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bio-de-results

Maintainer FreedomIntelligence · Last updated April 1, 2026

Extract, filter, annotate, and export differential expression results from DESeq2 or edgeR. Use for identifying significant genes, applying multiple testing corrections, adding gene annotations, and preparing results for downstream analysis. Use when filtering and exporting DE analysis results.

OpenClawNanoClawAnalysisReproductionbio-de-results🧬 bioinformatics (gptomics bio-* suite)bioinformatics — differential expression & transcriptomicsextract

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-de-results

Maintainer: FreedomIntelligence
License: MIT
Last updated: April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

Extract, filter, and export differential expression results.
res <- results(dds, alpha = 0.05).

Source Doc

Excerpt From SKILL.md

Extracting DESeq2 Results

Goal: Retrieve DE statistics from a fitted DESeq2 model as a usable data frame.

Approach: Call results() with optional shrinkage, then convert to a data frame with gene identifiers.


## With log fold change shrinkage

res <- lfcShrink(dds, coef = 'condition_treated_vs_control', type = 'apeglm')

## Convert to data frame

res_df <- as.data.frame(res)
res_df$gene <- rownames(res_df)

Use cases

Use for identifying significant genes, applying multiple testing corrections, adding gene annotations, and preparing results for downstream analysis.
Use when filtering and exporting DE analysis results.