「oci」の検索結果

Performs gene-level association from GWAS summary statistics via genetically predicted tissue expression using FUSION, PrediXcan, S-PrediXcan, S-MultiXcan, UTMOST, MOSTWAS, kTWAS, EpiXcan, TIGAR-V2, and probabilistic fine-mapping with FOCUS and MA-FOCUS. Use when running TWAS from GWAS sumstats, prioritising candidate causal genes from a GWAS lead locus, picking single-tissue vs cross-tissue models, identifying LD-induced TWAS false positives, choosing ancestry-matched prediction weights, fine-mapping co-regulated TWAS hits, or triangulating TWAS with cis-eQTL Mendelian randomization and colocalization to nominate a causal gene.

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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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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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Decide when to order coronary artery calcium (CAC) scoring in a primary-prevention patient and interpret the result per the 2026 ACC/AHA multisociety dyslipidaemia guideline. Covers the Class 1 indication (men ≥40 / women ≥45, borderline / intermediate PREVENT-ASCVD risk, uncertainty about LLT), CAC score interpretation (0, 1–99, 100–299, ≥300, ≥1000), how CAC modifies LDL and non-HDL goals, when to repeat CAC, and pitfalls (incidental CAC on non-cardiac CT, radiation, cost). Use when a clinician asks should I order a CAC score, CAC indications, what does CAC 150 mean, treatment goals with CAC score, repeat CAC frequency, CAC in a smoker, CAC vs CCTA, is CAC useful in intermediate risk. Grounded in the 2026 ACC/AHA multisociety dyslipidaemia guideline.

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Work a primary-prevention patient through the 2026 ACC/AHA multisociety dyslipidaemia guideline CPR framework — Calculate (10-year and 30-year PREVENT-ASCVD), Classify (low / borderline / intermediate / high), Personalize (demographic, clinical, biomarker, and reproductive risk enhancers), and Reclassify (coronary artery calcium scoring where appropriate). Use when a clinician asks how to assess ASCVD risk for primary prevention, who needs a statin, borderline risk patient what to do, intermediate risk should I start a statin, risk enhancers to look for, premature family history of ASCVD how does it change risk, pregnancy-related risk factors, PCOS and cardiovascular risk. Grounded in the 2026 ACC/AHA multisociety dyslipidaemia guideline.

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Set absolute LDL-C, non-HDL-C, and ApoB treatment goals, PLUS percent LDL-C reduction, for a primary-prevention patient on lipid-lowering therapy per the re-introduced treatment goals in the 2026 ACC/AHA multisociety dyslipidaemia guideline. Covers goals by PREVENT-ASCVD category (low / borderline / intermediate / high), by CAC score, in severe hypercholesterolaemia / FH, in diabetes with multiple ASCVD risk factors, and the ApoB targets once LDL-C and non-HDL-C goals are met. Use when a clinician asks what LDL goal to aim for, LDL target for intermediate risk, non-HDL goal, ApoB target, dual goals on statin, patient at goal or not, how low should LDL go, statin not enough what next. Grounded in the 2026 ACC/AHA multisociety dyslipidaemia guideline.

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Order and interpret lipoprotein(a) [Lp(a)] measurement at least once in a lifetime, apply the risk-enhancer threshold (≥125 nmol/L or ≥50 mg/dL), and run cascade screening of first-degree relatives for premature ASCVD, familial hypercholesterolaemia, or elevated Lp(a) per the 2026 ACC/AHA multisociety dyslipidaemia guideline. Covers the Class 1 lifetime measurement, how elevated Lp(a) affects LLT initiation and intensification, the cascade screening indications, the interaction of Lp(a) with ASCVD risk estimation, and current therapeutic limitations. Use when a clinician asks when to check Lp(a), how often to repeat Lp(a), elevated Lp(a) what next, treatment for high Lp(a), should I screen my patient's family, Lp(a) and statins, cascade screening indications. Grounded in the 2026 ACC/AHA multisociety dyslipidaemia guideline.

