하나의 Skill, 완전히 새로운 가능성. 다음 워크플로를 찾아보세요.
capa-officer
CAPA system management for medical device QMS. Covers root cause analysis, corrective action planning, effectiveness verification, and CAPA metrics. Use when running CAPA investigations, 5-Why analysis, fishbone diagrams, root cause determination, corrective action tracking, effectiveness verification, or CAPA program optimization.
amazon-aurora-postgresql
Amazon Aurora PostgreSQL — creates, modifies, and advises on Aurora PostgreSQL clusters specifically (PostgreSQL-compatible engine, Aurora serverless, express configuration, pgvector, Babelfish). Trigger for Aurora PostgreSQL cluster operations, express-configuration quick-start, ACU sizing, I/O-Optimized storage, commitment pricing, or PostgreSQL upgrade p…
shell-completion-generator
Generate shell completion scripts for bash, zsh, and fish from CLI command definitions. Creates intelligent completions with argument suggestions, file completions, and dynamic values.
root-cause-analyzer
Systematic root cause identification skill with 5 Whys, fishbone diagrams, fault tree analysis, and hypothesis testing
tooluniverse-spatial-omics-analysis
Spatial multi-omics interpretation pipeline. Transforms spatially variable genes (SVGs), domain annotations, and tissue context into biological insights via domain-by-domain characterization, cell-type composition, spatial gene expression patterns, RNA+protein+metabolite integration. Use for Visium, MERFISH, seqFISH, Slide-seq, spatial proteomics, and spati…
tooluniverse-model-organism-genetics
Cross-species genetic analysis using model organism databases (MGI mouse, IMPC systematic knockout phenotyping, ZFIN zebrafish, FlyBase fruit fly, WormBase worm, SGD budding yeast plus protein-domain/PTM/literature detail, PomBase fission yeast, RGD rat, GeneNetwork systems-genetics/eQTL panels, HumanMine/MouseMine cross-species data-warehouse search, GBIF …
tooluniverse-spatial-omics-analysis
Spatial multi-omics interpretation pipeline. Transforms spatially variable genes (SVGs), domain annotations, and tissue context into biological insights via domain-by-domain characterization, cell-type composition, spatial gene expression patterns, RNA+protein+metabolite integration. Use for Visium, MERFISH, seqFISH, Slide-seq, spatial proteomics, and spati…
tooluniverse-spatial-transcriptomics
Spatial transcriptomics analysis — Visium, MERFISH, seqFISH, Slide-seq. Maps gene expression to tissue architecture, identifies spatially variable genes (SVGs), tissue-domain segmentation, and cell-cell interaction inference. Use for spatial gene-expression questions, tissue architecture analysis, and SVG identification.
tooluniverse-model-organism-genetics
Cross-species genetic analysis using model organism databases (MGI mouse, IMPC systematic knockout phenotyping, ZFIN zebrafish, FlyBase fruit fly, WormBase worm, SGD budding yeast plus protein-domain/PTM/literature detail, PomBase fission yeast, RGD rat, GeneNetwork systems-genetics/eQTL panels, HumanMine/MouseMine cross-species data-warehouse search, GBIF …
tooluniverse-spatial-omics-analysis
Spatial multi-omics interpretation pipeline. Transforms spatially variable genes (SVGs), domain annotations, and tissue context into biological insights via domain-by-domain characterization, cell-type composition, spatial gene expression patterns, RNA+protein+metabolite integration. Use for Visium, MERFISH, seqFISH, Slide-seq, spatial proteomics, and spati…
tooluniverse-spatial-transcriptomics
Spatial transcriptomics analysis — Visium, MERFISH, seqFISH, Slide-seq. Maps gene expression to tissue architecture, identifies spatially variable genes (SVGs), tissue-domain segmentation, and cell-cell interaction inference. Use for spatial gene-expression questions, tissue architecture analysis, and SVG identification.
bio-atac-seq-enhancer-gene-linking
Predict enhancer-gene regulatory connections from ATAC-seq using ABC, ENCODE-rE2G, HiChIP, or Cicero. Use when linking distal enhancers to target genes, choosing between contact-aware (ABC, ENCODE-rE2G), accessibility-only (Cicero), and orthogonal (HiChIP H3K27ac, EpiMap) approaches, validating predictions against CRISPRi-FlowFISH gold-standard, or building…
bio-clinical-biostatistics-categorical-tests
Tests associations between categorical variables in clinical data using chi-square, Fisher's exact, Boschloo, Cochran-Mantel-Haenszel, and modern McNemar variants with calibrated confidence intervals (Wilson, Newcombe, Miettinen-Nurminen). Use when analyzing categorical outcomes, paired binary endpoints, or testing treatment-outcome independence in confirma…
bio-ecological-genomics-edna-metabarcoding
Processes eDNA metabarcoding from raw paired-end reads to species tables, navigating ASV (DADA2, UNOISE3) vs OTU (swarm v2) decision (Callahan 2017 vs Schloss multi-copy-16S critique), marker/primer choice (Leray COI, MiFish 12S, 515F/806R 16S, ITS2) with primer-specific bias, OBITools3 v3 command-name break (obi stats plural; .tar.gz taxonomy), tag-jumping…
bio-experimental-design-randomization-blocking
Structures biological experiments so inference is valid by construction, covering Fisher's principles (randomization, replication, local control), the experimental-vs-observational unit distinction and pseudoreplication (Hurlbert 1984; Lazic 2018), randomization mechanics (complete, restricted, stratified, rerandomization, run-order), blocking layouts (rand…
bio-genome-assembly-genome-profiling
Profiles a genome from raw reads BEFORE assembly with a k-mer spectrum (KMC or Jellyfish histogram), then models it with GenomeScope2 to estimate genome size, heterozygosity, repeat content, and ploidy, and Smudgeplot to infer ploidy from heterozygous k-mer pairs (diploid AB vs triploid AAB vs tetraploid AABB). Covers choosing k via Merqury best_k.sh, the k…
bio-genome-intervals-overlap-significance
Tests whether two genomic interval sets overlap (colocalize) more than expected by chance using a permutation test against a structured-genome null model. Covers bedtools fisher (analytic 2x2 screen), bedtools shuffle + jaccard permutation, GAT (isochore/GC-conditioned simulation with FDR), regioneR (flexible permutation, randomizeRegions vs circularRandomi…
bio-pathway-go-enrichment
Runs Gene Ontology over-representation analysis (ORA) on a gene LIST with clusterProfiler enrichGO, the one-sided hypergeometric/Fisher 2x2 test phyper(k-1, M, N-M, n, lower.tail=FALSE). Covers why the BACKGROUND universe (not the gene list) is the null and decides significance, why omitting universe= is a bug, why enrichGO defaults to ont='MF' not 'BP', wh…
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