Statistical modelling of an outcome variable with integrated multi-omics
Multivariate methods provide a valuable framework for summarizing multi-omics datasets into low-dimensional components suitable for outcome modelling. Even in the presence of non-normal data, these methods offer a promising alternative to high-dimensional univariate approaches.
Authors
- Said el Bouhaddani (ORCID: https://orcid.org/0000-0002-2279-4337)
- Jeanine Houwing-Duistermaat
- Zander Gu
- He Li
Institutions
- University of Leeds (GB)
- Radboud University Nijmegen (NL)
- King Saud bin Abdulaziz University for Health Sciences (SA)
- University Medical Center Utrecht (NL)
- King Abdullah International Medical Research Center (SA)
- MRC Biostatistics Unit (GB)
- Eindhoven University of Technology (NL)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2025-12-24
- DOI
- https://doi.org/10.1186/s12859-025-06349-0
- Primary Topic
- Metabolomics and Mass Spectrometry Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Wellcome Trust
- Scottish Government
- EU Joint Programme – Neurodegenerative Disease Research
- National Institute for Health and Care Research
- King's College London
- European Commission
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek
- Versus Arthritis
- Medical Research Council