bio-flow-cytometry-differential-analysis
Differential abundance and state analysis for cytometry data. Compare cell populations between conditions using statistical methods. Use when testing for significant changes in cell frequencies or marker expression between groups.
npx skills add majiayu000/claude-skill-registry --skill differential-analysis --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.
# Differential Analysis ## Differential Abundance (DA) ```r library(CATALYST) library(diffcyt) # Load clustered data sce <- readRDS('sce_clustered.rds') # Create design matrix design <- createDesignMatrix(ei(sce), cols_design = 'condition') # Create contrast contrast <- createContrast(c(0, 1)) # Treatment vs Control # Differential abundance test res_DA <- testDA_edgeR(sce, design, contrast, cluster_id = 'meta20') # View results rowData(res_DA)$cluster_id rowData(res_DA)$p_adj # Significant clusters sig_DA <- rowData(res_DA)$p_adj < 0.05 table(sig_DA) ``` ## Differential State (DS) ```r # Test for marker expression differences within clusters res_DS <- testDS_limma(sce, design, contrast, cluster_id = 'meta20', markers_include = rownames(sce)[rowData(sce)$marker_class == 'state']) # Results per marker per cluster ds_results <- rowData(res_DS) ``` ## Visualization ```r # DA results heatmap plotDiffHeatmap(sce, res_DA, all = TRUE, fdr = 0.05) # DS results heatmap plotDiffHeatmap(sce, res_DS, all = TRUE, fdr = 0.05) # Abundance by condition plotAbundances(sce, k = 'meta20', by = 'cluster_id', group_by = 'condition') ``` ## Manual Statistical Testing ```r library(tidyverse) # Get cluster
- Differential Abundance (DA)
- Differential State (DS)
- Visualization
- Manual Statistical Testing
- Mixed Effects Models
- CITRUS (Automated Discovery)
- Volcano Plot
- Export Results
- Multiple Comparisons
- Related Skills
What does the bio-flow-cytometry-differential-analysis skill do?
Differential abundance and state analysis for cytometry data. Compare cell populations between conditions using statistical methods. Use when testing for significant changes in cell frequencies or marker expression between groups.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill differential-analysis --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 majiayu000/claude-skill-registry, a repository with 534 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.