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Background <p>Understanding the molecular interactions between cells, tissues or organs is key to understanding the functioning of a biological system as a whole.</p> Results <p>Here, we propose <i>crossWGCNA</i>: a co-expression-based method that identifies highly interacting genes unbiasedly and that we employ to study stroma-epithelium communication in breast cancer. CrossWGCNA can be applied to bulk, single cell and spatial transcriptomics data. We validate it both in silico and experimentally, and we provide a fully documented R package allowing users to employ it.</p> Conclusions <p>The wide applicability and agnostic nature of our tool make it complementary to existing methods overcoming the limitations arising from strong baseline assumptions.</p> Graphical Abstract <p></p>

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Cross-tissue gene expression interactions from bulk, single cell and spatial transcriptomics with crossWGCNA

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月1日

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  • Aurora Savino,
  • Raffaele M. Iannuzzi,
  • Lidia Avalle,
  • Andrea Lobascio,
  • Francesco Iorio,
  • Paolo Provero,
  • Valeria Poli

摘要

Background

Understanding the molecular interactions between cells, tissues or organs is key to understanding the functioning of a biological system as a whole.

Results

Here, we propose crossWGCNA: a co-expression-based method that identifies highly interacting genes unbiasedly and that we employ to study stroma-epithelium communication in breast cancer. CrossWGCNA can be applied to bulk, single cell and spatial transcriptomics data. We validate it both in silico and experimentally, and we provide a fully documented R package allowing users to employ it.

Conclusions

The wide applicability and agnostic nature of our tool make it complementary to existing methods overcoming the limitations arising from strong baseline assumptions.

Graphical Abstract