iTIME

iTIME characterizes the spatial organization and abundance of immune cells within tumor immune microenvironments using multiplex immunofluorescence (mIF) staining data and quantitative spatial statistics.

Key Features:

• Input data: Uses multiplex immunofluorescence (mIF) staining data combined with quantitative digital image analysis outputs.
• Spatial statistical analyses: Performs univariate and bivariate spatial statistical analyses including Ripley's K, Besag's L, Macdonald's M and G statistics, and nearest neighbor distance calculations.
• Software foundation: Implements analyses via the R package spatialTIME.
• Cell abundance and spatial pattern quantification: Quantifies immune cell abundance and intricate spatial arrangements within tumor samples for prognostic evaluation.
• Clinical integration: Statistically correlates immune cell abundance measures and spatial metrics with patient clinical features.
• Outputs: Produces publication-quality plots depicting the spatial organization of cells within tissue samples.

Scientific Applications:

• Tumor immunology studies: Characterizes spatial immune patterns within tumors to support investigations in cancer immunology.
• Prognostic analyses: Identifies spatial metrics and abundance measures that may relate to prognosis and treatment response.
• Clinical association studies: Enables correlation of TIME characteristics with patient clinical features to inform personalized medicine approaches.

Methodology:

Processes multiplex immunofluorescence (mIF) staining data with quantitative digital image analysis; performs univariate and bivariate spatial statistical analyses using the R package spatialTIME; computes Ripley's K, Besag's L, Macdonald's M and G statistics, and nearest neighbor distance calculations; statistically correlates immune cell abundance and spatial metrics with patient clinical features; generates publication-quality plots.