{"library":"scvi-tools","type":"library","category":null,"description":"scvi-tools provides a suite of deep learning models for the deep probabilistic analysis of single-cell omics data. It is built on PyTorch and AnnData, offering robust methods for tasks like dimensionality reduction, batch correction, and differential expression. The library is actively developed, releasing frequent minor versions and occasional major updates.","language":"python","status":"active","version":"1.4.2","tags":["single-cell","biology","omics","deep-learning","bioinformatics","pytorch"],"install":[{"cmd":"pip install scvi-tools","imports":["import scvi","from scvi.model import SCVI","from scvi.data import setup_anndata"]},{"cmd":"pip install 'scvi-tools[gpu]' --extra-index-url https://download.pytorch.org/whl/cu118","imports":[]},{"cmd":"conda install -c pytorch -c conda-forge -c bioconda scvi-tools","imports":[]}],"homepage":"https://scvi-tools.org","github":"https://github.com/scverse/scvi-tools","docs":"https://scvi-tools.org","changelog":null,"pypi":"https://pypi.org/project/scvi-tools/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":0,"avg_install_s":null,"avg_import_s":null,"wheel_type":null},"url":"https://checklist.day/v1/registry/scvi-tools/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}