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bulk-rna-seq-differential-expression-with-omicverse
维护者 FreedomIntelligence · 最近更新 2026年4月1日
bulk-rna-seq-differential-expression-with-omicverse：Follow this skill to run end-to-end differential expression (DEG) workflow showcased in [`t_deg.ipynb`](../../omicverse_guide/docs/Tutorials-bulk/t_deg.ipynb)。 It assumes user provides raw gene-level count matrix (e.g.，，面向 featureCounts) 、 wants to analyse bulk RNA-seq cohorts inside omicverse。
原始来源
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bulk-deg-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
- Follow this skill to run end-to-end differential expression (DEG) workflow showcased in t_deg.ipynb. It assumes user provides raw gene-level count matrix (e.g.，，面向 featureCounts) 、 wants to analyse bulk RNA-seq cohorts inside omicverse。
- Import omicverse as ov，scanpy as sc，、 matplotlib.pyplot as plt。
- Call ov.plot_set() so downstream plots adopt omicverse styling。
- When gene IDs must be converted to gene symbols，instruct user to download mapping pairs ，通过 ov.utils.download_geneid_annotation_pair() 、 store them under genesets/。
- Mention available prebuilt genomes (T2T-CHM13，GRCh38，GRCh37，GRCm39，danRer7，danRer11) 、 that users can generate their own mapping ，面向 GTF files if needed。
原始文档
SKILL.md 摘录
Examples
- "I have a featureCounts matrix for mouse tumour samples—normalize it with DESeq2, run t-test DEG, and highlight the top 8 genes in a volcano plot."
- "Use omicverse to compute edgeR-style differential expression between treated and control replicates, then run GO enrichment on significant genes."
- "Guide me through converting Ensembl IDs to symbols, performing limma DEG, and plotting boxplots for Krtap9-5 and Lef1."
适用场景
- 适合在user has bulk count matrices 、 needs differential expression analysis in omicverse时使用。
不适用场景
- Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。
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