Comprehensive analysis of multi-omics vaccine response data using MOFA and Stabl algorithms
Our research addresses a key knowledge gap: understanding how these fundamentally different analytical approaches perform when analyzing the same complex dataset. Our exploration evaluates their respective strengths, limitations, and biological insights and provides guidance on using MOFA and Stabl to find the best predictive cell subsets and features for understanding large immunological multi-omics data. The code for this project can be found at https://github.com/aanya21gupta/fluprint.
Authors
- Holden T. Maecker (ORCID: https://orcid.org/0000-0003-0795-9946)
- Koji Abe (ORCID: https://orcid.org/0000-0002-1670-0904)
- Amod Gupta (ORCID: https://orcid.org/0000-0001-8427-5738)
Institutions
- Institute of Infection and Immunity (CA)
Publication Details
- Journal
- Frontiers in Bioinformatics
- Published
- 2025-11-13
- DOI
- https://doi.org/10.3389/fbinf.2025.1636240
- Primary Topic
- vaccines and immunoinformatics approaches
- Type
- article
- Field-Weighted Citation Impact
- 0.00