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March 3, 20260 citationsOpen Access

EMTscore infers divergent EMT pathways from omics data and enables rapid screening for correlated gene sets

HWHaimei WenThe University of Texas at DallasLBLeonidas BlerisThe University of Texas at DallasTHTian HongThe University of Texas at Dallas

Key Points

  • EMTscore enables effective scoring of epithelial-mesenchymal transition pathways, enhancing understanding of cancer progression.
  • Using omics data, EMTscore revealed significant correlations within gene sets associated with EMT processes.
  • The approach utilizes unbiased scoring methods for both single-cell and bulk omics analyses, supporting diverse applications.
  • Further development is needed to assess the clinical relevance of findings in broader patient populations.

Abstract

Quantitative analyses of epithelial-mesenchymal transition (EMT) have been widely used in several areas of biomedical sciences due to its importance in development and cancer progression, but its multi-contextual nature requires standardization and implementation of gene set scoring methods beyond capacities of conventional tools. We developed EMTscore, a package that provides an efficient implementation of unbiased scoring methods for multiple EMT pathways using individual single-cell or bulk omics data, and the package allows rapid screening for relationships between EMT and other cellular processes.

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Cite This Study

Wen et al. (2026) studied this question.

synapsesocial.com/papers/69a75f3ac6e9836116a2a74ehttps://doi.org/10.64898/2026.01.27.702045
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