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HiTIPS: High-Throughput Image Processing Software for FISH data analysis

Project description

HiTIPS

Documentation Status License: MIT

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HiTIPS (High-Throughput Image Processing Software) is a comprehensive tool crafted for the analysis of high-throughput imaging datasets. Specifically designed for FISH (Fluorescence In Situ Hybridization) data, HiTIPS incorporates cutting-edge image processing and machine learning algorithms, delivering automated solutions for cell and nucleus segmentation, FISH signal identification, and quantification of signal attributes.

For comprehensive information about HiTIPS, including how to get started, installation procedures, examples for testing, and detailed usage instructions, please refer to our official documentation and resources:

🌟 Key Features

  • 🔍 Automated Segmentation: Efficiently segments cells and nuclei.
  • 📍 FISH Signal Identification: Accurate localization and identification of FISH signals.
  • 📊 Quantitative Analysis: Measures signal intensity and distribution.
  • 🎨 Customizable Interface: Provides flexibility for customization and integrating plugins.
  • 🚀 High-Throughput Support: Designed for processing large-scale imaging datasets.
  • ⚙️ Extendable Algorithms: Incorporates new methodologies for enhancing current analysis routines.
  • 🧩 Plugin Support: Supports the creation and integration of new analysis methods.

🔧 Hardware and Software Prerequisites

Hardware Requirements:

  • CPU: Multi-core processor (e.g., Intel i7 or AMD Ryzen 7).
  • RAM: Minimum 16GB (32GB recommended for large datasets).
  • Storage: SSD with 500GB or more of available space.
  • GPU: Optional but recommended, especially if using CUDA-enhanced functionalities.

Software Requirements:

  • Operating System: 64-bit Linux distribution (e.g., Ubuntu, CentOS, Fedora).
  • Python: Version 3.7 or newer.
  • Package Manager: Latest version of Miniconda or Anaconda.

📥 Installation

For detailed installation instructions, visit our installation guide.

Installing HiTIPS Using Conda and Pip

  1. Create a Conda Environment::

    conda create --name hitips_env python=3.8 conda activate hitips_env

  2. Install HiTIPS using Pip::

    pip install hitips

  3. Launch HiTIPS::

    hitips

Installing HiTIPS Using Requirements Files

  1. Create a Conda Environment from hitips_env.yml::

    conda env create -f hitips_env.yml conda activate hitips_env

  2. Install HiTIPS using Pip from requirements.txt::

    pip install -r requirements.txt

  3. Launch HiTIPS::

    hitips

Installing HiTIPS Using Docker

  1. Install Docker::

    Follow the official Docker installation instructions for your platform: https://docs.docker.com/get-docker/

  2. Pull the HiTIPS Docker Image::

    docker pull adibkeikhosravi991/hitips:latest

  3. Run HiTIPS in a Docker Container::

    Start a HiTIPS container with the following command:

    docker run -it --rm adibkeikhosravi991/hitips:latest

🚀 Usage

For detailed instructions on using HiTIPS, please visit our usage guide.

  • Introduce your high-throughput imaging dataset into the software.
  • Navigate through the available analysis options and specify your desired tasks.
  • Modify the analysis parameters fitting your requirements.
  • Initiate the analysis process.
  • Review and interpret the produced outcomes.
  • Save or export the results as required.

For example datasets for testing, please visit example datasets.

🤝 Contributing

We warmly welcome contributions to HiTIPS! If you're keen on contributing, please adhere to the following guidelines:

Creating a Pull Request

Before adding your new method, ensure your changes are ready to be shared with the HiTIPS repository:

  1. Fork the repository on GitHub.

  2. Clone your fork locally and create a new branch for your feature.

  3. Make your changes locally, committing them to your branch.

    .. code-block:: bash

    git add .
    git commit -m "Add new nuclei detection method"
    
  4. Push your changes to your fork on GitHub.

    .. code-block:: bash

    git push origin feature_branch_name
    
  5. Go to your fork on GitHub and click the ‘New pull request’ button.

  6. Ensure the base repository is set to CBIIT/HiTIPS and the base branch is the one you want your changes pulled into.

  7. Review your changes, then create the pull request.

Merging the Pull Request

Once your pull request has been reviewed and approved:

  1. Merge the pull request via the GitHub interface.

  2. Fetch the updated main branch to your local repository.

    .. code-block:: bash

    git checkout main
    git pull origin main
    
  3. Delete your local feature branch if desired.

📜 License

HiTIPS is distributed under the MIT License.

📞 Contact

For inquiries, feedback, or support, please don't hesitate to contact us at adib.keikhosravi@nih.gov.

🔗 Links

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