https://github.com/scvae/scvae

Deep learning for single-cell transcript counts
https://github.com/scvae/scvae

deep-learning genomics machine-learning single-cell

Last synced: 2 months ago
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Deep learning for single-cell transcript counts

• Host: GitHub
• URL: https://github.com/scvae/scvae
• Owner: scvae
• License: apache-2.0
• Created: 2017-02-13T11:42:21.000Z (over 9 years ago)
• Default Branch: main
• Last Pushed: 2025-03-14T10:20:14.000Z (about 1 year ago)
• Last Synced: 2026-03-05T19:38:55.076Z (3 months ago)
• Topics: deep-learning, genomics, machine-learning, single-cell
• Language: Python
• Homepage:
• Size: 1.77 MB
• Stars: 90
• Watchers: 4
• Forks: 26
• Open Issues: 7
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE.txt

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README

          
# scVAE: Single-cell variational auto-encoders #

scVAE is a command-line tool for modelling single-cell transcript counts using variational auto-encoders.

Install scVAE using pip for Python 3.6 and 3.7:

	$ python3 -m pip install scvae

scVAE can then be used to train a variational auto-encoder on a data set of single-cell transcript counts:

	$ scvae train transcript_counts.tsv

And the resulting model can be evaluated on the same data set:

	$ scvae evaluate transcript_counts.tsv

For more details, see the [documentation][], which include a user guide and a short tutorial.

[documentation]: https://scvae.readthedocs.io