「rope」の検索結果

Calculates statistical power for high-dimensional genomics experiments (bulk RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, methylation, proteomics) under negative-binomial count models using RNASeqPower, PROPER, and simulation via powsimR, distinguishing per-gene from marginal (transcriptome-wide) power, the role of mean expression and dispersion, and the sequencing-depth-versus-replicate tradeoff. Covers simulation as the honest default for overdispersed counts, FDR-aware average power versus single-test power, observed/post-hoc power as an anti-pattern, and the winner's-curse / Type-S / Type-M consequences of underpowering. Use when planning replicate number for a sequencing experiment, deciding whether to add depth or samples, choosing closed-form versus simulation power, estimating power from pilot dispersions, or justifying replication in a grant. For clinical-trial power see clinical-biostatistics/power-and-sample-size; for the inverse sample-size question see experimental-design/sample-size.

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。

Extracts, filters, annotates, and exports differential expression results from DESeq2 or edgeR with proper handling of padj=NA (independent filtering, Cook's outliers, all-zero), multiple-testing correction choice (BH vs Storey q-value vs IHW vs lfsr), TREAT vs post-hoc fold-change filtering, p-value histogram diagnostics, gene annotation via org.db/biomaRt/mygene, GSEA preranked input, ORA background construction, replication reality (Schurch 2016 small-n result), and SABV/sex-stratified reporting. Use when extracting and interpreting DE results, troubleshooting padj=NA, choosing FDR method, preparing ranked lists for pathway analysis, annotating gene IDs, or comparing DESeq2 vs edgeR outputs.

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。

Build forest plots (HR, OR, RR, beta-coefficient summaries with CIs) and funnel plots (meta-analysis publication-bias diagnostics) using forestplot, metafor, ggforest, and MendelianRandomization with proper axis-scaling, summary-diamond placement, subgroup nesting, and Egger / trim-and-fill asymmetry tests. Use when summarizing effects across subgroups, trials, or instruments — meta-analysis, Mendelian randomization, subgroup HRs.

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。

Predicts ADMET properties using ADMETlab 3.0 (119 endpoints with uncertainty), ADMET-AI, DeepChem MolNet, and chemprop D-MPNN with explicit handling of OECD QSAR principles, applicability domain assessment, calibration, hERG/CYP/AMES gold-standard endpoints, and PAINS / Lipinski / Ro5 / Veber / BBB druglikeness filters. Use when filtering compounds for drug-likeness, prioritizing leads by predicted safety, or building an in-house ADMET QSAR model.

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。

Designs novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based generators (DiGress, DiffSMol), and JT-VAE with explicit handling of multi-parameter optimization (MPO), goal-directed scoring functions, transfer/reinforcement/curriculum learning, synthetic accessibility scoring, and chemical space exploration vs exploitation. Use when designing new chemical matter against a target, decorating a scaffold, linking fragments, or optimizing a hit for multiple ADMET / activity properties simultaneously.

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。

Validate alignment quality with insert size distribution, proper pairing rates, GC bias, strand balance, and other post-alignment metrics. Use when verifying alignment data quality before variant calling or quantification.

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。

Use this skill when the user asks about passenger-carrying CMVs — buses, motorcoaches, charter operations, school buses, limousines, shuttle services. Covers different HOS rules (10-hour driving / 15-hour on-duty / no 34-restart), Class C CDL with P endorsement, S endorsement for school bus, FMCSA Hours-of-Service for passenger vehicles, $5M insurance minimum, BMC-32 filing, accessibility requirements, and how passenger ops differ from property. Cite 49 CFR 395.5 + 387.33.

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。

Use this skill when a driver needs to move a CMV within a yard, terminal, or property under § 395.8 yard-move provisions. Covers what counts as yard move, ELD configuration, and where yard move ends and on-duty driving begins.

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。

Use this skill to ensure IFTA decals are properly displayed on every IFTA-qualified vehicle. Covers decal placement, replacement, and what happens at inspection if missing.

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。

Use this skill when a driver believes an inspection was conducted improperly. Covers how to request re-inspection, when state agencies will honor it, and what to expect.

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。

Use this skill when the user asks anything that touches US Department of Transportation (DOT) or Federal Motor Carrier Safety Administration (FMCSA) regulation for commercial motor vehicles (CMVs) — including who's regulated, MC vs DOT number differences, operating authority, BOC-3 process agents, MCS-150 biennial updates, intrastate vs interstate distinctions, exemptions, or pointing to the right CFR section. Cite the actual regulation when answering. Don't guess; if you're not sure which Part applies, ask the user to clarify the operation type (for-hire vs private, passenger vs property, intra vs interstate, hazmat, gross weight rating).

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。

Use this skill when conducting a self-audit of your DQF library before an FMCSA compliance review. Covers the systematic approach to verifying all 12 documents are current, complete, and properly maintained.

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。

Use this skill to set proper expectations on how a DataQ challenge is actually reviewed. Covers state vs federal authority, typical timelines, and common review outcomes.

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。

Three.js materials - PBR, basic, phong, shader materials, material properties. Use when styling meshes, working with textures, creating custom shaders, or optimizing material performance.

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。

Layout structure for web interfaces, from grouping and alignment to reading order, progressive disclosure, and adaptive breakpoints. Use when structuring a page or component, spacing or aligning controls, deciding what collapses at small sizes, handling RTL layout direction, or reviewing frontend code for layout. Triggers on layout, spacing, alignment, grouping, negative space, whitespace, visual hierarchy, reading order, progressive disclosure, breakpoints, responsive layout, container queries, safe area, full-bleed, edge-to-edge, layout margins, RTL layout, logical properties.

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。

Design and generate Convex database schemas with proper validation, indexes, and relationships. Use when creating schema.ts or modifying table definitions.

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。

Set up Convex authentication with proper user management, identity mapping, and access control patterns. Use when implementing auth flows, setting up OAuth providers, or adding role-based access control.

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。

Create Convex queries, mutations, and actions with proper validation, authentication, and error handling. Use when implementing new API endpoints.

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。

Reflection-first problem solving methodology for Convex development. Use before implementing any solution to ensure proper root cause analysis, 98% code confidence, and minimal change scope.

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。

Generates PHPUnit unit tests for PHP 8.5. Creates isolated tests with AAA pattern, proper naming, attributes, and one behavior per test. Supports Value Objects, Entities, Services.

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。

Analyzes PHP code for immutability violations. Checks Value Objects, Events, DTOs for readonly properties, no setters, final classes, and wither patterns. Ensures domain objects maintain invariants.

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。

ABP Framework domain layer patterns including entities, aggregates, repositories, domain services, and data seeding. Use when: (1) creating entities with proper base classes, (2) implementing custom repositories, (3) writing domain services, (4) seeding data.

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。

When the user requests to add academic papers to a BibTeX bibliography file while maintaining format consistency and sourcing from appropriate repositories. This skill handles 1) Reading existing BibTeX files to understand formatting conventions, 2) Searching for academic papers across multiple sources (OpenReview for conference papers, arXiv for preprints), 3) Extracting proper BibTeX metadata from conference pages or arXiv entries, 4) Determining appropriate citation format (@article vs @inproceedings) based on publication venue, 5) Appending new entries while preserving existing file structure and formatting. Triggers include requests to 'add to ref.bib', 'update bibliography', 'cite papers', or when working with academic reference files.

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。

Write academic research documents following academic guidelines with peer-reviewed sources from Google Scholar and other academic databases. Always verify source credibility and generate IEEE standard references. Use for research papers, literature reviews, technical reports, theses, dissertations, conference papers, and academic proposals requiring proper citations and scholarly rigor.

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。