bysynthetic-sciences· 59 skills
Deep generative models for single-cell omics. Use when you need probabilistic batch correction (scVI), transfer learning, differential expression with uncertainty, or multi-modal integration (TOTALVI, MultiVI). Best for advanced modeling, batch effects, multimodal data. For standard analysis pipelines use scanpy.
$npx -y skills add synthetic-sciences/openscience --skill scvi-toolsInstalls into the current project.
Run `npx skills use "https://github.com/synthetic-sciences/openscience" --skill "synthetic-sciences/openscience/scvi-tools"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/synthetic-sciences/openscience" that are relevant to the current task. Run `npx skills add "https://github.com/synthetic-sciences/openscience"` and select the relevant skills, then follow their instructions.