GateFinder

GateFinder identifies optimal sequences of two-marker polygon gates on two-dimensional scatter plots to isolate and enrich target cell populations from high-parameter single-cell datasets for validation with lower-parameter assays.

Key Features:

• Simplified enrichment strategy: Enables isolation and enrichment of specific cell populations from high-dimensional single-cell data using stepwise gating.
• Stepwise polygon gates: Constructs a sequence of polygonal gates that operate on two-dimensional scatter plots using only two markers per gate.
• Cluster-membership driven selection: Analyzes a vector of cluster memberships to guide identification of gates that enrich the target cell type.
• Compatibility with high-parameter data: Leverages high-parameter single-cell technologies as the input basis for deriving lower-parameter gating strategies.

Scientific Applications:

• Efficient assay design: Supports design of lower-parameter validation assays by providing simple gating sequences to enrich target populations.
• Novel biomarker discovery: Facilitates isolation of specific cell subsets to enable downstream identification of candidate biomarkers.
• Clarification of biological mechanisms: Aids investigation of cellular heterogeneity and distinct cell types through targeted enrichment.

Methodology:

GateFinder analyzes a vector of cluster memberships and identifies an optimal sequence of polygonal gates on 2D scatter plots, each gate defined by two markers, to isolate the desired cell type.