「rag」の検索結果

Analyzes CUT&RUN (Skene Henikoff 2017) and CUT&Tag (Kaya-Okur 2019) chromatin profiling data. Handles SEACR vs MACS2 peak calling (with the btaf375 2025 benchmark guidance), pA-MNase vs pA-Tn5 vs pAG-Tn5 chimera differences, E. coli spike-in carryover normalization, IgG-only control logic (no input), characteristic fragment-size signatures (25-75 bp for CUT&Tag), and lower depth requirements (5M reads typical vs 25M for ChIP). Use when calling peaks from CUT&RUN/CUT&Tag, scaling by E. coli spike-in carryover, choosing SEACR norm mode, or comparing CUT&RUN/Tag results to traditional ChIP.

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。

Enumerates virtual chemical libraries via reaction SMARTS transformations using RDKit and Reaction templates, with explicit handling of atom mapping, template extraction (RDKit reaction mining), product validation, RECAP/BRICS fragmentation, R-group decomposition, matched molecular pair analysis (MMPA), and Free-Wilson analysis. Use when generating combinatorial libraries from building blocks, enumerating analog series, deriving structure-activity rules, or extracting transformations from reaction 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。

Assesses ChIP-seq quality across antibody specificity, fragmentation, enrichment, replicate concordance, and library complexity. Computes FRiP, NSC/RSC (phantompeakqualtools), library complexity (NRF/PBC1/PBC2), deepTools plotFingerprint (JS distance, AUC, synthetic JS), ChIPQC, IDR with ENCODE Nself/Nt rules, and detects hyper-ChIPable artifacts. Use when validating an antibody, diagnosing failed peak calls, deciding whether to proceed with downstream analysis, grading against ENCODE thresholds, or auditing replicate concordance.

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。

ATAC-seq library quality control -- TSS enrichment, FRiP, fragment-size periodicity, library complexity (NRF/PBC1/PBC2), mitochondrial fraction, and ENCODE 4 thresholds. Use when assessing whether an ATAC-seq library passes ENCODE acceptance criteria, diagnosing transposition artefacts, comparing Omni-ATAC vs standard prep quality, or selecting which replicates to drop before peak calling.

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Detects differential alternative splicing between conditions using rMATS-turbo (binomial LRT on junction counts), leafcutter (Dirichlet-multinomial GLM on intron clusters), MAJIQ V3 deltapsi/HET (Bayesian posterior on LSVs), SUPPA2 (empirical-null on TPM-derived PSI), or Shiba (junction-imbalance-corrected, 2025 SOTA at low coverage). Reports FDR-corrected significance and delta PSI effect sizes. Tools differ in statistical model, annotation dependence, calibration regime, and replicate-count requirements. Use when comparing splicing patterns between treatment groups, tissues, or disease states.

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。

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/SUPPA2/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.

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。

Map nucleosome center positions, occupancy, and fuzziness from ATAC-seq fragment-size patterns using NucleoATAC, ATACseqQC, DANPOS3, or scprinter. Use when characterizing nucleosome organization at promoters and enhancers, calling +1/-1 nucleosomes flanking NFRs, generating V-plots for chromatin structure visualization, or comparing nucleosome positioning between conditions.

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 trucking insurance — types of coverage (commercial auto, cargo, occupational accident, workers comp, bobtail/non-trucking, MCS-90 endorsement), federal minimums (49 CFR 387), what each covers, owner-operator vs company-driver implications, and how to read a Certificate of Insurance (COI). Cite 49 CFR 387.

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Use this skill when the user asks about CMV roadside inspection levels (Level I through Level VIII), what each level inspects, average inspection times, CVSA decal eligibility, what triggers a level upgrade, and how to coach drivers through a roadside inspection. Reference CVSA North American Standard Inspection Program.

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Use this skill when the user asks about weigh-station bypass services — Drivewyze, PrePass, BestPass, NORPASS, OOIDA toll savings — how they work, eligibility criteria, costs, and how they tie into CSA scores. Reference each provider's coverage area + pricing.

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 US-Mexico cross-border CMV operations — long-haul cross-border program, B-1 visas for Mexican drivers, FMCSA OP-1(MX) authority, US-Mexico border commercial zones, USMCA / NAFTA implications, customs brokerage (C-TPAT, FAST), and how a US carrier handles cross-border loads. Reference 49 CFR 365.501-507.

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 Household Goods (HHG) movers — 49 CFR 375 + 376 consumer protection rules, FMCSA HHG-specific authority, mover certification, binding vs non-binding estimates, dispute resolution, weight ticket requirements, valuation coverage, and how HHG operations differ from general freight. Cite 49 CFR 375.

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 when a carrier asks how to improve MPG, lower fuel cost per mile, manage fuel surcharge, set up a fuel-purchase strategy (in-network vs out-of-network), train drivers on fuel-efficient driving, spec new tractors for fuel economy, or benchmark fleet MPG against industry averages.

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Use when a carrier (asset-based, brokerage, or 3PL) asks how to respond to a shipper RFP / RFQ — bid packaging, lane analysis, rate strategy, SOPs/SOWs, qualifications response, insurance compliance, EDI requirements, and how to win competitive bids without leaving margin on the table.

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Audit an existing Coval evaluation setup for coverage, misleading scores, missing evidence, judge validation and execution risk. Read-only; use when inheriting an eval or deciding whether its results support a release decision.

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 a compact Coval test set from product requirements, observed conversation failures or a coverage gap. Design realistic scenarios with separate expected behaviors, provenance and controlled voice/persona variation.

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Analyze a Coval adversarial / red-team testing report and turn it into an agent-hardening plan. Use when a user provides a Coval report URL, report export, run IDs, screenshots, or a per-scenario scorecard from an adversarial sweep and wants evidence-backed next steps such as prompt/guardrail changes, refusal hardening, verification fixes, escalation routing, or expanded attack coverage.

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。

Analyze a Coval accent testing report from runs across different speaker accents. Use when a user provides a Coval report URL, report export, run IDs, screenshots, or metric summary and wants evidence-backed next steps such as prompt changes, STT/confirmation adjustments, accent-robust routing, or expanded accent coverage.

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。

Analyze a Coval audio-quality testing report from runs across different voice, speaking-style, volume, interruption, and background-noise scenarios. Use when a user provides a Coval report URL, report export, run IDs, screenshots, or metric summary and wants evidence-backed next steps such as prompt changes, tool handling fixes, STT/TTS adjustments, trace setup, or expanded audio-scenario coverage.

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。

Run the pytest test suite with coverage. Accepts optional filter flags. Use after making changes to verify nothing broke.

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。

Profound LLM citation tracker (extension). Time-series brand citation rates across ChatGPT, Perplexity, and other LLMs. Pairs with seo-seranking for triangulated AI visibility coverage.

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。

The WindowPanel component and Window Manager. Use when a window won't drag/resize/minimize, the tray is missing, window state doesn't persist, rendering `<WindowPanel>` on a page, or editing features/window-panels/** or windowManagerSlice.ts. NOT for opening/registering overlays (use overlay-system).

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Recipe for creating or changing a floating window panel. Use when adding a window, editing a window component, adding persistence, onCollectData, or ephemeral mode, wiring the Tools grid, or a window fails to restore after reload. NOT for WindowPanel drag/resize/tray internals (use window-panels).

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。

react-resizable-panels v4 rules for this SSR codebase. Use when importing react-resizable-panels (PanelGroup and PanelResizeHandle are v3 names), editing components/ui/resizable* or features/code/layout/, building a split-pane, sidebar, or drag-handle layout, or persisting or toggling panel sizes.

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。