Reproducible Exploration of Disease Maps with Galaxy Workflows and the MINERVA Platform

Helena Rasche; Matti Hoch; Julia Scheel; Saskia Hiltemann; Martina Kutmon; Chris T. Evelo; Iacopo Cristoferi; Myrthe van Baardwijk; Andrew Stubbs; Marek Ostaszewski

doi:10.20944/preprints202403.1211.v1

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preprints.org > computer science and mathematics > mathematical and computational biology > doi: 10.20944/preprints202403.1211.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Reproducible Exploration of Disease Maps with Galaxy Workflows and the MINERVA Platform

Version 1 : Received: 20 March 2024 / Approved: 20 March 2024 / Online: 20 March 2024 (13:30:14 CET)

How to cite: Rasche, H.; Hoch, M.; Scheel, J.; Hiltemann, S.; Kutmon, M.; Evelo, C.T.; Cristoferi, I.; van Baardwijk, M.; Stubbs, A.; Ostaszewski, M. Reproducible Exploration of Disease Maps with Galaxy Workflows and the MINERVA Platform. Preprints 2024, 2024031211. https://doi.org/10.20944/preprints202403.1211.v1 Rasche, H.; Hoch, M.; Scheel, J.; Hiltemann, S.; Kutmon, M.; Evelo, C.T.; Cristoferi, I.; van Baardwijk, M.; Stubbs, A.; Ostaszewski, M. Reproducible Exploration of Disease Maps with Galaxy Workflows and the MINERVA Platform. Preprints 2024, 2024031211. https://doi.org/10.20944/preprints202403.1211.v1

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MDPI and ACS Style

Rasche, H.; Hoch, M.; Scheel, J.; Hiltemann, S.; Kutmon, M.; Evelo, C.T.; Cristoferi, I.; van Baardwijk, M.; Stubbs, A.; Ostaszewski, M. Reproducible Exploration of Disease Maps with Galaxy Workflows and the MINERVA Platform. Preprints 2024, 2024031211. https://doi.org/10.20944/preprints202403.1211.v1

APA Style

Rasche, H., Hoch, M., Scheel, J., Hiltemann, S., Kutmon, M., Evelo, C.T., Cristoferi, I., van Baardwijk, M., Stubbs, A., & Ostaszewski, M. (2024). Reproducible Exploration of Disease Maps with Galaxy Workflows and the MINERVA Platform. Preprints. https://doi.org/10.20944/preprints202403.1211.v1

Chicago/Turabian Style

Rasche, H., Andrew Stubbs and Marek Ostaszewski. 2024 "Reproducible Exploration of Disease Maps with Galaxy Workflows and the MINERVA Platform" Preprints. https://doi.org/10.20944/preprints202403.1211.v1

Abstract

Visual exploration of complex data helps interpretation, especially in the case of omics data analysis in life sciences and clinical research. Generating and analysing omics data requires bioinformatic skills, while they are interpreted by domain experts, for whom parsing large and complex data structures may be challenging. However, outcomes of visual analytics are often difficult to quantify, which emphasises precision and reproducibility, especially for research on human diseases. Here, we propose a workflow combining a reproducible computational environment with a dedicated visualisation functionality for systems biology diagrams. By linking the Galaxy with the MINERVA Platform, we visualise and explore COVID-19 transcriptomic data to demonstrate the utility of our workflow. Visualised data recapitulate findings of the original publication and offer new insights about the COVID-19 pathology. Our results offer a blueprint for quick prototyping of computational workflows that facilitate communication and exploration of complex data in biomedical research.

Keywords

Galaxy workflows
disease maps
visual exploration
systems biomedicine

Subject

Computer Science and Mathematics, Mathematical and Computational Biology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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