scvi 0.6.3

Single-cell Variational Inference

scVI - Single cell Variational Inference

scVI is a package for end-to-end analysis of single-cell omics data. The package is composed of several deep generative models for omics data analysis, namely:

• scVI for analysis of single-cell RNA-seq data, as well as its improved differential expression framework

• scANVI for cell annotation of scRNA-seq data using semi-labeled examples

• totalVI for analysis of CITE-seq data

• gimVI for imputation of missing genes in spatial transcriptomics from scRNA-seq data

• AutoZI for assessing gene-specific levels of zero-inflation in scRNA-seq data

• LDVAE for an interpretable linear factor model version of scVI

Tutorials and API reference are available in the documentation. Please use the issues here to discuss usage, or submit bug reports. If you’d like to contribute, please check out our contributing guide. If you find a model useful for your research, please consider citing the corresponding publication (linked above).

History

0.6.3 (2020-4-01)

• bug in version for Louvian in setup.py @adam

0.6.2 (2020-4-01)

• update highly variable gene selection to handle sparse matrices @adam

• update DE docstrings @pierre

• improve posterior save load to also handle subclasses @pierre

• Create NB and ZINB distributions with torch and refactor code accordingly @pierre

• typos in autozivae @achille

• bug in csc sparse matrices in anndata data loader @adam

0.6.1 (2020-3-13)

• handles gene and cell attributes with the same name @han-yuan

• fixes anndata overwriting when loading @adam, @pierre

• formatting in basic tutorial @adam

0.6.0 (2020-2-28)

• updates on TotalVI and LDVAE @adam

• fix documentation, compatibility and diverse bugs @adam, @pierre @romain

• fix for external module on scanpy @galen-xing

0.5.0 (2019-10-17)

• do not automatically upper case genes @adam

• AutoZI @oscar

• Made the intro tutorial more user friendly @adam

• Tests for LDVAE notebook @adam

• black codebase @achille @gabriel @adam

• fix compatibility issues with sklearn and numba @romain

• fix Anndata @francesco-brundu

• docstring, totalVI, totalVI notebook and CITE-seq data @adam

• fix type @eduardo-beltrame

• fixing installation guide @jeff

• improved error message for dispersion @stephen-flemming

0.4.1 (2019-08-03)

• docstring @achille

• differential expression @oscar @pierre

0.4.0 (2019-07-25)

• gimVI @achille

• synthetic correlated datasets, fixed bug in marginal log likelihood @oscar

• autotune, dataset enhancements @gabriel

• documentation @jeff

• more consistent posterior API, docstring, validation set @adam

• fix anndataset @michael-raevsky

• linearly decoded VAE @valentine-svensson

• support for scanpy, fixed bugs, dataset enhancements @achille

• fix filtering bug, synthetic correlated datasets, docstring, differential expression @pierre

• better docstring @jamie-morton

• classifier based on library size for doublet detection @david-kelley

0.3.0 (2019-05-03)

• corrected notebook @jules

• added UMAP and updated harmonization code @chenling @romain

• support for batch indices in csvdataset @primoz-godec

• speeding up likelihood computations @william-yang

• better anndata interop @casey-greene

• early stopping based on classifier accuracy @david-kelley

0.2.4 (2018-12-20)

• updated to torch v1 @jules

• added stress tests for harmonization @chenling

• fixed autograd breaking @romain

• make removal of empty cells more efficient @john-reid

• switch to os.path.join @casey-greene

0.2.2 (2018-11-08)

• added baselines and datasets for sMFISH imputation @jules

• added harmonization content @chenling

• fixing bugs on DE @romain

0.2.0 (2018-09-04)

• annotation notebook @eddie

• Memory footprint management @jeff

• updated early stopping @max

• docstring @james-webber

0.1.6 (2018-08-08)

• MMD and adversarial inference wrapper @eddie

• Documentation @jeff

• smFISH data imputation @max

0.1.5 (2018-07-24)

• Dataset additions @eddie

• Documentation @yining

• updated early stopping @max

0.1.3 (2018-06-22)

• Notebook enhancement @yining

• Semi-supervision @eddie

0.1.2 (2018-06-13)

• First release on PyPi

• Skeleton code & dependencies @jeff

• Unit tests @max

• PyTorch implementation of scVI @eddie @max

• Dataset preprocessing @eddie @max @yining

0.1.0 (2017-09-05)

• First scVI TensorFlow version @romain