{"paper_id":"3b3c9ec2-a71e-4bbc-bbd6-17f85c1553a8","body_text":"Abstract\nSummary 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.\nAvailability and Implementation EMTscore 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.\nContact Tian Hong (hong{at}utdallas.edu)\nCompeting Interest Statement\nThe authors have declared no competing interest.","source_license":"CC-BY-4.0","license_restricted":false}