Single-cell proteomic data from a controlled human influenza challenge study. The dataset was created by Klodiana Rizzo Nervo and published on figshare in March 2026. It contains immune cell profiles used to train random forest models for predicting infection timing and shedding status.
Use Cases
- Training predictive models for infection timing based on immune population dynamics.
- Developing classifiers to distinguish virus shedders from non-shedders based on immune profiles.
- Validating immune-based temporal biomarkers across independent challenge cohorts.
- Analyzing longitudinal immune cell subset changes following influenza exposure.
Strengths
- Data originates from a controlled human challenge study, providing a structured experimental context.
- Models were independently validated using data from a separate challenge study.
- Profiling was done using 42-marker mass cytometry panels, suggesting high-dimensional measurements.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- The dataset is very small (106.0 B), indicating limited scope.
Provenance
- Source
- Klodiana Rizzo Nervo
- Collection Method
- Data from a controlled human challenge with influenza A/California/2009 (H1N1), profiled longitudinally using mass cytometry.
- Freshness
- Last updated 2026-03-19 08:43:39