Innate immune responsiveness predicts both enhanced cellular immunity and symptomatic disease after controlled human influenza infection
This dataset contains processed multi-omics data and trained models used for integrative analysis of the H3N2 influenza challenge study using the MEFISTO framework. MEFISTO (Multi-omics Factor Analysis with Interpolation for Spatial and Temporal Outcomes) is a Gaussian process factor analy
This dataset contains processed multi-omics data and trained models used for integrative analysis of the H3N2 influenza challenge study using the MEFISTO framework.
MEFISTO (Multi-omics Factor Analysis with Interpolation for Spatial and Temporal Outcomes) is a Gaussian process factor analysis method designed to capture structured variation across time and modalities.
The dataset includes:
– Preprocessed data
– Trained MEFISTO models
– Derived outputs used for downstream analysis and figure generation
The accompanying notebooks (available in the linked GitHub repository) reproduce the full analysis pipeline, including preprocessing, model training, and interpretation of latent factors.
This resource enables reproducibility of the results presented in the associated manuscript.
Related publication for MEFISTO:
https://www.nature.com/articles/s41592-021-01343-9
[Link to manuscript will be added upon publication]
Data is available upon request: Please contact: l[dot]papargyris[at]imperial[dot]ac[dot]uk
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Files are hosted on the source repository. Click download to access the full dataset.