scVI: deep generative model for single-cell RNA-seq data

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Authors: Robrecht Cannoodt, Wouter Saelens, Lukas Sikkema, Yvan Saeys, et al.
Year: 2017
Journal: Nature Methods
DOI: 10.1038/s41592-018-0229-2
Publisher: https://www.nature.com/articles/s41592-018-0229-2

Keywords: scvi, single-cell

Abstract

scVI is a scalable deep generative model for single-cell RNA-seq data.

Cite this paper

bibtex

@misc{scvi2017,
  title  = {scVI: deep generative model for single-cell RNA-seq data},
  author = {Robrecht Cannoodt, Wouter Saelens, Lukas Sikkema, Yvan Saeys, et al.},
  year   = {2017},
  journal = {Nature Methods},
  doi    = {10.1038/s41592-018-0229-2},
  url    = {https://doi.org/10.1038/s41592-018-0229-2},
}

Source files

[metadata.json](https://raw.githubusercontent.com/badhope/ScholarLib/main/papers/computer-science/Bioinformatics/Sequencing/2019-and-earlier/Nature Methods/empirical/bio/scvi/metadata.json)
[paper.bib](https://raw.githubusercontent.com/badhope/ScholarLib/main/papers/computer-science/Bioinformatics/Sequencing/2019-and-earlier/Nature Methods/empirical/bio/scvi/paper.bib)