950 件 ・ 関連度順
概要と使いどころ
Zenith performs gene set analysis on the result of differential expression using linear (mixed) modeling with dream by considering the correlation between gene expression traits. This package implements the camera method from the limma package proposed by Wu and Smyth (2012). Zenith is a simple extension of camera to be compatible with linear mixed models implemented in variancePartition::dream().
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MEM, Marker Enrichment Modeling, automatically generates and displays quantitative labels for cell populations that have been identified from single-cell data. The input for MEM is a dataset that has pre-clustered or pre-gated populations with cells in rows and features in columns. Labels convey a list of measured features and the features' levels of relative enrichment on each population. MEM can be applied to a wide variety of data types and can compare between MEM labels from flow cytometry,
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Expert knowledge for Azure Digital Twins development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when modeling DTDL graphs, integrating IoT Hub/ADx, configuring endpoints/routes, securing access, or tuning query units, and other Azure Digital Twins related development tasks. Not for Azure IoT Hub (use azure-iot-hub), Azure IoT Central (use azure-iot-central), Azure IoT Operations (use azure-iot-operations).
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Use when creating a Cubit or Bloc, modeling state with sealed classes or status enums, wiring BlocBuilder/BlocListener/BlocProvider, writing bloc tests, or choosing between Cubit and Bloc.
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Security design principles, STRIDE threat modeling, OWASP Top 10 architectural mitigations, and secure patterns. Load when designing systems or reviewing architecture for security.
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Clojure language-specific patterns, data-first modeling, REPL-driven development, and spec
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Cyber threat intelligence and OSINT analysis toolkit. Runs structured investigations and delivers analyst-grade intelligence products with sourced, trust-scored findings. Use for OSINT and CTI cases, digital-footprint and exposure review, domain/subdomain/DNS/certificate recon, web-infrastructure pivoting (favicon hashes, tracker IDs, TLS certs, phishing-kit fingerprinting, campaign clustering), username/email/phone enumeration, breach and infostealer-log triage, image forensics, geolocation, crypto-wallet and IBAN/bank-account tracing, darknet search, M365/Azure and SaaS tenant recon, China/Sinophone recon (ICP filings, PRC corporate registries, Baidu/FOFA/Quake/ZoomEye), vulnerability and ransomware lookup, threat modeling, PII redaction, and structured reporting. Commands include /case, /sweep, /query, /webpivot, /username, /phone, /email-deep, /breach-deep, /icp, /cn-corp, /iban, /stealer-log, /exposure, /threat-model, /report, /brief, /redact, /apikeys.
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根据指定字段设计Couchbase订单文档模型（单桶策略），并生成包含引用完整性的N1QL插入语句。
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Your climate and energy brain trust. 25 named personas across 7 cells covering energy transition, carbon markets, climate modeling, sustainability, grid infrastructure, environmental policy, and ESG.
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Clarify domain concepts, language, boundaries, and durable architectural decisions. Use when terminology is ambiguous, the user is shaping a domain model, or a design depends on resolving what concepts mean.
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Apply MongoDB data-modeling, indexing, and query rules from access patterns. Use when designing schemas, choosing embed vs reference, or tuning MongoDB query behavior.
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Design relational or document schemas from access patterns, cardinality, and lifecycle. Use when modeling entities, choosing embed vs normalize, or shaping schema boundaries before implementation.
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Configure ViewModel state emission with StateFlow, SharedFlow, and sealed UiState classes in Android. Use for state modeling and sharing policies; defer generic lifecycle collection, navigation-event plumbing, Hilt injection, test code, and configuration-change recipes to their specific skills.
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Create a repository-grounded AppSec threat model covering assets, trust boundaries, attackers, abuse paths, and mitigations. Use only for explicit threat-modeling requests, not general architecture or code review.
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Document modeling, aggregation pipeline, indexing strategy, change streams, and multi-document transactions.
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Azure Functions, Cosmos DB modeling, Service Bus patterns, Bicep templates
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Graph database implementation for relationship-heavy data models. Use when building social networks, recommendation engines, knowledge graphs, or fraud detection. Covers Neo4j (primary), ArangoDB, Amazon Neptune, Cypher query patterns, and graph data modeling.
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Strategic guidance for designing modern data platforms, covering storage paradigms (data lake, warehouse, lakehouse), modeling approaches (dimensional, normalized, data vault, wide tables), data mesh principles, and medallion architecture patterns. Use when architecting data platforms, choosing between centralized vs decentralized patterns, selecting table formats (Iceberg, Delta Lake), or designing data governance frameworks.
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Design comprehensive security architectures using defense-in-depth, zero trust principles, threat modeling (STRIDE, PASTA), and control frameworks (NIST CSF, CIS Controls, ISO 27001). Use when designing security for new systems, auditing existing architectures, or establishing security governance programs.
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Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a GLOSSARY.md, or recording or editing an ADR.
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Write, review, or modernize F# code in .NET repositories with functional-first design, algebraic data types, pattern matching, pipelines, async workflows, project ordering, and C# interop. USE FOR: F# .fs/.fsproj code; discriminated unions, records, options, results, pattern matching, computation expressions, or functional domain modeling; strongly typed AI-generated .NET code. DO NOT USE FOR: C# language modernization; FSI-only exploratory scripts with no project changes. INVOKES: inspect .fsproj file order and SDK settings, edit F# source and project files, and run dotnet build/test or dotnet fsi validation commands when changes are made.
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Use XTwitterScraper when a .NET application needs typed access to Xquik's X automation REST API for tweet search, user lookup, posting workflows, extraction jobs, monitors, webhooks, or giveaway draws. USE FOR: integrating the XTwitterScraper NuGet package; reviewing Xquik API client usage; modeling API-key configuration, pagination, binary exports, raw responses, retries, and webhook/event flows in .NET. DO NOT USE FOR: unrelated stacks; direct browser automation; generic social-media strategy; or code that does not call Xquik. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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Use the open-source free `NetArchTest.Rules` library for architecture rules in .NET unit tests. Use when a repo wants lightweight, fluent architecture assertions for namespaces, dependencies, or layering. USE FOR: the repo uses or wants NetArchTest.Rules; architecture rules should be enforced in automated tests. DO NOT USE FOR: very rich architecture modeling that needs a heavier DSL. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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Integrate ManagedCode.Orleans.Graph into an Orleans-based .NET application for grain-call policy enforcement, deadlock detection, live-call telemetry, and Mermaid graph diagnostics. USE FOR: ManagedCode.Orleans.Graph integration; allowed grain transitions; Orleans call filters; live policy graphs; reviewing Orleans call-cycle risk. DO NOT USE FOR: generic graph data modeling or traversal unrelated to Orleans calls. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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