Available Resources

• ODNN ^{(https://github.com/BooneAndrewsLab/ODNN.git)}
  - Scripts for data pre-processing, running supervised two hidden-layer fully connected neural network for single cell classification, and penetrance calculation
  - "Systematic genetics and single‐cell imaging reveal widespread morphological pleiotropy and cell‐to‐cell variability" Mattiazzi Usaj M, Sahin N, Friesen H, Pons C, Usaj M, Masinas MPD, Shuteriqi E, Shkurin A, Aloy P, Morris Q, Boone C, Andrews BJ. Molecular Systems Biology (2020) 16:e9243 https://doi.org/10.15252/msb.20199243
• One-Class SVM ^{(https://github.com/BooneAndrewsLab/ocSVM.git)}
  - Outlier Detection with One-Class SVM
  - "Systematic genetics and single‐cell imaging reveal widespread morphological pleiotropy and cell‐to‐cell variability" Mattiazzi Usaj M, Sahin N, Friesen H, Pons C, Usaj M, Masinas MPD, Shuteriqi E, Shkurin A, Aloy P, Morris Q, Boone C, Andrews BJ. Molecular Systems Biology (2020) 16:e9243 https://doi.org/10.15252/msb.20199243
• Single Cell Labeling Tool ^{(https://github.com/BooneAndrewsLab/singlecelltool)}
  - Custom-made graphical user interface (GUI) application that allows users to view and label single cell images in a grid layout. Users can save a phenotype for each cell and then export the data.
  - "Systematic genetics and single‐cell imaging reveal widespread morphological pleiotropy and cell‐to‐cell variability" Mattiazzi Usaj M, Sahin N, Friesen H, Pons C, Usaj M, Masinas MPD, Shuteriqi E, Shkurin A, Aloy P, Morris Q, Boone C, Andrews BJ. Molecular Systems Biology (2020) 16:e9243 https://doi.org/10.15252/msb.20199243
• DeepLoc ^{(https://github.com/okraus/DeepLoc)}
  - Contains the code, pretrained models, and datasets for the paper: "Automated analysis of high-content microscopy data with deep learning" Kraus, O.Z., Grys, B.T., Ba, J., Chong, Y., Frey, B.J., Boone, C., Andrews, B.J. Molecular Systems Biology 13.4 (2017): 924. http://msb.embopress.org/content/13/4/924