「event」の検索結果

Detect horizontal gene transfer (HGT / LGT) using compositional methods (GC%, codon usage, tetranucleotide z-scores via SIGI-HMM, AlienHunter, IslandViewer 4, IslandPath-DIMOB), phylogenetic-incongruence methods (AvP, HGTphyloDetect, ALE / GeneRax / AleRax reconciliation, RANGER-DTL), and BLAST-distribution methods (HGTector v2, DarkHorse, Alien Index). Use when screening prokaryote genomes for genomic islands and HGT events, distinguishing HGT from incomplete lineage sorting / differential gene loss / hybridization, mapping donor lineages via phylogenetic placement, separating eukaryotic HGT from contamination, ruling out gBGC as a false signal, or quantifying DTL rates with ALE/GeneRax on bacterial trees.

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Identify recurrent and driver copy number alterations across a tumor cohort with GISTIC2 (G-score, Ziggurat deconstruction, focal vs broad/arm-level analysis, q-values from permutation) and quantify copy-number signatures with the Steele 2022 COSMIC framework and the Drews 2022 CINSignatures framework. Covers driver-gene localization from recurrence peaks, distinguishing focal drivers from arm-level passengers, and the caller-sensitivity caveats of copy-number signatures. Use when finding recurrently amplified or deleted regions in a cohort, localizing driver genes, separating focal from broad events, running GISTIC2, or extracting copy-number mutational signatures.

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Normalize read-depth copy-ratio profiles and segment them into copy-number regions using circular binary segmentation (CBS, DNAcopy), hidden Markov models, HaarSeg, and fused-lasso methods. Covers GC-content, mappability, and replication-timing (wave-artifact) bias correction, panel-of-normals/PCA denoising, diploid-baseline centering, and algorithm selection by sequencing depth and event size. Use when choosing a segmentation algorithm, correcting depth bias, diagnosing oversegmentation or a mis-centered baseline, tuning CBS or HMM parameters, or understanding why a downstream CNV caller produced fragmented or shifted segments.

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Computes sample size and power for clinical trials including continuous, binary, and time-to-event endpoints; superiority, non-inferiority, and equivalence designs; FDA 2016 non-inferiority margin selection with M1/M2 framework; Schoenfeld 1981 and Lakatos 1988 for survival; Schuirmann TOST and 80-125% bioequivalence; minimum clinically important difference (MCID) vs δ distinction. Use when justifying trial size in protocol or SAP per CONSORT 2025 item 16a.

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Prepares statistical reports for clinical trials following CONSORT 2025, SPIRIT 2025, ICH E9(R1) estimands, and FDA 2023 covariate adjustment guidance. Covers Table 1 generation, analysis populations (ITT/FAS/PP/Safety), the 5 ICH E9(R1) intercurrent-event strategies, MMRM under MAR (mmrm), reference-based MI (rbmi J2R/CR/CIR), Permutt tipping-point sensitivity, and Rubin's-rules vs frequentist variance debate. Use when preparing regulatory submissions, defining estimands, or implementing missing-data sensitivity analyses.

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Creates sashimi-style plots showing RNA-seq read coverage and splice junction counts using ggsashimi (general-purpose, condition-grouped overlays), rmats2sashimiplot (rMATS-output-aware), MAJIQ-VOILA (LSV posteriors interactive HTML), leafviz (leafcutter clusters Shiny), Jutils (tool-agnostic heatmaps and sashimi for rMATS/leafcutter/MntJULiP/MAJIQ output), or pyGenomeTracks (multi-track publication figures). Tool choice depends on the upstream differential-splicing tool's output format and the publication vs interactive use case. Use when visualizing specific splicing events, validating differential splicing calls, or producing publication-quality figures.

