ConvexGating infers gating strategies from clusters in single cell cytometry data.

ConvexGating automatically infers interpretable gating strategies with high accuracy for cell sorting from single-cell cytometry data, including unknown populations, enabling practical implementation.

• Why it matters: Manual gating is inconsistent and limited by inter-rater variability and increasing data complexity, hindering reproducibility and scalability in cell population analysis and sorting.
• What they did: ConvexGating employs artificial intelligence to learn gating strategies from clusters in high-dimensional data, validated on known and novel cell types, and adaptable across different cytometry platforms.
• The result: The method produces low-contamination, biologically meaningful sorting strategies, demonstrated through experimental validation and improved marker panel design, facilitating precise cell isolation.