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Differential Gene Expression Analysis (RNA-seq)

Name: Differential Gene Expression Analysis (RNA-seq)
Author: kenthompson2088

作者 kenthompson2088 · GitHub ↗ · v1.0.1 · MIT-0

cross-platform ✓ 安全检测通过

219

总下载

当前安装

版本数

在 OpenClaw 中安装

/install differential-gene-analysis

功能描述

Performs differential gene expression analysis on RNA-seq count data using DESeq2 and outputs significant genes, volcano plot, PCA, and heatmap.

使用说明 (SKILL.md)

Differential Gene Expression Analysis (RNA-seq)\r

OpenCLAW Skill for bioinformatics data analysis.\r \r

License\r

MIT-0\r \r

Description\r

This skill performs differential gene analysis using DESeq2 with simulated expression data.\r \r

Input\r

input/count_matrix.csv\r \r

Output\r

output/volcano.png\r
output/pca.png\r
output/heatmap.png\r
output/diff_genes_significant.csv\r \r

Code\r

# ==============================\r
# OpenCLAW Skill Run Code\r
# ==============================\r
\r
if (!require("BiocManager", quietly = TRUE)) {\r
  install.packages("BiocManager", repos = "https://cloud.r-project.org/")\r
}\r
\r
BiocManager::install(c("DESeq2", "ggplot2", "pheatmap"), update = FALSE, ask = FALSE)\r
\r
library(DESeq2)\r
library(ggplot2)\r
library(pheatmap)\r
\r
if (!dir.exists("output")) dir.create("output")\r
\r
# Read input\r
count_df \x3C- read.csv("input/count_matrix.csv", row.names = 1)\r
count_matrix \x3C- as.matrix(count_df)\r
group \x3C- factor(c("Control","Control","Control","Treat","Treat","Treat"))\r
colData \x3C- data.frame(group = group)\r
\r
# DESeq2\r
dds \x3C- DESeqDataSetFromMatrix(round(count_matrix), colData, ~ group)\r
dds \x3C- dds[rowSums(counts(dds)) > 3, ]\r
dds \x3C- DESeq(dds)\r
res \x3C- results(dds, contrast = c("group", "Treat", "Control"))\r
res_sig \x3C- subset(res, padj \x3C 0.05 & abs(log2FoldChange) > 1)\r
write.csv(as.data.frame(res_sig), "output/diff_genes_significant.csv")\r
\r
# Volcano\r
res_df \x3C- as.data.frame(res)\r
res_df$sig \x3C- ifelse(res_df$padj \x3C 0.05 & abs(res_df$log2FoldChange) > 1, "Sig", "NS")\r
p \x3C- ggplot(res_df, aes(log2FoldChange, -log10(padj))) + geom_point(aes(color=sig)) + theme_bw()\r
ggsave("output/volcano.png", p, dpi=300)\r
\r
# PCA\r
vsd \x3C- vst(dds, blind=FALSE)\r
p_pca \x3C- plotPCA(vsd, intgroup="group") + theme_bw()\r
ggsave("output/pca.png", p_pca)\r
\r
# Heatmap\r
if(nrow(res_sig) > 0) {\r
  top \x3C- head(rownames(res_sig), 10)\r
  mat \x3C- t(scale(t(assay(vsd)[top,])))\r
  png("output/heatmap.png", width=800, height=600)\r
  pheatmap(mat, annotation_col=data.frame(group))\r
  dev.off()\r
}\r
\r
cat("✅ Skill run successfully\
")

安全使用建议

This skill appears to do exactly what it says: it runs R/DESeq2 on an input count matrix and writes plots and a CSV. Before running, ensure: (1) you provide a correctly formatted input/count_matrix.csv (the code expects six samples arranged as 3 Control then 3 Treat), (2) you run it in a sandbox or environment where installing R/Bioconductor packages is safe (installing packages downloads and executes package installation code), and (3) you accept that the skill will install packages at runtime (network access and write permissions required). Also note the packaging mismatch (skill.json references main.R which is not present); consider asking the publisher for a proper entry file or confirm that executing the code embedded in SKILL.md is the intended workflow.

功能分析

Type: OpenClaw Skill Name: differential-gene-analysis Version: 1.0.1 The skill performs standard bioinformatics differential gene expression analysis using the DESeq2 R package. The code in skill.md follows typical data science workflows, including installing necessary dependencies from official repositories (CRAN/Bioconductor), processing local CSV input, and generating visualization plots (Volcano, PCA, Heatmap). No evidence of data exfiltration, malicious execution, or prompt injection was found.

能力评估

✓ Purpose & Capability

Name/description (DE analysis with DESeq2) matches the actions in SKILL.md: installing DESeq2, plotting, and writing result files. Required resources (R packages) are appropriate. Minor inconsistency: skill.json claims an entryFile main.R and runtime R-4.2, but no main.R is present and the runnable R code lives in SKILL.md; this is likely bookkeeping/packaging sloppiness rather than suspicious behavior.

ℹ Instruction Scope

The SKILL.md contains full R code that installs BiocManager and Bioconductor/CRAN packages, reads input/count_matrix.csv, performs DESeq2 analysis with a hard-coded group vector (3 Control, 3 Treat), and writes output images/CSV. Instructions do not read unrelated files or environment variables and do not transmit data externally. Note: installing R packages requires network access to CRAN/Bioconductor and will fetch and run package installation scripts — normal but worth noting.

✓ Install Mechanism

No platform install spec; runtime R code calls install.packages() and BiocManager::install() to pull DESeq2, ggplot2, pheatmap from standard repositories (CRAN/Bioconductor). These are standard/public package sources, not arbitrary URLs or archive downloads.

✓ Credentials

The skill requests no environment variables, no credentials, and accesses only the declared input path input/count_matrix.csv and writes to output/. The requested resources are proportional to the stated purpose.

✓ Persistence & Privilege

always is false and the skill does not request persistent system-wide privileges or modify other skills/config. It runs ad-hoc R code at runtime only.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install differential-gene-analysis
安装完成后，直接呼叫该 Skill 的名称或使用 /differential-gene-analysis 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.1

- Adds initial support for differential gene expression analysis using DESeq2 on RNA-seq count data. - Generates key output files: volcano plot, PCA plot, heatmap of significant genes, and CSV with significant differential genes. - Uses simulated group assignments (Control vs Treat) for analysis. - Outputs visualizations and results to an output directory.

元数据

Slug differential-gene-analysis

版本 1.0.1

许可证 MIT-0

累计安装 1

当前安装数 1

历史版本数 1

常见问题