perseus-statistical-analyzer
Perseus statistical analysis skill for proteomics data analysis and visualization
Profile →npx skills add a5c-ai/babysitter --skill perseus-statistical-analyzer --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.
# Perseus Statistical Analyzer Skill ## Purpose Enable Perseus statistical analysis for proteomics data analysis and visualization. ## Capabilities - Missing value imputation - Normalization strategies - Statistical testing (t-test, ANOVA) - Hierarchical clustering - PCA and enrichment analysis - Publication-quality plots ## Usage Guidelines - Impute missing values appropriately - Normalize data before statistical analysis - Apply appropriate statistical tests - Visualize results with clustering and PCA - Generate publication-quality figures - Document normalization and imputation methods ## Dependencies - Perseus - MSstats - limma ## Process Integration - Mass Spectrometry Proteomics Pipeline (ms-proteomics-pipeline) - Multi-Omics Data Integration (multi-omics-integration)
- Purpose
- Capabilities
- Usage Guidelines
- Dependencies
- Process Integration
What does the perseus-statistical-analyzer skill do?
Perseus statistical analysis skill for proteomics data analysis and visualization
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill perseus-statistical-analyzer --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.