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

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Content:

Contents:

• 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
    • Training
    • Prefiltering_and_SelectFeatures
    • Neural-Network learning
    • Accuracy plot, the overall clustering accuracy is ~95%
    • Make predition and visualization in Radar plot
    • permutation control
    • Cell_Type Purity
    • association between cell-types
    • Save data
    • Prediction
    • Couturier2020_humanGlioblastoma
    • Save data
  • Tutorials_scCAMEL-SWAPLINEv1_LiverMacrophage
  • Accuracy plot, the overall clustering accuracy is ~85%
• Tutorials_scCAMEL_EVO
• Tutorials_scCAMEL_VICUNA
• Reference