CytoDx

CytoDx predicts clinical outcomes from flow cytometry and mass cytometry data using a gating-free analytical framework that operates directly on high-dimensional single-cell measurements.

Key Features:

• Gating-Free Analysis: Performs clinical outcome prediction without manual or algorithmic gating of cytometry cell populations.
• Single-Cell Data Aggregation: Aggregates high-dimensional single-cell measurements into structured predictors for statistical and machine-learning models.
• High-Dimensional Cytometry Support: Analyzes datasets generated from flow cytometry and mass cytometry platforms.
• Robustness to Batch Variation: Maintains predictive performance across heterogeneous datasets with substantial batch and instrument effects.
• Cell-State Distribution Modeling: Captures subtle shifts in immunological cell-state distributions that may be lost in population-level gating analyses.

Scientific Applications:

• Clinical Outcome Prediction: Predicts clinical phenotypes and responses using single-cell cytometry measurements.
• Immunological Profiling: Identifies immune cell-state patterns associated with clinical outcomes.
• Vaccine Response Prediction: Analyzes cytometry datasets to predict vaccine responsiveness across heterogeneous cohorts.

Methodology:

CytoDx aggregates high-dimensional single-cell measurements from flow cytometry or mass cytometry datasets into structured predictors and applies statistical or machine-learning models to associate cytometric phenotypes with clinical outcomes without performing cell population gating.