biostudies-literatureUnknown5Gupta A<h4>Introduction</h4>FluPRINT is a multi-omics dataset that measures donors' protein expression and cell counts across various assays. Donors were also assigned a binary value (0 or 1), being labeled as high responders if they had a fold change ≥4 of the antibody titer for hemagglutination inhibition (HAI) from day 0 to day 28, and low responders otherwise (0). In this project, we used the MOFA and Stabl algorithms to analyze FluPRINT, estimate the population structure from the data, and identify the most important features for predicting response to the vaccine.<h4>Methods</h4>The preprocessing of the dataset included removing repeat features, scaling by assay, and removing outliers. Since Stabl does not directly address missing values, features with high amounts of missing values were reFrontiers in bioinformatics1636240https://www.ebi.ac.uk/biostudies/studies/S-EPMC12657425biostudies-literatureComprehensive analysis of multi-omics vaccine response data using MOFA and Stabl algorithms.PMC12657425Gupta AMaecker HTAbe KfalseComprehensive analysis of multi-omics vaccine response data using MOFA and Stabl algorithms.<h4>Introduction</h4>FluPRINT is a multi-omics dataset that measures donors' protein expression and cell counts across various assays. Donors were also assigned a binary value (0 or 1), being labeled as high responders if they had a fold change ≥4 of the antibody titer for hemagglutination inhibition (HAI) from day 0 to day 28, and low responders otherwise (0). In this project, we used the MOFA and Stabl algorithms to analyze FluPRINT, estimate the population structure from the data, and identify the most important features for predicting response to the vaccine.<h4>Methods</h4>The preprocessing of the dataset included removing repeat features, scaling by assay, and removing outliers. Since Stabl does not directly address missing values, features with high amounts of missing values were re2025-01-01T00:00:00Z20252026-05-22T03:26:30.634Z2026-05-22T03:16:15.885ZS-EPMC126574254132205210.3389/fbinf.2025.1636240