SAPHIR

SAPHIR performs histo-cytometry analysis and visualization of segmented immunofluorescence tissue-section images acquired by confocal, spectral, or multiplex imaging to characterize cell phenotypes, counts, spatial distribution, and interactions.

Key Features:

• Scatterplot Representation: Generates scatterplots from segmentation-derived multi-parameter measurements to visualize cell-level attributes.
• Data Filtering: Filters spurious data points to improve integrity of downstream analyses.
• Cell Subset Selection: Enables selection of specific cell subsets on scatterplots for focused analysis of cellular populations within tissue samples.
• Interactive Visualization: Maps selected data back onto the original images to provide spatial context for analyzed cells.
• Statistical Analysis: Performs statistical analysis of selected data points to quantify phenotypes, cell numbers, and spatial relationships.
• Data Annotation: Supports annotation of analyzed cells and regions within image-based datasets.

Scientific Applications:

• Basic research: Characterizes labeled cell phenotypes and population heterogeneity within tissue sections.
• Medical research: Quantifies cell numbers and spatial distributions in pathological or treatment-response studies.
• Spatial interaction analysis: Examines proximities and interactions between different cell types within tissue architecture.
• Multiparametric image analysis: Integrates spectral or multiplex imaging outputs to analyze high-dimensional immunofluorescence data.

Methodology:

Processes segmented image data from confocal, spectral, or multiplex imaging to extract multi-parameter measurements, generate scatterplots, apply data filtering, allow scatterplot-based subset selection, map selections back onto images for spatial context, perform statistical analyses, and support annotation.