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1,421 件 ・ 関連度順

概要と使いどころ

Visualises RNA-modification data with transcript-feature metagene plots (Guitar GuitarPlot; MetaPlotR; deepTools computeMatrix scale-regions), peak-centred heatmaps (ComplexHeatmap; deepTools plotHeatmap), IP-vs-input paired browser tracks (log2 IP/input bigWig via deepTools bamCompare; pyGenomeTracks; Gviz; IGV/UCSC track hubs), DRACH sequence-logo plots (ggseqlogo; MEME), feature-distribution stacked bars, and volcano/MA plots for differential modification. Establishes stop-codon enrichment in the metagene plot as the biological QC anchor for any MeRIP dataset (Dominissini 2012; Meyer 2012). Use when producing the canonical metagene plot with stop-codon enrichment as a QC anchor, building paired IP/input genome-browser tracks at single-locus resolution, plotting peak-centred heatmaps clustered by condition, summarising peak distribution across transcript features, generating DRACH motif logos as sanity checks, rendering volcano plots of differential m6A, or reproducing the stop-codon enrichment plot.

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。

GPTomics/bioSkills1,2232026年8月15日 更新

Add p-value brackets, significance asterisks, and effect-size annotations to distribution plots using ggpubr, ggsignif, and statannotations with correct test selection (parametric vs non-parametric vs paired), multiple-testing adjustment, and rendering of negative results. Use when a boxplot/violin/raincloud needs in-figure statistical comparisons between groups.

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。

GPTomics/bioSkills1,2232026年8月15日 更新

Build circular genome visualizations using circlize (R), pyCirclize (Python), or Circos (Perl CLI) with ideogram tracks, multi-data tracks (scatter, histogram, heatmap), chord/link arcs for interactions, and explicit circos.clear() between plots. Covers when circular is appropriate vs when Cartesian wins (Cleveland-McGill 1984), karyograms, and chromosome adjacency in chord diagrams. Use when adjacency on the circle conveys meaning — chromosome-level overview, structural variants, Hi-C interactions, cross-genome comparisons.

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。

GPTomics/bioSkills1,2232026年8月15日 更新

Quantifies CRISPR editing outcomes with CRISPResso2 (Clement 2019 Nat Biotechnol) across Cas9-nuclease (indels, HDR), CBE and ABE base editors (target conversion + bystander), and prime editor (pegRNA-templated) modes. Covers single-amplicon (CRISPResso), multi-sample batch (CRISPRessoBatch), pooled-amplicon (CRISPRessoPooled), WGS off-target (CRISPRessoWGS), and sample-comparison (CRISPRessoCompare) workflows; quantification-window math that controls what is called edited; substitution-vs-indel diagnostic to distinguish BE from Cas9 contamination; MMEJ deletion pattern interpretation; allele-frequency tables; and failure modes from amplicon misalignment or contamination. Use when quantifying editing from amplicon sequencing, choosing CRISPResso mode by design, distinguishing intended edits from bystanders and indel byproducts, debugging low-alignment runs, or generating publication-grade editing reports.

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。

GPTomics/bioSkills1,2232026年8月15日 更新

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.

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。

GPTomics/bioSkills1,2232026年8月15日 更新

Build a differential-ready consensus peakset from per-replicate ATAC-seq peaks using iterative overlap removal, fixed-width re-centering, and majority-rule overlap. Use when generating a stable peak coordinate system for downstream differential accessibility, ML feature engineering, cross-sample comparison, or fixed-width peak counts; covers Corces 2018 iterative overlap (501 bp), DiffBind summit re-centering, and ENCODE consistency rules.

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。

GPTomics/bioSkills1,2232026年8月15日 更新

Detects aberrant splicing in single rare-disease patients vs a control panel using FRASER 2.0 (Bioconductor; Beta-binomial autoencoder on Intron Jaccard Index, default delta cutoff 0.1, q hyperparameter), OUTRIDER (gene-level outlier expression via autoencoder denoising), LeafcutterMD (Dirichlet-multinomial outlier mode of LeafCutter for annotation-free junctions), and DROP (Snakemake pipeline integrating FRASER2 + OUTRIDER + monoallelic expression for clinical diagnostics). The statistical model is fundamentally different from differential splicing — single-sample-vs-cohort outlier detection rather than two-group comparison. Standard tool in EU rare-disease (Solve-RD) and NIH UDN programs. Use when applying RNA-seq to undiagnosed Mendelian disease, validating predicted splice variants in clinical samples, or detecting cryptic splicing in disease tissue.

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。

GPTomics/bioSkills1,2232026年8月15日 更新

Fetch WeatherKit current, minute, hourly, and daily forecasts; weather alerts; iOS 18+ changes, historical comparisons, summaries, and statistics; and required Apple Weather attribution. Use when integrating weather data, showing forecasts or alerts, caching WeatherKit responses, displaying attribution, or reviewing WeatherKit query limits in iOS apps.

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。

dpearson2699/swift-ios-skills1,1992026年8月1日 更新

Use when capturing or analyzing an iOS .memgraph, especially when the task mentions a memory leak, heap growth, persistent memory increase, ownership path, or matched-capture comparison with Apple CLI tools. Covers unambiguous Simulator capture, leaks/heap/vmmap/malloc_history evidence, raw artifact preservation, and same-flow verification. Use debugging-instruments for interactive Xcode Memory Graph, Instruments, generic retain-cycle inspection, or LLDB work.

