FlowScatt

FlowScatt decouples fluorescence from scattering signals in flow cytometry data to enable volume-independent, more accurate single-cell fluorescence measurements.

Key Features:

• Volume decoupling: Removes the positive correlation between fluorescence and scattering caused by cell volume to produce size-independent fluorescence metrics.
• Scattering decomposition: Decomposes scattering signals into constituent parts to derive a unified estimate of cell volume.
• Fluorescence recalculation: Recalculates fluorescence values based on a unified cell volume to yield volume-normalized fluorescence measurements.
• Flow cytometry compatibility: Operates on fluorescence and scattering measurements typical of flow cytometry single-cell data.
• Accuracy and precision improvement: Improves the reliability of fluorescence as an independent metric for cellular characterization by removing volume-related artifacts.
• Validation data: Uses experimental data sets for validation of its methodology.
• Implementation: Implemented in Python.

Scientific Applications:

• Volume-independent fluorescence analysis: Enables comparison of fluorescence across cells without confounding by cell size or shape.
• Single-cell performance characterization: Supports high-precision single-cell performance characterization in flow cytometry studies.
• Cytometry and single-cell analysis: Enhances robustness and interpretability of cellular property measurements derived from flow cytometry.

Methodology:

Decomposes scattering signals into constituent parts, derives a unified cell volume from that decomposition, and recalculates fluorescence values based on the unified volume; implemented in Python and validated with experimental data sets.