EMTscore infers divergent EMT pathways from omics data and enables rapid screening for correlated gene sets
wen, h.; Bleris, L.; Hong, T.
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SummaryQuantitative 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. Availability and ImplementationEMTscore is available from GitHub https://github.com/wenmm/EMTscore under the GNU General Public License, and it will be deposited to Zenodo upon acceptance. It is also under review at Bioconductor. ContactTian Hong (hong@utdallas.edu)
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