The code provided is the one used for the 3 class classification and the T-SNE visualization. Apart from it, there is also the .yml file with the local environment required. To run the MorphologyClassification_tSNE.py script, it must be opened in some coding editor such as Visual Studio. The input to start the classifier are the paths to the training data files, the classification data path and the path where the result will be saved. To run MorphologyClassification_tSNE.py, it must be provided the classification result for each media culture (FM, TGFB) and the training set directory. Along execution of the code T-SNE projections will pop-up. - The file Training_set.csv corresponds to th data to train the SVM classifier with data inclunding the media (FM/TGFB) variable. - PDAC93_Raw_Data.tsv is the data to be classified. As the classification has already been donde, its result can be seen in the files: Result_FM_2025-03-17, Result_TGFB_2025-03-17.