bio-flow-cytometry-gating-analysis
Manual and automated gating for defining cell populations in flow cytometry. Covers rectangular, polygon, and data-driven gates. Use when identifying cell populations through hierarchical gating strategies.
npx skills add majiayu000/claude-skill-registry --skill gating-analysis-gptomics-bioskills --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.
# Gating Analysis ## Manual Rectangular Gates ```r library(flowCore) # Create rectangular gate cd4_gate <- rectangleGate(filterId = 'CD4+', 'CD4' = c(500, Inf), 'CD3' = c(200, Inf)) # Apply gate cd4_result <- filter(fcs, cd4_gate) summary(cd4_result) # Get cells in gate cd4_cells <- Subset(fcs, cd4_gate) ``` ## Polygon Gates ```r # Define polygon vertices vertices <- matrix(c(100, 100, # x1, y1 1000, 100, # x2, y2 1000, 1000, # x3, y3 100, 1000), # x4, y4 ncol = 2, byrow = TRUE) colnames(vertices) <- c('FSC-A', 'SSC-A') # Create polygon gate poly_gate <- polygonGate(filterId = 'Lymphocytes', .gate = vertices) # Apply lymph <- Subset(fcs, poly_gate) ``` ## Gating Hierarchy (flowWorkspace) ```r library(flowWorkspace) # Create GatingSet from flowSet gs <- GatingSet(fs) # Add gates to hierarchy gs_pop_add(gs, cd4_gate, parent = 'root') # Add child gate cd4_cd8_gate <- rectangleGate(filterId = 'CD8+', 'CD8' = c(500, Inf)) gs_pop_add(gs, cd4_cd8_gate, parent = 'CD4+') # View hierarchy gs_get_pop_paths(gs) # Recompute statistics recompute(gs) # Get population statistics gs_pop_get_stats(gs) ``` ## Automated Gating: flowDensity ```r library(flowDensity) # Data-driven gate based on density
- Manual Rectangular Gates
- Polygon Gates
- Gating Hierarchy (flowWorkspace)
- Automated Gating: flowDensity
- Automated Gating: openCyto
- Quadrant Gates
- Boolean Gates
- Extract Gated Populations
- Visualization
- Export Gating Strategy
- Related Skills
What does the bio-flow-cytometry-gating-analysis skill do?
Manual and automated gating for defining cell populations in flow cytometry. Covers rectangular, polygon, and data-driven gates. Use when identifying cell populations through hierarchical gating strategies.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill gating-analysis-gptomics-bioskills --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.