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Extract the genomic locations of genes, transcripts, exons, introns, and CDS, for the gene models stored in a TxDb object. A TxDb object is a small database that contains the gene models of a given organism/assembly. Bioconductor provides a
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Provides Bayesian PCA, Probabilistic PCA, Nipals PCA, Inverse Non-Linear PCA and the conventional SVD PCA. A cluster based method for missing value estimation is included for comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA o
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BEER implements a Bayesian model for analyzing phage-immunoprecipitation sequencing (PhIP-seq) data. Given a PhIPData object, BEER returns posterior probabilities of enriched antibody responses, point estimates for the relative fold-change in comparison to negative control samples, and more. Additionally, BEER provides a convenient implementation for using edgeR to identify enriched antibody responses.
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This package is a implementation of biclustering ensemble method MoSBi (Molecular signature Identification from Biclustering). MoSBi provides standardized interfaces for biclustering results and can combine their results with a multi-algorithm ensemble approach to compute robust ensemble biclusters on molecular omics data. This is done by computing similarity networks of biclusters and filtering for overlaps using a custom error model. After that, the louvain modularity it used to extract biclus
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Client for the gypsum REST API (https://gypsum.artifactdb.com), a cloud-based file store in the ArtifactDB ecosystem. This package provides functions for uploads, downloads, and various adminstrative and management tasks. Check out the docu
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Reactome is a free, open-source, curated and peer-reviewed pathway database. Their goal is to provide intuitive bioinformatics tools for the visualization, interpretation and analysis of pathway knowledge.
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Provides efficient containers for storing and manipulating short genomic alignments (typically obtained by aligning short reads to a reference genome). This includes read counting, computing the coverage, junction detection, and working wit
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HiContacts provides a collection of tools to analyse and visualize Hi-C datasets imported in R by HiCExperiment.
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Provides guidance for writing and benchmarking optimized Triton kernels for AMD GPUs (MI355X, R9700) on ROCm, targeting HuggingFace diffusers (LTX-Video, SD3, FLUX) and transformers. Core kernels: RMSNorm, RoPE 3D, GEGLU, AdaLN. Includes XCD swizzle, autotune, diffusers integration patterns, and LTX-Video pipeline injection.
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Provides guidance for writing, optimizing, and benchmarking Triton kernels for Intel XPU GPUs (Battlemage/Arc Pro B50) using the Xe-Forge optimization framework. Includes an LLM-driven trial-loop workflow (analyze, validate, benchmark, profile, finalize), XPU-specific patterns (tensor descriptors, GRF mode, tile swizzling), KernelBench fused kernels, and Flash Attention.
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Provides guidance for writing and benchmarking optimized CUDA kernels for NVIDIA GPUs (H100, A100, T4) targeting HuggingFace diffusers and transformers libraries. Kernels must be kernel-builder/ABI3-compliant: no pybind11, no setup.py, TORCH_LIBRARY_EXPAND bindings only. Supports models like LTX-Video, Stable Diffusion, LLaMA, Mistral, and Qwen. Includes integration with HuggingFace Kernels Hub (get_kernel) for loading pre-compiled kernels. Includes benchmarking scripts to compare kernel performance against baseline implementations.
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Provides guidance for writing, optimizing, and benchmarking C++ CPU kernels with SIMD intrinsics (AVX2/AVX512) for the Hugging Face kernels ecosystem. Includes a two-phase workflow: Phase 1 correctness (generic → AVX2) and Phase 2 performance exploration (AVX512 with branching trial loop), runtime CPU dispatch, OpenMP threading, and brgemm integration for GEMM-heavy kernels.
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META skill — build the largest possible qualified lead list for any request, end to end. Orchestrates discovery (Prospeo + GetLeads + Blitz + Google Maps + lookalike snowball from /list-expander), AI qualification with live-website verify, uncapped contact pull (GetLeads → Blitz → Prospeo), and provider emails (GetLeads/Blitz/Prospeo) validated with MillionVerifier before sending. Use for any "build me a list", "get me leads for X", "find everyone who...", client list request, or campaign list build. Starts with a 7-line intake brief; outputs to Postgres, Google Sheet, and/or CSV (asks which).
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This skill should be used when searching for people/leads using the Prospeo Search Person API. It provides the correct API format, filter types, rate limiting patterns, and state-by-state crawling techniques to overcome the 25K result limit. Use when building lead lists, searching by job title/industry/location, or integrating with Prospeo.
