spatialTIME and iTIME: R package and Shiny application for visualization and analysis of immunofluorescence data
Jordan H Creed1, Christopher M Wilson1, Alex C Soupir1,2
1Department of Biostatistics and Bioinformatics, Tampa, FL, USA.
Bioinformatics (Oxford, England)
|November 4, 2021
Summary
New R package spatialTIME and iTIME web app analyze spatial patterns of immune cells in tumor microenvironments. This advances understanding of tumor immunity and prognosis beyond simple cell abundance metrics.
Area of Science:
- Computational Biology
- Bioinformatics
- Cancer Research
Background:
- Multiplex immunofluorescence (mIF) and digital image analysis characterize tumor immune microenvironment (TIME).
- Current methods often focus on immune cell abundance, neglecting crucial spatial patterns.
- Spatial architecture of immune cells is increasingly recognized for its prognostic significance.
Purpose of the Study:
- To develop tools for comprehensive spatial analysis of mIF data.
- To enable characterization of both immune cell abundance and spatial organization within the TIME.
- To provide accessible platforms for researchers to explore TIME spatial data.
Main Methods:
- Development of the R package spatialTIME for spatial statistics (e.g., Ripley's K, Besag's L) and plotting.
- Creation of the iTIME web application for user-friendly analysis and visualization of TIME.
- Integration of abundance measures with clinical features for statistical comparison.
Main Results:
- spatialTIME enables calculation of univariate and bivariate spatial statistics for cell distribution.
- iTIME provides interactive visualization and statistical comparison of TIME characteristics.
- The tools facilitate detailed analysis of immune cell spatial organization in tissue samples.
Conclusions:
- spatialTIME and iTIME address the need for spatial analysis in mIF data.
- These tools enhance the characterization of the tumor immune microenvironment.
- The developed resources support deeper insights into TIME and its prognostic implications.
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