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Related Experiment Video

Updated: Jul 21, 2025

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy

Published on: June 15, 2022

DIMPLE: AN R PACKAGE TO QUANTIFY, VISUALIZE, AND MODEL SPATIAL CELLULAR INTERACTIONS FROM MULTIPLEX IMAGING WITH

Maria Masotti¹, Nathaniel Osher¹, Joel Eliason²

¹University of Michigan Department Biostatistics.

Biorxiv : the Preprint Server for Biology

|July 28, 2023

Summary

A new R package, DIMPLE, offers a scalable framework to analyze cell-cell interactions within the tumor microenvironment (TME). This tool aids in understanding how these interactions impact tumor development and drug resistance, using advanced imaging data.

Keywords:

Multiplex Imaging Point Process Spatial Statistics

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Last Updated: Jul 21, 2025

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Area of Science:

Oncology
Computational Biology
Bioinformatics

Background:

The tumor microenvironment (TME) is a complex system of cells, vessels, and matrix crucial for tumor progression.
Multiplexed imaging enables high-resolution spatial mapping of cellular phenotypes within the TME.
Existing statistical methods struggle to analyze the vast data from advanced TME imaging.

Approach:

We developed DIMPLE, a scalable analytical framework and R package.
DIMPLE quantifies, visualizes, and models cell-cell interactions in the TME.
The framework is designed to handle large datasets from advanced imaging technologies.

Key Points:

DIMPLE effectively analyzes complex cell-cell interactions in multiplexed imaging data.
The R package provides a scalable solution for TME data analysis.
Application of DIMPLE identified significant associations between TME interactions and patient covariates.

Conclusions:

DIMPLE offers a powerful new tool for researchers studying the TME.
The framework facilitates deeper insights into the role of cellular interactions in tumor biology and drug resistance.
This approach enhances the utility of high-resolution imaging data in cancer research.