bio-flow-cytometry-gating-analysis

npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-flow-cytometry-gating-analysis --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

## Version Compatibility Reference examples tested with: flowCore 2.14+ 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. # Gating Analysis **"Gate my flow cytometry data to identify cell populations"** → Define cell populations through manual or automated gating strategies using rectangular, polygon, or data-driven gates in a hierarchical framework. - R: `flowWorkspace::gs_add_gating_method()`, `openCyto::gating()` for automated gating ## 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-