flowDensity

flowDensity automates sequential bivariate gating to identify and quantify cell populations from flow cytometry data for reproducible, high-throughput marker-based analysis.

Key Features:

• Sequential bivariate gating: Implements automated sequential bivariate gates that replicate predefined manual gating strategies to define cell populations from flow cytometry data.
• Optimal cut-off determination: Determines marker-specific cut-offs by analyzing characteristics of the density distribution for each marker.
• Reproducibility and high-throughput analysis: Enables reproducible application of gating across datasets and supports analysis of large volumes of flow cytometry data.

Scientific Applications:

• Immunology: Quantification and characterization of immune cell subsets from flow cytometry experiments.
• Oncology: Identification and quantification of cellular populations in oncology studies using marker-based gating.
• Developmental biology: Analysis of cell population dynamics and phenotypic characterization during development.

Methodology:

Automated sequential bivariate gating using a predefined sequential gating strategy with marker cut-offs determined by density-distribution analysis.