「apply」の検索結果

Trains and applies base-resolution deep learning models on ChIP-seq / ChIP-nexus / CUT&RUN data. Uses BPNet (Avsec 2021 Nat Genet 53:354; soft motif syntax from ChIP-nexus), chromBPNet (Pampari A et al 2025 Nat Genet; bias-factorized base-resolution profiles), EnFormer (Avsec 2021 Nat Methods 18:1196; 196 kb input, ~100 kb effective receptive field), DeepSEA (Zhou 2015; multi-task CNN), and JASPAR 2026 deep-learning collection (1259 BPNet ChIP models). Performs in silico mutagenesis for variant-effect prediction, DeepLIFT/Grad attribution, and TF-MoDISco motif discovery from attribution scores. Use when predicting variant effects on TF binding, discovering soft motif syntax / cooperativity, integrating ChIP-seq with sequence-only predictions, or applying precomputed JASPAR Deep Learning models to new variants.

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Calls ChIP-seq peaks with MACS3, MACS2, HOMER, or SPP across narrow (TF) and broad (histone) modes. Handles input control matching, fragment-size modeling vs --nomodel, effective genome size, ENCODE-style IDR vs naive overlap, hyper-ChIPable artifacts, and aligner-specific shifts. Use when calling peaks from ChIP-seq alignments, choosing between narrow vs broad mode for a histone mark, deciding model vs nomodel for low-depth data, applying ENCODE pseudoreplicate IDR, or reconciling MACS vs HOMER vs SPP results.

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Detects aberrant splicing in single rare-disease patients vs a control panel using FRASER 2.0 (Bioconductor; Beta-binomial autoencoder on Intron Jaccard Index, default delta cutoff 0.1, q hyperparameter), OUTRIDER (gene-level outlier expression via autoencoder denoising), LeafcutterMD (Dirichlet-multinomial outlier mode of LeafCutter for annotation-free junctions), and DROP (Snakemake pipeline integrating FRASER2 + OUTRIDER + monoallelic expression for clinical diagnostics). The statistical model is fundamentally different from differential splicing — single-sample-vs-cohort outlier detection rather than two-group comparison. Standard tool in EU rare-disease (Solve-RD) and NIH UDN programs. Use when applying RNA-seq to undiagnosed Mendelian disease, validating predicted splice variants in clinical samples, or detecting cryptic splicing in disease tissue.

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Call accessible chromatin regions from ATAC-seq BAM files using MACS3, MACS2, Genrich, or HMMRATAC. Use when identifying open chromatin from aligned ATAC-seq, choosing between point-source vs HMM peak callers, applying ENCODE-style pseudoreplicate IDR, removing blacklist regions, or fixing 501bp consensus peaks for downstream differential analysis.

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Iteratively detects and auto-fixes technical debt in a codebase using three quality criteria from debt-analysis references: conditional branch simplification, encapsulation, and separation of concerns. Applies fixes directly to code, runs existing tests to verify no regressions, re-analyzes, and loops until all high-severity issues are resolved or max iterations (5) reached. Use this skill when you want to automatically improve code quality with real code changes, reduce technical debt systematically, or clean up code to meet quality standards. Trigger on phrases like "fix technical debt", "clean up code quality", "refactor and fix issues", "improve code quality automatically", "apply debt fixes", "fix code problems", "eliminate debt".

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Initialize or resume the SDD Composy workspace of a repository: preview missing governance and OKF bundle files, apply only approved absent paths, persist the artifact language, and verify. Use when a project needs SDD set up or resumed — 'inicializar o SDD', 'configurar o workspace SDD', 'run init first', or when any SDD skill returned not_initialized. Do NOT use for generic CLAUDE.md or repository setup outside SDD Composy, or for other plugins' init.

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Reconcile SDD Composy task Markdown and the JSON projection: read-only inspect and plan, then apply only with an explicit authority and the CONFIRM-SDD-SYNC token. Use when task contracts and operational state diverged — 'sincronizar as tarefas', 'o JSON das tasks está desatualizado', 'markdown and json disagree'. Do NOT use to list or advance tasks (sdd-tasks), for a status overview (sdd-status), or to simulate approval.

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Use when starting any conversation in a repository that uses PWDEV Power - establishes how to find and apply Power skills before any response, including clarifying questions

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Analyze a completed phase diff for high-confidence behavior-preserving simplifications and apply only explicitly approved proposals. Use after execution and before review to reduce duplication, dead code, needless complexity, or avoidable inefficiency.

