数据与复现生物信息与基因组学FreedomIntelligence/OpenClaw-Medical-Skills数据与复现
BI

bio-experimental-design-multiple-testing

维护者 FreedomIntelligence · 最近更新 2026年4月1日

Multiple testing correction: Bonferroni, BH/FDR, q-values.

OpenClawNanoClaw分析处理复现实验bio-experimental-design-multiple-testing🧠 bioos extended suitebioos extended bioinformatics suitemultiple

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-experimental-design-multiple-testing

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

2 min

核心说明

  • p_adj <- p.adjust(pvalues,method = 'bonferroni')。
  • p_adj <- p.adjust(pvalues,method = 'BH')。

原始文档

SKILL.md 摘录

The Problem

Testing 20,000 genes at p < 0.05 yields ~1,000 false positives by chance. Correction is essential.

q-value (Recommended for Large-Scale)

library(qvalue)
qobj <- qvalue(pvalues)
qvalues <- qobj$qvalues
pi0 <- qobj$pi0  # Estimated proportion of true nulls

## Method Selection Guide

| Scenario | Recommended Method | Threshold |
|----------|-------------------|-----------|
| Genome-wide DE | BH or q-value | FDR < 0.05 |
| Candidate genes | Bonferroni | p < 0.05/n |
| Exploratory | BH | FDR < 0.10 |
| Validation study | Bonferroni | p < 0.05/n |
| GWAS | Bonferroni | p < 5e-8 |

适用场景

  • Use bio-experimental-design-multiple-testing ,用于 genomics 、 bioinformatics workflows。
  • Apply bio-experimental-design-multiple-testing to sequencing,variant,或 omics analysis tasks。

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

  • differential-expression/de-results - Applying corrections to DE output
  • population-genetics/association-testing - GWAS significance thresholds
  • pathway-analysis/go-enrichment - Correcting enrichment p-values

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