise to account for the properties of heterogeneous data.

Results: This paper presents the miodin R package, which provides a streamlined workflow-based syntax for multi-omics data analysis. The package allows users to perform analysis of omics data either across experiments on the same samples (vertical integration), or across studies on the same variables (horizontal integration). Workflows have been designed to promote transparent data analysis and reduce the technical expertise required to perform low-level data import and processing.

Conclusions: The miodin package is implemented in R and is freely available for use and extension under the GPL-3 license. Package source, reference documentation and user manual are available at https://gitlab.com/algoromics/miodin.

Place, publisher, year, edition, pages
London: BioMed Central, 2019. Vol. 20, no 649
Keywords [en]
Multi-omics, Data analysis, Data integration, Transparency
National Category
Biological Sciences Computer Sciences Bioinformatics and Systems Biology
Research subject
Bioinformatics
Identifiers
URN: urn:nbn:se:his:diva-18026DOI: 10.1186/s12859-019-3224-4ISI: 000511608800001PubMedID: 31823712Scopus ID: 2-s2.0-85076360669OAI: oai:DiVA.org:his-18026DiVA, id: diva2:1380928
Available from: 2019-12-19 Created: 2019-12-19 Last updated: 2020-02-20Bibliographically approved

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Publisher's full textPubMedScopushttps://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-019-3224-4

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