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| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | 1.Pydeseq Differential gene expression analysis for bulk RNA-seq count matrices using a DESeq2-like workflow in Python; use when you need Wald tests, FDR correction, and optional LFC shrinkage for… | aipoch/ | 1.9k | — | ~1.8k | Automated safety check: Pass | MIT | 24 days ago |
| 2 | 2.Scanpy Standard single-cell RNA-seq analysis pipeline. An agent skill from aipoch/medical-research-skills. | aipoch/ | 1.9k | — | ~3.9k | Automated safety check: Pass | MIT | 24 days ago |
| 3 | Deep generative models for single-cell omics; use when you need probabilistic batch correction (scVI), transfer learning, uncertainty-aware differential expression, or multimodal integration… | aipoch/ | 1.9k | — | ~1.5k | Automated safety check: Pass | MIT | 24 days ago |
| 4 | 4.Anndata Data structure for annotated matrices in single-cell analysis; use when reading/writing .h5ad (or zarr) and exchanging data with the scverse ecosystem. | aipoch/ | 1.9k | — | ~1.7k | Automated safety check: Pass | MIT | 24 days ago |
| 5 | Programmatically query the CZ CELLxGENE Census (61M+ cells) when you need cross-tissue, disease, or cell-type expression data for population-scale queries and reference atlas comparisons. | aipoch/ | 1.9k | — | ~1.6k | Automated safety check: Pass | MIT | 24 days ago |