菜单
Single-cell clustering workflow: PCA dimensionality reduction, k-NN neighbor graph, Leiden/Louvain community detection, UMAP/tSNE embedding, and optional PAGA graph abstraction. Covers Scanpy (Python) and Seurat (R).
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Load BioMaster as one integrated skill-driven bioinformatics assistant.
BioMaster conversational bioinformatics assistant; starts workflows only after execution intent or empty activation.
Automated and marker-guided single-cell cell type annotation using CellTypist, marker review, reference transfer, and confidence-aware label curation.
Ligand-receptor communication inference in single-cell or spatial data with sender-receiver summaries and cautious interpretation.
Workflow for paired or integrated single-cell RNA and ATAC analysis with multimodal latent spaces and regulatory interpretation.
Workflow for spatial transcriptomics preprocessing, domain detection, deconvolution, neighborhood analysis, and publication-ready spatial maps.
| name | bioskills-clustering |
| description | Single-cell clustering workflow: PCA dimensionality reduction, k-NN neighbor graph, Leiden/Louvain community detection, UMAP/tSNE embedding, and optional PAGA graph abstraction. Covers Scanpy (Python) and Seurat (R). |
| domain | single-cell |
| primary_tool | scanpy |
| methods | ["scanpy","seurat","leiden","louvain","umap","tsne","paga"] |
| macro_tags | ["clustering","dimensionality-reduction","visualization","single-cell"] |
| micro_tags | ["scanpy","seurat","leiden","louvain","umap","tsne","paga","pca","dimensionality-reduction","neighbors","knn-graph","clustering","resolution","visualization","trajectory"] |
| source | bioskills-clustering |
| status | active |
| enabled | true |
