bio-experimental-design-sample-size
Estimates required sample sizes for differential expression, ChIP-seq, methylation, and proteomics studies. Use when budgeting experiments, writing grant proposals, or determining minimum replicates needed to achieve statistical significance for expected effect sizes.
npx skills add majiayu000/claude-skill-registry --skill sample-size-gptomics-bioskills --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.
# Sample Size Estimation ## RNA-seq Sample Size ```r library(ssizeRNA) # Estimate sample size for RNA-seq # m = total genes, m1 = expected DE genes # fc = fold change, fdr = target FDR result <- ssizeRNA_single(nGenes = 20000, pi0 = 0.9, m = 200, mu = 10, disp = 0.1, fc = 2, fdr = 0.05, power = 0.8) result$ssize # Required n per group ``` ## DESeq2-based Estimation ```r library(DESeq2) # From pilot data dds_pilot <- DESeqDataSetFromMatrix(pilot_counts, colData, ~condition) dds_pilot <- DESeq(dds_pilot) # Extract dispersion estimates for power calculation dispersions <- mcols(dds_pilot)$dispGeneEst median_disp <- median(dispersions, na.rm = TRUE) # Use median_disp in power calculations ``` ## Single-cell Sample Size ```r library(powsimR) # Estimate for scRNA-seq # Accounts for dropout and cell-to-cell variability params <- estimateParam(pilot_sce) power <- simulateDE(params, n1 = 100, n2 = 100, p.DE = 0.1, pLFC = 1) ``` ## Sample Size by Assay Type | Assay | Min Recommended | For Small Effects | |-------|-----------------|-------------------| | Bulk RNA-seq | 3 | 6-12 | | scRNA-seq | 3 samples, 1000 cells | 6+ samples | | ATAC-seq | 2 | 4-6 | | ChIP-seq | 2 | 3-4 | | Proteomics | 3
- RNA-seq Sample Size
- DESeq2-based Estimation
- Single-cell Sample Size
- Sample Size by Assay Type
- Budget Optimization
- Related Skills
What does the bio-experimental-design-sample-size skill do?
Estimates required sample sizes for differential expression, ChIP-seq, methylation, and proteomics studies. Use when budgeting experiments, writing grant proposals, or determining minimum replicates needed to achieve statistical significance for expected effect sizes.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill sample-size-gptomics-bioskills --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.