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Assesses RNA-seq data quality specifically for alternative splicing analysis. QC layers include experimental design audit (library prep, read length, depth, replicates), STAR 2-pass cohort-style alignment, junction saturation curves and discovery plateau detection, novel-vs-known junction ratio diagnostics, junction-overhang distribution, splice-site strength scoring (MaxEntScan intrinsic + SpliceAI context-aware), strandedness verification, GENCODE basic vs comprehensive choice, and rRNA contamination screening. Splicing analysis is more demanding than DGE on read length, depth, library prep, alignment strategy, and annotation choice — failures silently bias PSI estimates and inflate novel-junction false positives. Use when evaluating data suitability for splicing analysis, troubleshooting low event detection, or designing sequencing experiments where AS is a primary endpoint.

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Analyzes alternative splicing at single-cell resolution. The first decision is library chemistry — 10X 3' is fundamentally limited (RT primes from poly-A, R2 falls in 3' UTR, <0.1 junction read per cell per AS event). Plate-based full-length methods (Smart-seq3, FLASH-seq, VASA-seq, STORM-seq) and single-cell long-read (MAS-Iso-seq, scISOr-Seq2) are the chemistries that give per-cell isoform structure. Tools include MARVEL (R, Smart-seq integrated), BRIE2 (Bayesian PSI with regulatory features and ELBO_gain test), scQuint (junction-cluster, plate-based; not for 10X), SpliZ (annotation-free Z-score), Psix (graph-smoothness regulated AS), and Sierra (alternative polyadenylation, often confused with AS). Use when analyzing isoform usage in scRNA-seq, identifying cell-type-specific splicing, or determining whether scRNA-seq chemistry supports splicing analysis at all.

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Analyzes alternative splicing from PacBio Iso-Seq (HiFi, Kinnex/MAS-Iso-seq) and Oxford Nanopore (direct cDNA, direct RNA, R10.4.1+) long-read RNA-seq with full-isoform resolution. Tools include FLAIR (correct/collapse/quantify/diffSplice for PacBio + ONT), IsoQuant (de-novo or annotation-guided isoform discovery 2024 SOTA), Bambu (annotation-aware Bayesian discovery + quantification with Novel Discovery Rate), SQANTI3 (isoform classification: FSM/ISM/NIC/NNC + artifact flags), rMATS-long (event calling on long-read isoforms), and minimap2 (-ax splice:hq for HiFi; -ax splice -k14 for ONT cDNA; add -uf only for direct RNA or stranded cDNA preps). Solves microexon detection, recursive splicing, complex multi-exon isoforms, and DTU without transcript-quantification uncertainty. Use when short-read AS limitations (anchor length, complex isoforms, microexons, recursive splicing, transcript ambiguity) demand full-isoform resolution.

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Mandatory operating rules for ANY task involving KiCAD projects. Loaded when the user mentions KiCAD, schematics, PCBs, or any .kicad_* file. Prevents file corruption by routing all changes through Konnect MCP tools.

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Use when the user mentions memory leak prevention, code review for memory issues, or proactive leak checking — retain cycles, leaks, and Timer/observer patterns.

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Use when the user mentions concurrency checking, Swift 6 compliance, data race prevention, or async code review.

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Use when building ANY macOS app — windows, menus, sandboxing, distribution, AppKit bridging or modernization (control events, state restoration, concentric corners), or macOS-specific SwiftUI patterns.

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Review TDesign Flutter 组件的公开 Demo、API 收敛、Flutter 设计模式、主题、测试和 Golden 证据。以小程序公开 Demo 作为可见效果参考，但不机械映射其 props/events；适用于组件对齐和 PR Review。

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Implement and review Apple TipKit feature-discovery UI for iOS 17+ apps. Use when adding or auditing in-app tips, contextual help, coach marks, Tip, TipView, popoverTip, rules, events, actions, display frequency, testing overrides, reusable tip identifiers, or iOS 18+ TipGroup and CloudKit tip sync; avoid for generic SwiftUI navigation or layout outside tip presentation.

