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.

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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
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article

Comprehensive analysis of multi-omics vaccine response data using MOFA and Stabl algorithms

Holden T. Maecker, Koji Abe, Amod Gupta
Frontiers in Bioinformatics
vaccines and immunoinformatics approaches
article

Comprehensive analysis of multi-omics vaccine response data using MOFA and Stabl algorithms

Holden T. Maecker, Koji Abe, Amod Gupta
article en

Abstract

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.

Frontiers in BioinformaticsVol. 5
Institute of Infection and Immunity (CA)
Openalex Percentile: Top 70%
vaccines and immunoinformatics approaches
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