llama-cancer 0.1.0

Tools and models for cancer research using LlamaAI components.

LlamaCancer

LlamaCancer is a specialized toolkit within the LlamaSearch AI ecosystem designed for cancer research data analysis. It provides tools for statistical analysis, data visualization, and potentially interfacing with relevant biomedical datasets or APIs.

Key Features

• Cancer Data Analysis: Core functions for analyzing cancer-related datasets (analysis.py).
• Statistical Tools: Includes specific statistical methods relevant to biomedical research (stats.py).
• Data Visualization: Components for creating visualizations of analysis results (vis.py).
• Data I/O: Utilities for reading and writing common biomedical data formats (io.py).
• API Endpoints: Potential for exposing analysis functions via API (endpoints.py).
• Main Application: A central entry point (main.py) likely orchestrates analysis workflows.
• Configurable: Supports basic configuration (config.py).

Installation

pip install llamacancer
# Or install directly from GitHub for the latest version:
# pip install git+https://github.com/llamasearchai/llama-cancer.git

Usage

(Usage examples demonstrating data loading, analysis, and visualization will be added here.)

# Placeholder for Python client usage
# from llamacancer import CancerAnalyzer, DataReader

# reader = DataReader(config_path="config.yaml")
# data = reader.load_data("path/to/cancer_data.csv")

# analyzer = CancerAnalyzer()
# analysis_results = analyzer.run_survival_analysis(data)
# print(analysis_results)

# analyzer.visualize_kaplan_meier(analysis_results)

Architecture Overview

graph TD
    A[Input Data (e.g., CSV, VCF)] --> B{Data I/O (io.py)};
    B --> C{Main Application / Orchestrator (main.py)};
    C --> D[Analysis Module (analysis.py)];
    C --> E[Statistics Module (stats.py)];
    C --> F[Visualization Module (vis.py)];
    D --> G[Analysis Results];
    E --> G;
    F -- Uses --> G;
    F --> H[Plots / Visualizations];

    I[API Endpoints (endpoints.py)] -- Calls --> C;
    J[Configuration (config.py)] -- Configures --> C;
    K[Utilities (utils.py)] -- Used by --> D;
    K -- Used by --> E;
    K -- Used by --> F;

    style C fill:#f9f,stroke:#333,stroke-width:2px

1. Input: Loads biomedical data using the I/O module.
2. Orchestrator: The main application coordinates the analysis workflow.
3. Analysis/Stats/Vis: Dedicated modules perform core analysis, statistical calculations, and generate visualizations.
4. Endpoints (Optional): An API layer can expose functionality.
5. Config/Utils: Configuration guides the process; utilities provide shared functions.

Configuration

(Details on configuring data paths, analysis parameters, visualization options, etc., will be added here.)

Development

Setup

# Clone the repository
git clone https://github.com/llamasearchai/llama-cancer.git
cd llama-cancer

# Install in editable mode with development dependencies
pip install -e ".[dev]"

Testing

pytest tests/

Contributing

Contributions are welcome! Please refer to CONTRIBUTING.md and submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.