Individual skill
deg-screening-analysis
Use when screening differentially expressed genes from a bulk expression matrix between two user-specified groups, producing DEG tables, a volcano plot, and a clustered heatmap. Triggers include DEG analysis, volcano plot, clustered heatmap, limma-based two-group comparison, and case-vs-control screening. NOT for single-cell RNA-seq, multi-group contrasts, count-model workflows such as DESeq2/edgeR, or non-expression omics data.
awesome-med-research-skills/Data Analysis/deg-screening-analysis/SKILL.md
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- License
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- bioinformatics Repository topic
- computational-biology Repository topic
- data-analysis Repository topic
- ai Repository topic
- biology Repository topic
- cancer-genomics Repository topic
- data-visualization Repository topic
- differential-expression Repository topic
- genomics Repository topic
- medical Repository topic
- engineering Derived category
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SKILL.mdcore · 8,282 bytesSKILL.mdcore · 8,282 bytesSKILL.mdcore · 8,282 bytesSKILL.mdcore · 8,282 byteseval_report_deg-screening-analysis_result.jsonasset · 15,206 bytesreferences/algorithm.mddoc · 3,296 bytesreferences/cli-guide.mddoc · 4,601 bytesreferences/troubleshooting.mddoc · 3,638 bytesscripts/diff_methods.Rasset · 875 bytesscripts/diff_visualization.Rasset · 5,033 bytesscripts/functions.Rasset · 5,122 bytesscripts/main.Rruns · 4,020 bytesscripts/run_analysis.Rasset · 3,042 bytesscripts/utils.Rasset · 6,836 bytestests/data/oa_exp.csvasset · 1,022,202 bytestests/data/oa_group.csvasset · 2,220 bytestests/run_tests.Rruns · 8,683 bytes
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> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
# Differential Expression Gene Screening Analysis (Volcano Plot & Clustered Heatmap)
## When to Use
Use this skill when you need a reproducible two-group DEG workflow on a bulk expression matrix and want:
- a full differential expression table
- a filtered DEG table
- a volcano plot
- a clustered heatmap of top differential genes
Typical requests include:
- compare case vs control samples with limma
- screen upregulated and downregulated genes from a normalized expression matrix