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Calculate and interpret the PREVENT-ASCVD risk score (10-year and 30-year) for primary prevention of atherosclerotic cardiovascular disease per the 2026 ACC/AHA multisociety dyslipidaemia guideline. Covers inputs required, risk-category thresholds (low <3%, borderline 3–<5%, intermediate 5–<10%, high ≥10%), when to use the 30-year calculation (adults 30–59), and how PREVENT differs from the older Pooled Cohort Equations (lower risk estimates by 40–50%, race-agnostic). Use when a clinician asks what the 10-year ASCVD risk is, how to calculate PREVENT, PCE vs PREVENT, risk category for this patient, does my patient need a statin, 30-year risk calculation, primary prevention risk assessment. Grounded in the 2026 ACC/AHA multisociety dyslipidaemia guideline.

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。

Interact with AgentGram social network for AI agents.

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Planifie le prochain sprint : calcule la capacité (vélocité glissante 3 sprints), reporte les tickets non livrés du sprint courant, puis complète depuis le backlog par priorité jusqu'à la capacité. Présente le plan, attend validation, puis assigne les tickets au sprint. Usage: /plan-sprint [<titre-sprint-cible>]

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Use when balancing eng-team velocity vs quality vs burnout — on-call load, focus fragmentation, reorg shock. Triggers on 'team is burning out', 'why is velocity dropping'.

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Generate brand assets — banners, social cards, CIP elements — with brand-token injection + provider routing. Use when generating a banner / social image / branded asset.

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Run evidence-disciplined Xiaohongshu social listening for foreign pharma employee pain points. Use when the user asks to collect and analyze notes/comments about pharma companies, aliases, roles, compliance, medical affairs, or AI topics, then produce a cited and scored sampled-insight report. Includes independent-evidence counting, MediaCrawler batch collection, and CAPTCHA/461 fallback to Agent Reach/OpenCLI.

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Generates infographic image card series with 12 visual styles, 8 layouts, and 3 color palettes. Breaks content into 1-10 cartoon-style image cards optimized for social media engagement. Use when user mentions "小红书图片", "小红书种草", "小绿书", "微信图文", "微信贴图", "image cards", "图片卡片", baoyu-xhs-images, or wants social media infographic series.

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Design phishing and social engineering simulations with explicit authorization and measurable outcomes.

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Use when drafting, reviewing, or revising Xiaohongshu/Douyin/social-platform Chinese text so it has real internet-native judgment instead of README tone, technical-briefing tone, or mechanical meme-word stuffing.

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Generate Guizang-style social cards, Xiaohongshu carousels, 3:4 covers, and WeChat 21:9 plus 1:1 cover pairs from articles, scripts, screenshots, notes, subtitles, or photos.

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Spearphishing simulation is a targeted social engineering attack vector used by red teams to gain initial access. Unlike broad phishing campaigns, spearphishing uses OSINT-derived intelligence to craf

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METAINFORMANT rules for directory scripts/gwas/association. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.

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Apply the 90/10 visual-to-text rule when composing a piece on a canvas (poster, card, social post). Use when the deliverable lives on a single fixed surface where each element competes for attention.

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Trabajo con genogramas: Reconocimiento y reflexión sobre los patrones de relaciones familiares. Perspectiva multigeneracional, símbolos del genograma, reconocimiento de patrones y recursos en la historia familiar.

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KI-gestuetzte Textproduktion in drei Teilskills: Allgemeine Texte (Blogpost, Social, Newsletter, Copy, E-Mail, Bericht), narrative Storys (Skript, Kurzgeschichte, RPG, Weltenbau) und PR-Kommunikation (Pressemitteilung, Positionspapier) mit lokalem LaTeX-PDF-Compiler. Kein externer Dienst zwingend erforderlich.

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Create and process videos using AI generation (Runway, Pika, Replicate, Sora, Veo) and FFmpeg processing. MCP bridge provides frame extraction (extract_video_frames); the Design Stack media worker handles full FFmpeg processing (resize, trim, compress, GIF, format conversion). Covers social-media-optimized video output. Use when generating AI videos, extracting frames/thumbnails, transcoding videos, creating GIFs from clips, or preparing video for social platforms.

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Generate images using AI models — Gemini, DALL·E, Stable Diffusion, Midjourney, Flux, Leonardo, Ideogram, and more. MCP bridge tools are primary; the Design Stack media worker is the fallback for advanced providers. Covers prompt engineering, model selection, size/aspect ratios, style parameters, batch generation, multi-site awareness, and WordPress integration. Use when you need to create hero images, social graphics, product mockups, brand illustrations, or any visual asset for marketing, social media, or e-commerce.

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。