bio-single-cell-scatac-analysis
Single-cell ATAC-seq analysis with Signac (R/Seurat) and ArchR. Process 10X Genomics scATAC data, perform QC, dimensionality reduction, clustering, peak calling, and motif activity scoring with chromVAR. Use when analyzing single-cell ATAC-seq data.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-single-cell-scatac-analysis --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Version Compatibility Reference examples tested with: MACS2 2.2+, scanpy 1.10+ Before using code patterns, verify installed versions match. If versions differ: - R: `packageVersion('<pkg>')` then `?function_name` to verify parameters If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # scATAC-seq Analysis **"Analyze my single-cell ATAC-seq data"** → Process peak-barcode matrices, perform QC/filtering, reduce dimensions with LSI, cluster cells, call peaks per cluster, and score motif activity. - R: `Signac::CreateChromatinAssay()` → `RunTFIDF()` → `FindTopFeatures()` → `RunSVD()` - R: `ArchR::createArrowFiles()` for large datasets Analyze single-cell chromatin accessibility data to identify cell types and regulatory elements. ## Tool Comparison | Tool | Ecosystem | Strengths | |------|-----------|-----------| | Signac | Seurat | Integration with scRNA-seq, familiar API | | ArchR | Standalone | Memory efficient, comprehensive | | chromVAR | Bioconductor | TF motif deviation scoring | | SnapATAC2 | Python | Fast, scalable | ## Signac (R/Seurat) **Goal:** Process scATAC-seq da
- Version Compatibility
- Tool Comparison
- Signac (R/Seurat)
- Installation
- Load 10X Data
- Add Gene Annotations
- QC Metrics
- QC Filtering
- Normalization and Dimensionality Reduction
- Clustering
- Gene Activity Scores
- Peak Calling per Cluster
- Differential Accessibility
- Motif Analysis with chromVAR
What does the bio-single-cell-scatac-analysis skill do?
Single-cell ATAC-seq analysis with Signac (R/Seurat) and ArchR. Process 10X Genomics scATAC data, perform QC, dimensionality reduction, clustering, peak calling, and motif activity scoring with chromVAR. Use when analyzing single-cell ATAC-seq data.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-single-cell-scatac-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.