deseq2-differential-expression
DESeq2 differential expression analysis skill with normalization, statistical modeling, and visualization
npx skills add a5c-ai/babysitter --skill deseq2-differential-expression --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# DESeq2 Differential Expression Skill ## Purpose Provide DESeq2 differential expression analysis with normalization, statistical modeling, and visualization. ## Capabilities - Size factor normalization - Negative binomial modeling - Shrinkage estimation - Batch effect modeling - Multi-factor designs - Result visualization (MA plots, volcano plots) ## Usage Guidelines - Design experiments with appropriate replication - Include batch effects in model when present - Apply appropriate shrinkage estimators - Use multiple testing correction - Generate publication-quality visualizations - Document analysis parameters and thresholds ## Dependencies - DESeq2 - edgeR - limma-voom ## Process Integration - RNA-seq Differential Expression Analysis (rnaseq-differential-expression) - Single-Cell RNA-seq Analysis (scrnaseq-analysis) - CRISPR Screen Analysis (crispr-screen-analysis)
- Purpose
- Capabilities
- Usage Guidelines
- Dependencies
- Process Integration
What does the deseq2-differential-expression skill do?
DESeq2 differential expression analysis skill with normalization, statistical modeling, and visualization
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill deseq2-differential-expression --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.