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数据与复现
TO
tooluniverse-epigenomics
维护者 FreedomIntelligence · 最近更新 2026年4月1日
tooluniverse-epigenomics：Production-ready genomics 、 epigenomics data processing ，用于 BixBench questions。 Handles methylation array analysis (CpG filtering，differential methylation，age-related CpG detection，chromosome-level density)，ChIP-seq peak analysis (peak calling，motif enrichment，coverage stats)，ATAC-seq chromatin accessibility，multi-omics integration (expression + methylation correlation)，、 genome-wide statistics。
原始来源
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/tooluniverse-epigenomics
- 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
- Production-ready computational skill ，用于 processing 、 analyzing epigenomics data. Combines local Python computation (pandas，scipy，numpy，pysam，statsmodels) ，支持 ToolUniverse annotation tools ，用于 regulatory context. Designed to solve BixBench-style questions about methylation，ChIP-seq，ATAC-seq，、 multi-omics integration。
- import pandas as pd import numpy as np ，面向 scipy import stats import statsmodels.stats.multitest as mt。
原始文档
SKILL.md 摘录
When to Use This Skill
Triggers:
- User provides methylation data (beta-value matrices, Illumina arrays) and asks about CpG sites
- Questions about differential methylation analysis
- Age-related CpG detection or epigenetic clock questions
- Chromosome-level methylation density or statistics
- ChIP-seq peak files (BED format) with analysis questions
- ATAC-seq chromatin accessibility questions
- Multi-omics integration (expression + methylation, expression + ChIP-seq)
- Genome-wide epigenomic statistics
- Questions mentioning "methylation", "CpG", "ChIP-seq", "ATAC-seq", "histone", "chromatin", "epigenetic"
- Questions about missing data across clinical/genomic/epigenomic modalities
- Regulatory element annotation for processed epigenomic data
Example Questions This Skill Solves:
- "How many patients have no missing data for vital status, gene expression, and methylation data?"
- "What is the ratio of filtered age-related CpG density between chromosomes?"
- "What is the genome-wide average chromosomal density of unique age-related CpGs per base pair?"
- "How many CpG sites show significant differential methylation (padj < 0.05)?"
- "What is the Pearson correlation between methylation and expression for gene X?"
- "How many ChIP-seq peaks overlap with promoter regions?"
- "What fraction of ATAC-seq peaks are in enhancer regions?"
- "Which chromosome has the highest density of hypermethylated CpGs?"
- "Filter CpG sites by variance > threshold and map to nearest genes"
- "What is the average beta value difference between tumor and normal for chromosome 17?"
NOT for (use other skills instead):
- Gene regulation lookup without data files -> Use existing epigenomics annotation pattern
- RNA-seq differential expression -> Use
tooluniverse-rnaseq-deseq2 - Variant calling/annotation from VCF -> Use
tooluniverse-variant-analysis - Gene enrichment analysis -> Use
tooluniverse-gene-enrichment - Protein structure analysis -> Use
tooluniverse-protein-structure-retrieval
Optional but useful
import pysam # BAM/CRAM file access import gseapy # Enrichment of genes from methylation analysis
ToolUniverse (for annotation)
from tooluniverse import ToolUniverse
---
适用场景
- User provides methylation data (beta-value matrices，Illumina arrays) 、 asks about CpG sites。
- Questions about differential methylation analysis。
- Age-related CpG detection 或 epigenetic clock questions。
- Chromosome-level methylation density 或 statistics。
不适用场景
- Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。
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