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数据与复现
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数据与复现
BI
bio-single-cell-multimodal-integration
维护者 FreedomIntelligence · 最近更新 2026年4月1日
Analyze multi-modal single-cell data (CITE-seq, Multiome, spatial). Use when working with data that measures multiple modalities per cell like RNA + protein or RNA + ATAC. Use when analyzing CITE-seq, Multiome, or other multi-modal single-cell data.
原始来源
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-single-cell-multimodal-integration
- 维护者
- FreedomIntelligence
- 许可
- MIT
- 最近更新
- 2026年4月1日
技能摘要
来自 SKILL.md 的关键信息
核心说明
- R：Seurat：：FindMultiModalNeighbors() ，用于 WNN integration。
- Python：muon ，用于 MuData handling，scanpy + anndata ，用于 multimodal objects。
- 整合 RNA 、 protein data ，面向 my CITE-seq experiment" → Jointly analyze multiple modalities (RNA + protein，RNA + ATAC) measured in same cells ，使用 weighted nearest neighbor 或 factor analysis. R：Seurat：：FindMultiModalNeighbors() ，用于 WNN integration Python：muon ，用于 MuData handling，scanpy + anndata ，用于 multimodal objects。
- 分析 multi-modal single-cell data where multiple measurements are made per cell。
- data <- Read10X('filtered_feature_bc_matrix/')。
原始文档
SKILL.md 摘录
Common Modalities
| Technology | Modalities | Package |
|---|---|---|
| CITE-seq | RNA + surface proteins (ADT) | Seurat |
| 10X Multiome | RNA + ATAC | Seurat, Signac, ArchR |
| SHARE-seq | RNA + ATAC | Seurat, Signac |
| Spatial (Visium) | RNA + spatial coordinates | Seurat, Squidpy |
Separate RNA and ADT
rna_counts <- data$Gene Expression
adt_counts <- data$Antibody Capture
Create Seurat object with both assays
obj <- CreateSeuratObject(counts = rna_counts, assay = 'RNA') obj[['ADT']] <- CreateAssayObject(counts = adt_counts)
适用场景
- 适合在working ，支持 data that measures multiple modalities per cell like RNA + protein 或 RNA + ATAC时使用。
- 适合在analyzing CITE-seq，Multiome，或 other multi-modal single-cell data时使用。
不适用场景
- Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。
上游相关技能
- single-cell/data-io - Loading single-cell data
- single-cell/clustering - Clustering methods
- single-cell/markers-annotation - Cell type annotation
- chip-seq/peak-calling - For ATAC peak calling
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