Release notes


Minor improvements and dependency fixes


New features:

  • Added fit_SCGLUE function to simplify model training - Incorporates weighted adversarial alignment by default, with increased robustness on datasets with highly-skewed cell type compositions

  • Added support for batch effect correction, which can be activated by setting use_batch in configure_dataset

  • Added a model diagnostics metric “integration consistency score”


  • Support for training directly on disk-backed AnnData objects, scaling to almost infinite number of cells

Bug fixes:

  • Fixed a bug where the graph dataset was not shuffled across epochs

Experimental features:


First public release