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。

dpearson2699/swift-ios-skills1,1992026年8月1日 更新

Deep competitive intelligence for any market. Analyzes competitors' products, pricing, customer sentiment, GTM strategy, and growth signals using real web data. Produces battle cards, pricing landscape, and feature matrix. Use when the user wants to understand their competitive landscape, analyze competitors, compare products in a market, or research who they're competing against. Triggers for "who are my competitors", "competitive analysis", "competitor research", "battle cards", "pricing comparison", "competitor pricing", "market players", "competitive intelligence", "competitive landscape", "who else is in this space", "competitive moat", or any request to profile, compare, or map competitors in a category. Works standalone — no prior startup-design session needed.

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。

ferdinandobons/startup-skill1,1922026年7月1日 更新

Supply Chain Bottleneck Analyzer for Walmart Marketplace sellers. Diagnose cash flow, inventory, WFS costs, and referral fees. Includes comparison with Amazon FBA, lower storage fee optimization, and Walmart Connect ad spend analysis. No API key required for basic analysis.

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。

nexscope-ai/eCommerce-Skills1,1512026年8月26日 更新

Walmart profit margin calculator for sellers. Calculate cost breakdowns including WFS fulfillment, storage fees, and referral fees. Includes comparison with Amazon FBA and lower competition advantage analysis. No API key required.

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。

nexscope-ai/eCommerce-Skills1,1512026年8月26日 更新

Brand monitoring tool for tracking mentions across social media platforms. Monitor Reddit, Google News, YouTube, and DuckDuckGo for brand mentions. Includes sentiment analysis, trend tracking, crisis detection, and competitor comparison. No API key required for basic monitoring.

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。

nexscope-ai/eCommerce-Skills1,1512026年8月26日 更新

Competitor research — pricing comparison, bestseller analysis, differentiation strategy

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。

nexscope-ai/eCommerce-Skills1,1512026年8月26日 更新

Compare and optimize shipping rates across carriers and fulfillment methods. UPS, FedEx, USPS, DHL rate comparison, zone optimization, and shipping strategy to maximize margins.

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。

nexscope-ai/eCommerce-Skills1,1512026年8月26日 更新

Clean a raw transcript before ingestion: punctuate, paragraph, label speakers, fix mistranscribed technical terms, and split long recordings by topic. Use this skill when the user drops an auto-generated transcript, subtitle file, podcast or lecture transcript, meeting recording text, or asks to process a video or audio source. Do NOT use for text that is already prose, for summarising a transcript, or for the ingestion itself.

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。

undefined-ui/second-brain-os1,0702026年10月10日 更新

Produce a research report from the vault: scope the question against existing pages, name the gaps, and write findings with citations, disagreements and limits. Use this skill when the user asks for a research report, a deep write-up on a topic, or wants to understand a subject thoroughly using what they have collected. Do NOT use for a quick answer from the vault, for drafting an article in the user's voice, or for summarising a single source.

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。

undefined-ui/second-brain-os1,0702026年10月10日 更新

Test website responsiveness across viewport widths using browser automation. Resizes a single session through breakpoints, screenshots each width, and detects layout transitions (column changes, nav switches, overflow). Produces comparison reports showing exactly where layouts break. Trigger with 'responsiveness check', 'check responsive', 'breakpoint test', 'viewport test', 'responsive sweep', 'check breakpoints', or 'test at mobile'.

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。

jezweb/claude-skills1,0632026年10月9日 更新

Plan the smallest set of diagnostic, comparison, paper, and appendix figures or tables needed to support verified mathematical-modeling decisions and claims.

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。

zhnnky329/MathModeling-skills1,0572026年9月24日 更新

When the user wants to analyze competitors for SEO, content, backlinks, or positioning. Also use when the user mentions "competitor analysis," "competitor research," "competitor keywords," "competitor backlinks," "link gap," "content gap," "competitor content," "competitive analysis," or "competitor comparison." For content roadmap, use content-strategy.

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。

kostja94/marketing-skills1,0382026年10月6日 更新

When the user wants to create SEO pages at scale using templates and data—including AI-assisted, grounded copy for per-URL differentiation (vs rigid mail-merge templates). Also use when the user mentions "programmatic SEO," "programmatic SEO pages," "template pages," "scale content," "location pages," "city pages," "comparison pages at scale," "X vs Y pages," "integration pages," "pages from data," "automated landing pages," or "programmatic landing pages." Uses a playbook matrix aligned to skills under skills/pages. For user-facing template galleries or marketplaces (browse → use), use template-page-generator.

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。

kostja94/marketing-skills1,0382026年10月6日 更新

Evaluate, select, and contract with vendors and SaaS tools. Use this skill when comparing alternatives, running an RFP, scoring vendors against criteria, negotiating contracts, planning a switch, or assessing a vendor's risk. Triggers on vendor evaluation, RFP, vendor selection, build vs buy, SaaS evaluation, vendor scorecard, vendor comparison, contract negotiation, vendor switch, procurement. Also triggers when a renewal is coming up or when a tool isn't meeting expectations.

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。

rampstackco/claude-skills9652026年10月7日 更新

How to design and run a programmatic SEO program that produces durable traffic instead of penalty-bait. Data source identification, template design, schema patterns, quality control at scale, internal linking architecture, crawl budget management, AEO/GEO for programmatic pages, refresh discipline, and the make-or-break question of whether pSEO is the right answer for your program at all. Triggers on programmatic SEO, pSEO, scaled content, page generation, template SEO, location pages, comparison pages, directory site, listing site, scaled landing pages, programmatic content. Also triggers when a content set is not ranking, has been hit by an algorithm update, or when a team is considering pSEO as a growth lever.

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。

rampstackco/claude-skills9652026年10月7日 更新

Kubernetes diagnostics for metrics, health checks, resource comparisons, and cluster analysis. Use when analyzing cluster health, comparing environments, or gathering diagnostic 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。

rohitg00/kubectl-mcp-server9642026年4月9日 更新