GateFinder: Automated Identification of Simple FACS Signatures from High Dimensional Mass Cytometry

GateFinder is a flexible, automated, objective algorithm that quickly analyzes complex mass cytometry datasets to identify simple signatures (“gates”) for FACS (fluorescent automated cell sorting) purification. Mass cytometry is a powerful tool for identifying novel cell populations with up to 42 markers (parameters) per cell. However, mass cytometry instruments are expensive, the analysis destroys cells, and the resulting high-parameter data is time consuming for humans to interpret. GateFinder provides a bioinformatics tool to interpret mass cytometry data and construct simple phenotypic signatures for target cell populations. These signatures can then be used to guide development of either high-throughput screens or gating strategies for enriching live cells using FACS in a variety of research, clinical or diagnostic applications.

Stage of Research
The inventors have demonstrated the utility of the algorithm on several real-world use cases and will make an R package available for non-commercial users when the work is published.

Enlarge thumbnail figure in the Media section below to see an overview of how the algorithm works and a sample use case on 31-parameter mass cytometry.