Release notes¶
v0.2.3¶
Minor improvements and bug fixes
Bug fixes:
Data frame in
obsm
no longer triggers an error during model training (Resolves #32).
Enhancements:
scglue.data.transfer_labels uses a new strategy with SNN-based estimation of transfer confidence (Resolves #23).
Allow setting custom bedtools path via scglue.config.BEDTOOLS_PATH (Resolves #22).
v0.2.2¶
Minor improvements and bug fixes
Bug fixes:
Device detection is now more reliable (Resolves #17).
Enhancements:
Custom encoders and decoders can now be registered without changing package code (Resolves #14).
v0.2.1¶
Minor improvements and dependency fixes
v0.2.0¶
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_datasetAdded a model diagnostics metric “integration consistency score”
Enhancements:
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:
A partially paired GLUE model for utilizing paired cells whenever available
The CLUE model that won the NeurIPS 2021 competition in multimodal integration is here!
v0.1.1¶
First public release