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Tyo edited this page Dec 8, 2025 · 6 revisions

🦞 Lobster AI Documentation

License: AGPL-3.0-or-later Documentation: CC BY 4.0 Python 3.11+

Welcome to the comprehensive documentation for Lobster AI - the AI-powered multi-omics bioinformatics analysis platform. This documentation provides everything you need to use, develop, and extend Lobster AI.

📚 Documentation Structure

🚀 Getting Started

Start here if you're new to Lobster AI

👤 User Guide

Learn how to use Lobster AI for your research

💻 Developer Guide

Extend and contribute to Lobster AI

📖 API Reference

Complete API documentation

🏗️ Architecture & Internals

Deep dive into system design

🔬 Advanced Features & Internals

Deep dives into specialized capabilities and system internals (v0.2+)

Agent Enhancements:

Content & Publication Intelligence:

Infrastructure & Performance:

Specialized Features:

Migration & Maintenance:

🎯 Tutorials & Examples

Learn by doing with practical tutorials

🔧 Support & Reference

Help and additional resources

🎯 Quick Navigation by Task

"I want to..."

Get Started Quickly

Analyze My Data

Understand the System

Extend Lobster AI

Solve Problems

Master Advanced Features

🌟 Key Features

🤖 AI-Powered Analysis

  • Natural language interface for complex bioinformatics
  • 8+ specialized AI agents for different analysis domains
  • Intelligent workflow coordination and parameter optimization

🧬 Scientific Capabilities

  • Single-Cell RNA-seq: QC, clustering, annotation, trajectory analysis
  • Bulk RNA-seq: pyDESeq2 differential expression with complex designs
  • Multi-Omics: Integrated cross-platform analysis

☁️ Deployment Flexibility

  • Local Mode: Full privacy with data on your machine
  • Cloud Mode: Scalable computing with managed infrastructure
  • Hybrid: Automatic switching between modes

📊 Professional Features

  • Publication-ready visualizations
  • W3C-PROV compliant provenance tracking
  • Comprehensive quality control metrics
  • Batch effect detection and correction

📈 Version Highlights

Current Release: v0.2 is the first public release of Lobster AI. See the comprehensive documentation for features and upgrade information.

Current Features (v0.2) ✨

Content Intelligence & Publications:

  • 🧬 Protein Structure Visualization - PyMOL integration for 3D protein visualization and analysis (Details)
  • 🔌 ContentAccessService - Unified publication/dataset access with 5 specialized providers (Details)
  • 📄 Docling PDF Parsing - Structure-aware Methods section extraction with >90% hit rate (Details)
  • 📊 Table Extraction - Parameter tables from scientific publications
  • 🧮 Formula Preservation - Mathematical formulas in LaTeX format

Data Management:

  • 📥 Download Queue System - Robust multi-step data acquisition with JSONL persistence (Details)
  • ⚡ Enhanced Two-Tier Caching - 30-50x speedup on repeat content access (0.2-0.5s cached)
  • 🔄 Workspace Restoration - Seamless session continuity (Details)
  • 📂 Pattern-based Dataset Loading - Smart memory management
  • 💾 Session Persistence - Automatic state tracking
  • 💾 WorkspaceContentService - Type-safe caching for research content (Details)

Analysis & Workflows:

  • 🧪 Formula-Based Differential Expression - Complex experimental designs with R-style formulas (Details)
  • 🤖 Enhanced Data Expert Agent - New restoration tools and workflows

Infrastructure:

  • 🏗️ Provider Infrastructure - Modular, extensible architecture for content retrieval
  • 🏗️ Agent Registry Auto-Discovery - Dynamic agent configuration (Details)
  • ⌨️ Enhanced CLI - Arrow navigation and command history
  • 🎨 Rich Interface - Professional orange branding
  • ⚡ Performance - Optimized startup and processing

🗂️ Feature Availability Matrix

Quick reference for feature availability across deployment modes.

Core Features by Deployment Mode

Feature Local Cloud
Content Intelligence
Docling structure-aware parsing ✅ ✅
Two-tier publication access ✅ ✅
ContentAccessService ✅ ✅
Provider infrastructure (5 providers) ✅ ✅
Analysis Capabilities
Simple DE (two-group) ✅ ✅
Formula-based DE ✅ ✅
Agent-guided formulas ✅ ✅
Protein visualization (batch) ✅ ✅
Protein visualization (interactive) ✅ ⚠️
Data Management
Basic workspace ✅ ✅
WorkspaceContentService ✅ ✅
Download queue (JSONL) ✅ ✅
Two-tier caching ✅ ✅
Infrastructure
Auto agent discovery ✅ ✅
FTP retry logic ✅ ✅

Legend:

  • ✅ Full support
  • ⚠️ Partial support (see notes below)

Note: Interactive PyMOL visualization requires local GUI support. Cloud mode supports batch image generation only.

For detailed feature documentation, see the Migration Guide.

🔗 Quick Links

📝 Documentation Standards

This documentation follows these principles:

  • Progressive Disclosure: Start simple, dive deeper as needed
  • Task-Oriented: Organized by what you want to accomplish
  • Example-Rich: Real datasets and practical code examples
  • Cross-Referenced: Links between related topics
  • Maintained: Regular updates with each release

🤝 Contributing to Documentation

Found an issue or want to improve the documentation?

  1. Check our developer overview
  2. Submit a pull request to the docs/wiki directory
  3. Follow our code style guidelines

Documentation for Lobster AI v0.2+ | Last updated: 2025

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