Single-cell Variational Inference
Project description
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
0.6.5 (2020-5-10)
0.6.4 (2020-4-14)
add back Python 3.6 support @adam
get_sample_scale() allows gene selection @valentine-svensson
bug fix to the dataset to anndata method with how cell measurements are stored @adam
fix requirements @adam
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)
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
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)
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
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)
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)
0.1.5 (2018-07-24)
0.1.3 (2018-06-22)
0.1.2 (2018-06-13)
0.1.0 (2017-09-05)
First scVI TensorFlow version @romain
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