「soc」の検索結果

Build Manhattan, Miami, QQ, and locuszoom-style regional plots from GWAS, TWAS, PWAS, and QTL summary statistics with correct genomic-inflation diagnostics, multi-trait overlays, lead-SNP labeling, and LD-aware regional rendering. Use when visualizing association results across the genome, comparing two traits, computing genomic inflation lambda, or zooming into a locus with LD coloring.

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Build and analyze pangenomes for prokaryotes (Panaroo, PPanGGOLiN, PEPPAN, GET_HOMOLOGUES, anvi'o pangenomics) and eukaryotes (Minigraph-Cactus, PGGB, vg pangenome graphs). Implement Tettelin core/accessory/cloud genome decomposition (Tettelin 2005), Heap's law open/closed pangenome modeling, gene presence/absence GWAS (Scoary, pyseer), pangenome graph variant calling (vg, PanGenie), and structural-variation graph indexing. Use when assembling species- or genus-level pan-gene catalogs, separating core from accessory/shell/cloud genes, testing gene-content associations with phenotypes, building pangenome graphs from haplotype-resolved assemblies, calling SVs from pangenome graphs, or selecting between bacterial-pangenome and eukaryotic-pangenome workflows.

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Calls HLA class I and class II alleles at 2/4/6/8-field resolution from WGS/WES/RNA-seq/long-read data using OptiType, HLA-LA, T1K, Polysolver, HLA-HD, arcasHLA, StarPhase, or HIBAG imputation. Use when typing for HSCT, solid-organ transplant, neoantigen prediction, PGx screening (B*57:01, B*15:02, etc.), or disease-association studies, with reconciliation across tools and IPD-IMGT/HLA version mismatch handling.

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Maps GWAS-implicated loci to candidate effector (causal) genes by integrating variant-to-gene (V2G) features via Open Targets L2G (Mountjoy 2021), MAGMA gene-based association (de Leeuw 2015), FUMA SNP2GENE, cS2G combined SNP-to-gene scores (Gazal 2022), Polygenic Priority Scores (PoPS, Weeks 2023), FLAMES, INQUISIT, DEPICT, and enhancer-gene predictors (ABC, ENCODE-rE2G). Use when narrowing a GWAS lead locus to a candidate causal gene, picking between proximity, eQTL-based, and similarity-based prioritizers, integrating multi-evidence streams (fine-mapping, colocalization, ABC enhancer-gene, distance, chromatin), reconciling discordant L2G vs PoPS calls, prioritizing tissue-specific eQTL evidence, or triangulating across at least three independent lines of evidence for a publication-grade effector-gene nomination.

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Annotates ChIP-seq peaks to genomic features, nearest genes, ENCODE candidate cis-regulatory elements (cCREs), and regulatory domains. Uses ChIPseeker (R), HOMER annotatePeaks.pl (CLI), pyranges (Python), GREAT/rGREAT (regulatory domain gene-set enrichment), ChIP-Enrich (locus-length-adjusted), ENCODE SCREEN cCRE classification (PLS/pELS/dELS/CTCF-only/DNase-H3K4me3), and ENCODE-rE2G for cell-type-specific enhancer-gene linking. Handles nearest-TSS vs host-gene ambiguity, promoter window definition, and feature priority. Use when assigning genomic context to peaks, linking enhancer peaks to target genes, classifying peaks against ENCODE cCRE registry, or running gene-set enrichment on peak-associated genes.

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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 confirmatory or exploratory clinical trials.

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Identifies super-enhancers from H3K27ac, MED1, or BRD4 ChIP-seq using ROSE, ROSE2, LILY, HOMER -style super, and ENCODE dELS cross-referencing. Handles peak stitching parameters, ranking choices, hockey-stick inflection, marker choice (H3K27ac vs MED1/BRD4), and cross-condition comparison with spike-in normalization. Constructs core regulatory circuitry (Saint-Andre 2016) from SE-encoded TFs. Use when identifying cell-identity / cancer-associated regulatory domains, comparing super-enhancers between conditions, identifying master transcription factor networks, or predicting BET-inhibitor responsiveness.

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Resolves GWAS associations to candidate causal variants and credible sets via SuSiE, susie_rss, FINEMAP, CAVIAR, DAP-G, PAINTOR, PolyFun, SuSiEx, MultiSuSiE, and FOCUS. Use when narrowing a GWAS lead SNP to a 95 percent credible set, choosing between in-sample and reference LD, calibrating non-sparse loci with SuSiE-inf or FINEMAP-inf, integrating functional priors via PolyFun, fine-mapping across ancestries with SuSiEx, diagnosing LD mismatch via estimate_s_rss and kriging_rss, handling HLA or long-range LD, or feeding credible sets into coloc.susie for colocalization.

