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Consensus tissue domain detection in spatial omics data using multiplex image labeling with regional morphology

Harsimran Kaur1,2, Cody N Heiser1,2, Eliot T McKinley1,3

  • 1Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, TN, USA.

Communications Biology
|October 31, 2024
PubMed
Summary

MILWRM is a new Python package for rapid, multi-scale tissue domain detection and annotation. It helps analyze complex spatial molecular data by identifying distinct tissue compartments for better understanding of pathology.

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Genomics

Background:

  • Spatially resolved molecular assays generate high-dimensional data (genetic, transcriptomic, proteomic, epigenetic) in situ.
  • Integrating molecular data with histology is crucial for studying tissue pathology within its microenvironment.
  • Analyzing large, multi-modal spatial datasets requires advanced data science for functional annotation.

Purpose of the Study:

  • To develop a data-driven approach for cross-sample domain detection in multiplex spatial datasets.
  • To present MILWRM (multiplex image labeling with regional morphology), a Python package for multi-scale tissue domain detection and annotation.
  • To enable analysis within and between consensus tissue compartments across high-volume tissue atlasing efforts.

Main Methods:

  • Developed MILWRM, a Python package for rapid, multi-scale tissue domain detection and annotation.
  • Employed spatially-informed clustering across different spatial data modalities and platforms.
  • Applied MILWRM to human colonic polyps, lymph nodes, mouse kidney, and mouse brain slices.

Main Results:

  • Successfully identified histologically distinct compartments in diverse tissue types.
  • Demonstrated MILWRM's utility in analyzing molecular distinctions between human colonic polyp subtypes.
  • Showcased MILWRM's capability to identify anatomical brain regions and their unique molecular profiles.

Conclusions:

  • MILWRM facilitates rapid, multi-scale tissue domain detection and annotation for spatial molecular data.
  • The package aids in elucidating molecular distinctions within and between tissue compartments across various samples and modalities.
  • MILWRM is a valuable tool for advancing studies in tissue pathology, atlasing, and comparative molecular analysis.