AR
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数据与复现
BI
bio-experimental-design-power-analysis
维护者 FreedomIntelligence · 最近更新 2026年4月1日
bio-experimental-design-power-analysis：Statistical power analysis ，用于 detecting differential signals。
原始来源
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-experimental-design-power-analysis
- 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
- rnapower(depth = 20，n = 3，cv = 0.4，effect = 2，alpha = 0.05)。
- rnapower(depth = 20，cv = 0.4，effect = 2，alpha = 0.05，power = 0.8)。
原始文档
SKILL.md 摘录
Core Concept
Power = probability of detecting a true effect. Underpowered studies waste resources; overpowered studies are inefficient.
RNA-seq Power Analysis
library(RNASeqPower)
## CV Guidelines
| Experiment Type | Typical CV | Notes |
|-----------------|------------|-------|
| Cell lines | 0.1-0.2 | Low variability |
| Inbred mice | 0.2-0.3 | Moderate |
| Human samples | 0.3-0.5 | High variability |
| Primary cells | 0.3-0.4 | Donor-dependent |
适用场景
- Use bio-experimental-design-power-analysis ，用于 统计检验 、 quantitative analysis。
- Apply bio-experimental-design-power-analysis to research 数据集s that require rigorous inference。
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
- experimental-design/sample-size - Detailed sample size calculations
- experimental-design/batch-design - Accounting for batch effects in design
- differential-expression/deseq2-basics - Running the actual DE analysis
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