deg-screening-analysis

1> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
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3# Differential Expression Gene Screening Analysis (Volcano Plot & Clustered Heatmap)
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5## When to Use
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7Use this skill when you need a reproducible two-group DEG workflow on a bulk expression matrix and want:
8- a full differential expression table
9- a filtered DEG table
10- a volcano plot
11- a clustered heatmap of top differential genes
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13Typical requests include:
14- compare case vs control samples with limma
15- screen upregulated and downregulated genes from a normalized expression matrix
16- generate a DEG table with volcano and heatmap outputs from bulk transcriptome data
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18## Out of Scope
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20Do not use this skill for:
21- single-cell RNA-seq workflows
22- multi-group contrasts or factorial designs
23- count-model pipelines that require `DESeq2` or `edgeR`
24- batch correction, covariate-adjusted models, or generalized design-matrix consulting
25- non-expression omics data
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27If the request falls outside this scope, stop and hand off to a more appropriate analysis workflow instead of forcing the data through this skill.
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29## Practical Caveats
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31- `Diffanalysis.csv` currently exports `name`, `logFC`, `P.value`, and `P.adj`.
32- `--p_type` controls both DEG screening semantics and volcano plot significance semantics.
33- `plot/heatmap.pdf` is generated only when at least two heatmap genes remain after ranking.
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