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Diagnóstico e operação de Kubernetes — pods, deployments, ingress, HPA, PVC, StorageClass, NetworkPolicy, Secrets, Helm, ArgoCD, cert-manager. Use quando o usuário disser "kubernetes", "k8s", "pod", "deployment", "ingress", "CrashLoopBackOff", "não sobe", "escalar", "helm", "argocd". Leitura livre; apply, scale, delete passam pelo portão.

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Format Haskell source files: *.hs, *.lhs, and *.hsig, with the project's configured formatter: fourmolu, ormolu, or stylish-haskell. Use before compiling, after source edits, and when applying project style.

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Apply continuous improvement principles to iteratively enhance processes, code quality, team practices, and system performance through small, incremental changes. Use when improving development processes, optimizing workflows, reducing waste, enhancing code quality over time, implementing retrospective learnings, or fostering a culture of continuous improvement.

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Introduce the cross-section read interface boundary (I<Section>ServiceRead) for one section's service per memory/architecture/section-read-write-split.md. Audits the surface, evaluates which methods belong on the read interface, sets up the workspace, dispatches a subagent that introduces the interface and migrates non-section callers, opens a PR. Use when the user says 'read split for X', 'split <Section>Service', 'add I<Section>ServiceRead boundary', 'apply the section-read-write-split rule to <Section>', or any variation of carving the cross-section read surface out of a section's full service interface. Reference implementation is Teams (PR 678). Operates on one section per invocation.

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When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' 'consumer behavior,' 'anchoring,' 'social proof,' 'scarcity,' 'loss aversion,' 'framing,' or 'nudge.' Use this whenever someone wants to understand or leverage how people think and make decisions in a marketing context.

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Apply DESIGN, canon, and modules to every page in the inventory, producing a deployable static HTML site. Three render branches (approved page, template-applied sibling, unique render). Per-page, incremental, idempotent, content-preserving by default.

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Apply a Content Driven Development process to AEM Edge Delivery Services development. Use for ALL code changes - new blocks, block modifications, CSS styling, bug fixes, core functionality (scripts.js, styles, etc.), or any JavaScript/CSS work that needs validation.

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[BETA] Expert assistance for the Adobe I/O CLI plugin `@adobe/aio-cli-plugin-aem-rde` — the `aio aem rde` / `aio aem:rde` command tree used to deploy, inspect, log-tail, snapshot, and troubleshoot AEM Rapid Development Environments (RDEs). Activate ONLY when the user explicitly references RDE concepts: 'AEM RDE', 'Rapid Development Environment', `aio aem rde`, `aio aem:rde`, `aem-rde`, RDE snapshots, RDE deploy/install, `rde install`, `rde inspect`, `rde status`, `rde history`, `rde reset`, the `@adobe/aio-cli-plugin-aem-rde` package, or Cloud Manager program/environment configuration that is specifically for an RDE environment. Do NOT activate on generic AEMaaCS phrases like 'deploy to AEM Cloud', 'push my bundle', 'tail the publish log', 'cloud sandbox', or unqualified 'dispatcher-config / frontend / env-config deployments' — those belong to Cloud Manager pipelines, not RDE. This skill is in beta. Verify all outputs before applying them to production projects.

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Guides Rust performance optimization. Use when profiling, benchmarking, reducing allocations, improving cache locality, choosing between rayon/async/threads, or applying SIMD/parallelism.

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Guides type-driven design in Rust. Use when encoding invariants in types, applying newtype pattern, implementing type state machines, using PhantomData, or making invalid states unrepresentable.

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Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.

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Whole-repo audit for over-engineering. Like ponytail-review, but scans the entire codebase instead of a diff: a ranked list of what to delete, simplify, or replace with stdlib/native equivalents. Use when the user says "audit this codebase", "audit for over-engineering", "what can I delete from this repo", "find bloat", "ponytail-audit", or "/ponytail-audit". One-shot report, does not apply fixes.

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Read all suggested PR changes and apply them directly to the codebase. Use when you have PR review comments to address, suggested changes to implement, or feedback to incorporate into your code.

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Sanguo RAG unresolved mention resolution loop. Use for: 三國 RAG, unresolved mentions, alias review, observed mentions, MCQ triage, manual roster seeds, false-positive exclusion, running run_resolution_loop.py, applying unresolved-triage answers, delegating 三國名詞查證 to a web-capable agent, or Pilot ETL chunk experiments with LangChain text splitters / LangGraph / LangFlow around 張飛長坂橋等小樣本流程。

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Apply the Red-Green-Refactor cycle to software development. Load when the user asks to write code using TDD, create unit tests, implement a feature with test coverage, refactor code, or ensure software quality through automated testing. Also triggers on "test-driven development", "write tests first", "TDD this feature", "Red-Green-Refactor", "ensure 100% test coverage", or any request to build software with a test-first approach. Supports unit, integration, and end-to-end testing strategies.

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