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Use this skill when the user asks how to manage a trucking carrier's public reputation — handling a major accident in the news, social media + Glassdoor + Indeed reviews, customer disputes that escalate, employee disputes, regulator perception, and how to communicate during a crisis. Reference industry PR + crisis communication practices.

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Configure an AI agent to send OpenTelemetry traces to Coval. Use when a user wants to add Coval tracing, instrument an agent for simulations or conversation monitoring, make traces show up in Coval, handle SIP/PSTN/WebSocket trace correlation, or replace the one-command wizard with a security-reviewable manual setup.

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Use whenever a form needs to accept ONE image and produce permanent public URLs for one or more platform-specific sizes (OG image, social posts, avatars, logos, favicons, app icons). Replaces every legacy image-URL input, single-size uploader, and base64-data-URL flow. Triggers when you see a manual `<input type="url">` for an image, a single-size uploader, or anywhere a `dataUrl` could leak into a clipboard or a saved record.

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Next.js route metadata, per-route favicons, OpenGraph, and Twitter cards. Use when adding a route or layout, adding a favicon or social share image, auditing missing metadata, naming tab titles, or touching createRouteMetadata, createDynamicRouteMetadata, generateFaviconMetadata, or titlePrefix.

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Bringing an existing table onto the platform base standard. Use when asked to canonicalize, retrofit, or 'Wave 3' a table, run apply_rls or an org backfill, retire a bespoke *_versions table, or move it onto platform comments/associations/permissions. NOT for a schema move (use db-move-table-schema).

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Locate CCSPlayerInventory::GetItemInLoadout in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the WeaponPaints gamedata entry "CCSPlayerInventory::GetItemInLoadout" (symbol CCSPlayerInventory_GetItemInLoadout). Non-virtual inventory method resolving a player's loadout item. Shortlist via callers inside CCSPlayerInventory code that walk the loadout item cache (m_pSOCache / CGCClientSharedObjectCache), and via the CSO/econ loadout message paths. The function takes an item definition index + loadout slot and returns the matching CEconItemView — the body iterates a small item list comparing definition indices and loadout slots. Trigger: CCSPlayerInventory_GetItemInLoadout, CCSPlayerInventory::GetItemInLoadout

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Locate CCSPlayerInventory::SendInventoryUpdateEvent in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the WeaponPaints gamedata entry "CCSPlayerInventory::SendInventoryUpdateEvent" (symbol CCSPlayerInventory_SendInventoryUpdateEvent). Shortlist via functions constructing the inventory-full-update usermessage/event around m_pSOCache contents for the owning controller. The body packs the SO cache snapshot and sends it via the GC/usermessage path. Cross-check with callers in inventory-dirty flows (weapon paint mutations). Trigger: CCSPlayerInventory_SendInventoryUpdateEvent, CCSPlayerInventory::SendInventoryUpdateEvent

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Writing style guide for technical content, social media, blog posts, READMEs, git commits, and developer documentation. Optimized to avoid AI detection patterns. Use when writing any content beyond code.

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Expert writing for technical content, social media, and developer documentation. Use when asked to write tweets, LinkedIn posts, blog posts, READMEs, commit messages, feature announcements, or any written content. Optimized to avoid AI detection patterns.

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Expert guidance for reviewing academic manuscripts submitted to journals, particularly in political science, economics, and quantitative social sciences. Use when asked to review, critique, or provide feedback on academic papers, research designs, or empirical strategies. Emphasizes methodological rigor, causal identification strategies, and constructive feedback on research design.

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Ably real-time messaging patterns, WebSocket channel management, message validation and processing, staleness filtering, error recovery strategies, collaborative editing with drag-and-drop, optimistic updates for voting, real-time board collaboration, and Ably integration best practices for ree-board project

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Agent-to-Agent (A2A) server configuration patterns for HTTP, STDIO, SSE, and WebSocket transports. Use when building A2A servers, configuring MCP transports, setting up server endpoints, or when user mentions A2A configuration, server transport, MCP server setup, or agent communication protocols.

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Ktor server patterns including routing DSL, plugins, authentication, Koin DI, kotlinx.serialization, WebSockets, and testApplication testing.

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Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

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Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

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C++ coding standards based on the C++ Core Guidelines (isocpp.github.io). Use when writing, reviewing, or refactoring C++ code to enforce modern, safe, and idiomatic practices.

日本語の概要は準備中です。原文の説明を表示しています。