CellBender 0.3.2 release

This release matches the outputs of v0.3.0, but aims to reduce peak memory usage and fix some bugs. This will hopefully enable users to get away with less RAM (CPU) even when the number of --total-droplets-included gets large (such as overloaded experiments, etc.).

NOTE: v0.3.1 was briefly released and then redacted. If you have an install of v0.3.1, do not use it, as it contains a major bug which was fixed in #347 .

Improvements:

• Make posterior generation more memory efficient

New features:

• WDL workflow updates to facilitate automatic retries on failure
• Added to list of allowed feature types to match 2024.04 CellRanger definitions

Bug fixes:

• Fix bug with MTX inputs for WDL
• Fix Windows bug during posterior generation
• Fix report generation bugs on Mac and Windows

CellBender 0.3.0 release

This release coincides with the publication of our manuscript in Nature Methods. https://doi.org/10.1038/s41592-023-01943-7

Changes from previous versions include:

• Output report in HTML format
• Code produces checkpoints, useful for automatic restarting of WDL workflow without losing progress (enabling use of preemptible GPUs on Terra, and potentially better use of Google Colab GPUs for free)
• Model includes new safeguards on count removal per gene, and treats the construction of the output count matrix as an auxiliary optimization problem
• --expected-cells and --total-droplets-included input arguments are not typically needed, as default behavior is very much improved
• The full posterior gets saved as an output h5 file
• Smoother learning curves and improved performance on tricky samples
• Bug fixes

CellBender 0.2.2 release

Minor bump with a fix for automatic retrying of training with a lower learning rate upon failure.

CellBender 0.2.1 release

Minor bump with a fix for setup.py to install sub packages, and new support for anndata inputs.

CellBender 0.2.0 release

CellBender v0.2.0 implements a modified model for remove-background, the command-line tool used to remove ambient RNA / background noise from scRNA-seq datasets according to a principled, generative model of scRNA-seq count data. The changes to the remove-background tool will be documented in an upcoming paper.

Please note that implementation details may be subject to change in future updates.

CellBender 0.1.0 release

CellBender v0.1.0 introduces remove-background, a command-line tool used to remove ambient RNA / background noise from scRNA-seq datasets according to a principled, generative model of scRNA-seq count data. The remove-background tool is documented in the following bioRxiv paper:
https://www.biorxiv.org/content/10.1101/791699v1

Please note that the implementation may be subject to change in future updates.