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-deseq2-basics

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

Perform differential expression analysis using DESeq2 in R/Bioconductor. Use for analyzing RNA-seq count data, creating DESeqDataSet objects, running the DESeq workflow, and extracting results with log fold change shrinkage. Use when performing DE analysis with DESeq2.

OpenClawNanoClaw分析处理复现实验bio-de-deseq2-basics🧬 bioinformatics (gptomics bio-* suite)bioinformatics — differential expression & transcriptomicsperform

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-de-deseq2-basics

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

Differential expression analysis ，使用 DESeq2 ，用于 RNA-seq count data。
dds <- DESeq数据集FromMatrix(countData = counts，colData = coldata，design = ~ condition)。

原始文档

SKILL.md 摘录

Creating DESeqDataSet

Goal: Construct a DESeqDataSet object from various input formats for DE analysis.

Approach: Wrap count data and sample metadata into the DESeq2 container, specifying the experimental design formula.

"Load my RNA-seq counts into DESeq2" → Create a DESeqDataSet from a count matrix, SummarizedExperiment, or tximport object with sample metadata and a design formula.

Standard DESeq2 Workflow

Goal: Run the complete DESeq2 pipeline from raw counts to shrunken log fold change estimates.

Approach: Create dataset, pre-filter low-count genes, set reference level, run size factor estimation + dispersion estimation + Wald test, then apply LFC shrinkage.

"Find differentially expressed genes between treated and control" → Test for significant expression changes between conditions using negative binomial models with empirical Bayes shrinkage.


## Create DESeqDataSet

dds <- DESeqDataSetFromMatrix(countData = counts,
                               colData = coldata,
                               design = ~ condition)

适用场景

可用于analyzing RNA-seq count data，creating DESeq数据集 objects，running DESeq workflow，、 extracting results ，支持 log fold change shrinkage。
适合在performing DE analysis ，支持 DESeq2时使用。