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Updated: Sep 17, 2025

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq
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Cross-tissue gene expression interactions from bulk, single cell and spatial transcriptomics with crossWGCNA.

Aurora Savino1,2, Raffaele M Iannuzzi3, Lidia Avalle4

  • 1Molecular Biotechnology Center, Department of Molecular Biotechnology and Health Sciences, University of Turin, Via Nizza 52, Turin, 10126, Italy. aurora.savino@unito.it.

BMC Genomics
|July 2, 2025
PubMed
Summary

We developed crossWGCNA, a novel gene co-expression method to unbiasedly identify interacting genes. This tool aids in understanding complex biological systems, such as stroma-epithelium communication in breast cancer.

Keywords:
Breast cancerCell–cell communicationCo-expression networksLaser capture microdissectionSpatial transcriptomicsTumor microenvironment

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Area of Science:

  • Molecular biology
  • Systems biology
  • Bioinformatics

Background:

  • Understanding molecular interactions is crucial for deciphering biological system functions.
  • Cell-cell and tissue-level communication are fundamental to biological processes.

Purpose of the Study:

  • To introduce crossWGCNA, a novel co-expression-based method for unbiased identification of highly interacting genes.
  • To apply crossWGCNA to investigate stroma-epithelium communication in breast cancer.

Main Methods:

  • Cross-correlation weighted gene co-expression network analysis (crossWGCNA).
  • Application to bulk, single-cell, and spatial transcriptomics data.
  • In silico and experimental validation of the method.

Main Results:

  • CrossWGCNA effectively identifies highly interacting genes without bias.
  • The method was successfully applied to study stroma-epithelium interactions in breast cancer.
  • A fully documented R package is available for user implementation.

Conclusions:

  • CrossWGCNA offers wide applicability across various transcriptomic data types.
  • The agnostic nature of crossWGCNA complements existing methods by overcoming baseline assumption limitations.