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bio-flow-cytometry-compensation-transformation
维护者 FreedomIntelligence · 最近更新 2026年4月1日
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.
原始来源
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-flow-cytometry-compensation-transformation
- 维护者
- FreedomIntelligence
- 许可
- MIT
- 最近更新
- 2026年4月1日
技能摘要
来自 SKILL.md 的关键信息
核心说明
- R：flowCore：：compensate() then flowCore：：transform() ，支持 estimateLogicle()。
- Compensate 、 transform my flow cytometry data" → Correct spectral overlap between fluorophores ，使用 compensation matrix 、 apply biexponential/arcsinh transforms ，用于 visualization 、 analysis. R：flowCore：：compensate() then flowCore：：transform() ，支持 estimateLogicle()。
- fcs <- read.FCS('sample.fcs'，transformation = FALSE) comp_matrix <- keyword(fcs)$$SPILLOVER。
原始文档
SKILL.md 摘录
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)
适用场景
- 适合在correcting spectral overlap between fluorophores 或 transforming data ，用于 analysis时使用。
不适用场景
- Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。
上游相关技能
- fcs-handling - Load FCS files first
- gating-analysis - Gate after preprocessing
- clustering-phenotyping - Cluster transformed data
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