torbcellselection
Separates T and non-T cells or B and non-B cells from a mixed cell population. Uses either clonotype percentage from VDJ data, indicator gene expression (CD3 markers for T cells, CD19/CD20 for B cells), custom selector expressions, or k-means clustering for automatic selection.
npx skills add majiayu000/claude-skill-registry --skill torbcellselection --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.
# TOrBCellSelection Process Configuration ## Purpose Separates T and non-T cells or B and non-B cells from a mixed cell population. Uses either clonotype percentage from VDJ data, indicator gene expression (CD3 markers for T cells, CD19/CD20 for B cells), custom selector expressions, or k-means clustering for automatic selection. ## When to Use - When dataset contains mixed cell types (T cells + other cell types, or B cells + other cell types) - Before TCR-specific or BCR-specific analysis to isolate relevant cells - After `SeuratClusteringOfAllCells` to identify which clusters are T/B cells - When scRNA-seq data includes scTCR-seq or scBCR-seq data - **DO NOT use** if all cells in your dataset are already T/B cells ## Configuration Structure ### Process Enablement ```toml [TOrBCellSelection] cache = true # Enable caching for this process ``` ### Input Specification ```toml [TOrBCellSelection.in] # Seurat object file (RDS/qs2 format) from SeuratClusteringOfAllCells srtobj = ["SeuratClusteringOfAllCells"] # Optional: Immune repertoire data file (RDS/qs2 format) from ScRepLoading # Required unless ignore_vdj is set to true immdata = ["ScRepLoading"] ``` ### Environment Variables ```t
- Purpose
- When to Use
- Configuration Structure
- Process Enablement
- Input Specification
- Environment Variables
- Configuration Examples
- Minimal Configuration (Default T Cell Markers)
- T Cell Selection with Multiple CD3 Markers
- B Cell Selection (Default Markers)
- Selection by Clonotype Percentage Threshold
- Selection Combined with Marker Expression
- Selection Without VDJ Data (Markers Only)
- B Cell Selection Without VDJ Data
What does the torbcellselection skill do?
Separates T and non-T cells or B and non-B cells from a mixed cell population. Uses either clonotype percentage from VDJ data, indicator gene expression (CD3 markers for T cells, CD19/CD20 for B cells), custom selector expressions, or k-means clustering for automatic selection.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill torbcellselection --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 majiayu000/claude-skill-registry, a repository with 534 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.