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bio-flow-cytometry-compensation-transformation
Maintainer FreedomIntelligence · Last updated April 1, 2026
Spillover compensation and data transformation for flow cytometry. Covers compensation matrix calculation, application, and biexponential/arcsinh transforms. Use when correcting spectral overlap between fluorophores or transforming data for analysis.
Original source
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-flow-cytometry-compensation-transformation
- Maintainer
- FreedomIntelligence
- License
- MIT
- Last updated
- April 1, 2026
Skill Snapshot
Key Details From SKILL.md
Key Notes
- R: flowCore::compensate() then flowCore::transform() with estimateLogicle().
- Compensate and transform my flow cytometry data" → Correct spectral overlap between fluorophores using a compensation matrix and apply biexponential/arcsinh transforms for visualization and analysis. R: flowCore::compensate() then flowCore::transform() with estimateLogicle().
- fcs <- read.FCS('sample.fcs', transformation = FALSE) comp_matrix <- keyword(fcs)$$SPILLOVER.
Source Doc
Excerpt From SKILL.md
Or from CSV file
comp_matrix <- as.matrix(read.csv('compensation.csv', row.names = 1))
## Create compensation object
comp <- compensation(comp_matrix)
## Apply to flowFrame
fcs_comp <- compensate(fcs, comp)
Use cases
- Use when correcting spectral overlap between fluorophores or transforming data for analysis.
Not for
- Do not rely on this catalog entry alone for installation or maintenance details.
Upstream Related Skills
- fcs-handling - Load FCS files first
- gating-analysis - Gate after preprocessing
- clustering-phenotyping - Cluster transformed data
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