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

bio-de-results

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

Extract, filter, annotate, and export differential expression results from DESeq2 or edgeR. Use for identifying significant genes, applying multiple testing corrections, adding gene annotations, and preparing results for downstream analysis. Use when filtering and exporting DE analysis results.

OpenClawNanoClaw分析处理复现实验bio-de-results🧬 bioinformatics (gptomics bio-* suite)bioinformatics — differential expression & transcriptomicsextract

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-de-results

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

提取，filter，、 export differential expression results。
res <- results(dds，alpha = 0.05)。

原始文档

SKILL.md 摘录

Extracting DESeq2 Results

Goal: Retrieve DE statistics from a fitted DESeq2 model as a usable data frame.

Approach: Call results() with optional shrinkage, then convert to a data frame with gene identifiers.


## With log fold change shrinkage

res <- lfcShrink(dds, coef = 'condition_treated_vs_control', type = 'apeglm')

## Convert to data frame

res_df <- as.data.frame(res)
res_df$gene <- rownames(res_df)

适用场景

可用于identifying significant genes，applying multiple testing corrections，adding gene annotations，、 preparing results ，用于 downstream analysis。
适合在filtering 、 exporting DE analysis results时使用。