菜单
Infer gene regulatory networks from single-cell data (pySCENIC for RNA-only, SCENIC+ for Multiome) and simulate TF perturbations with CellOracle.
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
| name | bioskills-grn-pipeline |
| description | Infer gene regulatory networks from single-cell data (pySCENIC for RNA-only, SCENIC+ for Multiome) and simulate TF perturbations with CellOracle. |
| domain | single-cell |
| primary_tool | pySCENIC |
| methods | ["pySCENIC","GRNBoost2","RcisTarget","AUCell","SCENIC+","cisTopic","pycistarget","CellOracle"] |
| macro_tags | ["gene-regulatory-network","regulon","perturbation-simulation","multiome","motif-enrichment"] |
| micro_tags | ["pySCENIC","GRNBoost2","RcisTarget","AUCell","SCENIC+","cisTopic","pycistarget","CellOracle","data-loading","path-selection","version-check","grnboost2","cistopic","grn-inference","rcistarget","motif-enrichment","regulon-pruning","aucell","scenicplus","egrn","qc","validation","celloracle","perturbation-simulation","knn-imputation"] |
| source | bioskills-grn-pipeline |
| status | active |
| enabled | true |
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.