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Use this skill when changing service structure, Subscribers, ServiceProviders, Container wiring, bootstrapping, Context classes, or any code that may affect the core caching engine in WP Rocket. Also use it when reading constants, writing unit tests that depend on constants, or opening a pull request.
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Read and refresh wp-rocket's pre-built dependency graph at .claude/graph/dependency-graph.json. Use to locate a class file, trace dependencies, find the ServiceProvider that wires a service, or enumerate Subscribers in a module — without re-scanning the codebase from scratch. This skill is primarily a reader: the graph is built (and incrementally refreshed) by `node bin/build-knowledge-graph.js`. Invoke this skill at session start (to refresh if stale) and before grep/glob searches for class relationships.
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Full brand naming workflow for founders, agencies, and businesses. Use this skill whenever the user says "help me name this brand", "brand naming", "I need a name for", "name ideas for", "what should I call my brand/company/product", "naming a startup", "brand name suggestions", "help with naming", or shares a brand brief and asks for name options. Also triggers when the user shares existing name options and asks for feedback, evaluation, ranking, or scoring of those names. Auto-detects whether to run the full generation workflow or the evaluation workflow based on what the user provides. Always use this skill for any brand or product naming task — even if the user just casually mentions needing a name.
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Creates and manages reusable character profiles (Soul IDs) for consistent facial and stylistic identity across multiple image and video generations. Provides identity-vs-motion prompt separation, character sheet creation workflows, micro-expression direction, and Soul Cast AI actor configuration. Use when the user wants to maintain character consistency across multiple generations, asks about Soul ID, creating reusable characters, or generating consistent people across different scenes and shots.
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Detect potential code-level performance smells in Java - streams, collections, boxing, regex, object creation. Provides awareness, not absolutes - always measure before optimizing. For JPA/database performance, use jpa-patterns instead.
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Provides reverse engineering techniques. Use when the main job is to understand how a compiled, obfuscated, packed, or virtualized target works before exploiting or solving it, including binaries, APKs, WASM, firmware, custom VMs, bytecode, malware-like loaders, and anti-debug or anti-analysis logic. Do not use it when the vulnerability is already understood and the remaining task is exploitation; use pwn instead. Do not use it for pure web workflows, log or disk forensics, or standalone crypto problems unless reversing the implementation is the real blocker.
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Clone any website into a pixel-perfect single-file HTML prototype. Extracts design tokens, assets, CSS computed styles, interaction patterns, and content via Playwright. Outputs a self-contained HTML file with real data injection. Use when the user wants to clone, replicate, reverse-engineer, or create a pixel-perfect copy of any website or web app. Provide one or more target URLs as arguments.
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Use when the agent must open a URL, fill a form, click through a flow, screenshot a page, or extract data from a live page. Covers two providers (agent-browser local CLI, agentic-browser cloud) and the shared @e ref workflow.
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专业微信公众号文章助手，支持四个独立且可组合模式：article 写正文；image-prompts 从文章生成版本化、provider-neutral 的图片提示词 manifest 与稳定占位符，但不调用生图；layout 把文章和 manifest 确定性转换为微信安全的内联 HTML；full-pipeline 串联正文、提示词/占位符和排版。用户提到公众号、微信文章、推文、配图提示词、图片 manifest、公众号排版、内联 HTML 或完整图文流水线时触发。支持企业官号、个人技术博客、活动回顾和产品评测。不用于：带引用的研究报告（用 deep-research）、PPT/组图（用 deck-studio）、英文文章、仅润色一小段。永不自动发布，永不把提示词或占位符声称为已生成图片。
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Use this skill when the user wants an evidence-based research memo, literature review, market/policy/technical landscape, or a multi-source decision brief with citations, trade-offs, and a clear conclusion. Best for tasks that need synthesis across multiple external sources, iterative follow-up research, or a reusable written artifact. Do not use for quick factual lookups, single-source summaries, simple Q&A, summarizing one document the user already provided, plan-only requests where the user explicitly defers the actual research, or when the user wants a short answer with no need for cited evidence (a short but evidence-backed conclusion is still a brief memo, which this skill covers). Chinese trigger examples: "帮我调研", "深度研究", "综述报告", "技术选型分析", "竞品研究", "政策分析".
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