A multivariate RNA Velocity model to estimate future cell states with uncertainty using probabilistic modeling with pyro.
𝒫robabilistic modeling of RNA velocity ⬱
| CI/CD |    |
| Docs |   |
| Package |    |
| Meta |     |
    |
Pyro-Velocity is a library for probabilistic inference in minimal models approximating gene expression dynamics from, possibly multimodal, single-cell sequencing data. It provides posterior estimates of gene expression parameters, predictive estimates of gene expression states, and local estimates of cell state transition probabilities. It can be used as a component in frameworks that attempt to retain the ability to propagate uncertainty in predicting: distributions over cell fates from subpopulations of cell states, response to cell state perturbations, or candidate genes or gene modules that correlate with determination of specific cell fates.
Please see the Documentation.
Changes for each release are listed in the Changelog.
Please review the Contributing Guide for instructions on setting up a development environment and submitting pull requests.
If you would like to apply Pyro-Velocity in your research, have an idea for a new feature, have a problem using the library, or just want to chat, please feel free to start a discussion.
If you have a feature request or issue using Pyro-Velocity that may require making changes to the contents of this repository, please file an issue containing
We are always interested in discussions and issues that can help to improve the Documentation.
FAQs
A multivariate RNA Velocity model to estimate future cell states with uncertainty using probabilistic modeling with pyro.
We found that pyrovelocity demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 3 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Research
Security News
Attackers used a malicious npm package typosquatting a popular ESLint plugin to steal sensitive data, execute commands, and exploit developer systems.
Security News
The Ultralytics' PyPI Package was compromised four times in one weekend through GitHub Actions cache poisoning and failure to rotate previously compromised API tokens.
Security News
Research
Socket researchers found a malicious Maven package impersonating the legitimate ‘XZ for Java’ library, introducing a backdoor for remote code execution.
