Deep probabilistic analysis of single-cell and spatial omics data
Analyze single-cell and spatial data to uncover insights in biological research using probabilistic modeling.
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scvi-tools has 1.7k stars on GitHub. It has been forked 467 times. scvi-tools is written mainly in Python. It has been in active development since 2017. scvi-tools is available under the BSD-3-Clause license. Its main topics are cite-seq, deep-generative-model, deep-learning, human-cell-atlas.
Deep probabilistic analysis of single-cell and spatial omics data
scvi-tools is an open-source project. It is released under the BSD-3-Clause license.
Yes. scvi-tools is free and open source — you can use, modify and self-host it.
scvi-tools is available under the BSD-3-Clause license.
scvi-tools is written mainly in Python.
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