scCAMEL
Pip installation via: https://pypi.org/project/scCAMEL/
Author: Yizhou Hu, YZstudio, Patrik Ernfors lab, Department of Medical Biochemistry and Biophysics, Karolinska Institutet
Reference of scCAMEL-SWAPLINE package: Hu Y.#, Jiang Y.#, Behnan J., Ribeiro MM., Kalantzi C., Zhang M., Lou D., Häring M., Sharma N., Okawa S., Del Sol A., Adameyko I., Svensson M., Persson O., Ernfors P., “Neural-network learning defines glioblastoma features to be of neural crest perivascular or radial glia lineages”, Science Advances, 2022 Jun 10;8(23) https://www.science.org/doi/10.1126/sciadv.abm6340
Content:
- Installation
- Tutorials_scCAMEL_SWAPLINEv2
- Tutorials_scCAMEL-SWAPLINE_SensoryNeurons_Training-SharmaMouse_Predict_ZeiselMouse
- Training
- Prefiltering_and_SelectFeatures
- Neural-Network learning
- Accuracy plot, the overall clustering accuracy is ~85%
- Make predition and visualization in Radar plot
- permutation control
- Cluster consistency and accuracy
- Cell_Type Purity
- association between cell-types
- Save data
- Prediction
- ZeiselMouse_cluster
- Save data
- Tutorials_scCAMEL-SWAPLINE_mouseDentateGyrus_humanGlioblastoma
- Tutorials_scCAMEL-SWAPLINEv1_LiverMacrophage
- Accuracy plot, the overall clustering accuracy is ~85%
- Tutorials_scCAMEL-SWAPLINE_SensoryNeurons_Training-SharmaMouse_Predict_ZeiselMouse
- Tutorials_scCAMEL_EVO
- Tutorials_scCAMEL_VICUNA
- Reference