Scaden Changelog

Version 1.1.2

  • Changed datatype for data simulation back to float32

Version 1.1.1

  • Fixed bugs in scaden model definition [#88]
  • removed installation instructions for bioconda as not functional at the moment [#86]
  • Fixed bug in scaden example [#85]

Version 1.1.0

  • Reduced memory usage of scaden simulate significantly by performing simulation for one dataset at a time.
  • Using .h5ad format to store simulated data
  • Allow reading data in .h5ad format for improved performance (courtesy of @eboileau)
  • Improved logging and using rich progress bar for training
  • Gene subsetting is now done only when merging datasets, which will allow to generate different combinations of simulated datasets
  • Added scaden merge command which allows merging of previously created datasets

Version 1.0.2

  • General improvement of logging using the 'rich' library for colorized output
  • Added verification check for '--train_datasets' parameter to notify user of unavailable datasets

Version 1.0.1

  • Made identification of datasets more robust to fix issue #66

Version 1.0.0

  • Rebuild Scaden model and training to use TF2 Keras API instead of the old compatibility functions
  • added scaden example command which allows to generate example data for test-running scaden and to inpstec the expected file format
  • added more tests and checks input reading function in scaden simulate
  • fixed bug in reading input data

Version 0.9.6

  • fixed Dockerfile (switched to pip installation)
  • added better error messages to simulate command
  • cleaned up dependencies


  • added --seed parameter to allow reproducible Scaden runs
  • added scaden simulate command to perform bulk simulation and training file creation
  • changed CLI calling


  • fixed dependencies (added python>=3.6 requirement)


  • upgrade to tf2
  • cleaned up dependencies


  • small code refactoring
  • RAM usage improvement


  • added automatic removal of duplicate genes
  • changed name of prediction file


Initial release of the Scaden deconvolution package.


  • scaden process: Process a training dataset for training
  • scaden train: Train a Scaden model
  • scaden predict: Predict cell type compositions of a given sample