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Optimize App Store product pages for search visibility and conversion. Use for App Store Optimization (ASO), keyword research, app name/subtitle/keyword-field strategy, conversion-focused descriptions and promotional text, screenshot captions and ordering, Custom Product Pages with assigned search keywords, In-App Events, Product Page Optimization tests, localized metadata, ratings/review strategy, and in-app review prompt timing with RequestReviewAction or AppStore.requestReview. Also use when routing ASO vs App Store review, privacy/ATT, or StoreKit implementation boundaries.

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Verify device legitimacy and app integrity using DeviceCheck (DCDevice per-device bits) and App Attest (DCAppAttestService key generation, attestation, and assertion flows). Use when implementing fraud prevention, detecting compromised devices, validating app authenticity with Apple's servers, protecting sensitive API endpoints with attested requests, or adding device verification to a backend architecture.

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Discover and configure Bluetooth and Wi-Fi accessories using AccessorySetupKit. Use when presenting a privacy-preserving accessory picker, defining discovery descriptors for BLE or Wi-Fi devices, handling accessory session events, migrating from CoreBluetooth permission-based scanning, or setting up accessories without requiring broad Bluetooth permissions.

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Query grid electricity forecasts and submit load events using EnergyKit to help users optimize home electricity usage. Use when building smart home apps, EV charger controls, HVAC scheduling, or energy management dashboards that guide users to use power during cleaner or cheaper grid periods.

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Manages MongoDB Atlas Stream Processing (ASP) workflows. Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations for streaming data workloads and event processing. NOT for general MongoDB queries or Atlas cluster management. Requires MongoDB MCP Server with Atlas API credentials.

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Use when building, modifying, or reviewing a Stripe App — or when the user describes something that implies one (e.g. "add a panel to the customer page", "customize my Stripe Dashboard", "react to Stripe events from my app", "connect my service to Stripe without sharing API keys"). Covers the full app development workflow (scaffold, preview, upload, versioning), UI extension architecture (sandboxed iframe, Stripe UI toolkit, viewports), extension types (UI extensions, backend-only, extension interfaces, embedded apps), authentication (platform keys, OAuth, restricted API keys), stripe-app.yaml manifest setup (permissions, viewports, CSP), webhook configuration for apps, Secret Store API, `fetchStripeSignature` auth, and marketplace publishing, plus submitting one agentic feedback report after a build. Use when the user mentions Stripe Apps, UI extensions, @stripe/ui-extension-sdk, @stripe/extensibility-sdk, script extensions, stripe-app.yaml, Dashboard extensions, or customizing the Stripe Dashboard.

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Deploys and operates a LiveKit agent in production: shipping a version to LiveKit Cloud and rolling it back, secrets and configuration, the worker process model and prewarming, safe async inside worker processes, provider timeouts and degradation, graceful shutdown, SDK upgrades, and observability. Use when the user says "deploy my agent", "roll back the deployment", "tail the agent logs", "the first call after a restart is slow", "attached to a different loop / event loop is closed", "prewarm the VAD", "shut down without dropping calls", "upgrade livekit-agents safely", "correlate logs by session", or is changing an agent codebase that is already live. Not for designing the agent (building-livekit-agents) or reproducing one bad conversation locally (debugging-livekit-agents).

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Prevents crashes due to problematic scope-related API misuse caused by agent escalation into internal scope framework objects. Use when configuring properties of scope-related Simulink blocks or MATLAB objects — constrains the agent to documented APIs and directs users to the scope UI when a property is not programmatically accessible.

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Add OpenTelemetry tracing to MATLAB code. Use when the user asks to "add tracing", "instrument with spans", "add OpenTelemetry", "trace my code", "add observability" (when about tracing), or mentions "spans", "distributed tracing", or "OTel tracing" in the context of MATLAB functions. Covers span creation, parent-child context propagation, error handling, attributes, events, and semantic conventions.

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