Metadata-Version: 2.1
Name: hitips
Version: 0.1.24
Summary: HiTIPS: High-Throughput Image Processing Software for FISH data analysis
Home-page: https://github.com/CBIIT/HiTIPS
Author: keikhosravi
Author-email: adib.keikhosravi@nih.gov
License: MIT
Keywords: high-throughput imaging FISH analysis cell segmentation signal quantification
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Image Processing
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: numpy
Requires-Dist: scikit-image (==0.18.3)
Requires-Dist: scipy
Requires-Dist: Pillow
Requires-Dist: pandas (==1.4.2)
Requires-Dist: matplotlib
Requires-Dist: btrack (==0.4.3)
Requires-Dist: imageio
Requires-Dist: tifffile
Requires-Dist: aicsimageio
Requires-Dist: deepcell
Requires-Dist: scikit-learn
Requires-Dist: hmmlearn
Requires-Dist: PyQt5
Requires-Dist: cellpose
Requires-Dist: tensorflow
Requires-Dist: joblib
Requires-Dist: dask
Requires-Dist: nd2reader
Requires-Dist: imaris-ims-file-reader
Requires-Dist: qimage2ndarray
Requires-Dist: spatial-efd
Requires-Dist: pydantic (==1.10.9)
Requires-Dist: aicspylibczi
Requires-Dist: opencv-python-headless

# HiTIPS

**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.

## 🌟 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 routines.
  
## 🔧 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](https://docs.conda.io/en/latest/miniconda.html) or [Anaconda](https://www.anaconda.com/products/distribution).

## 📥 Installation

### Using Conda and Pip

1. **Create a Conda Environment**:
   ```bash
   conda create --name hitips_env python=3.8
   conda activate hitips_env
   
2. **Install HiTIPS**:
   ```bash
   pip install hitips
   
4. **Launch HiTIPS:**
   ```bash
   hitips
   
## 🚀 Usage

- Launch HiTIPS using the command `python -m hitips`.
- 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.

## 🤝 Contributing

We warmly welcome contributions to HiTIPS! If you're keen on contributing, please adhere to the following guidelines:
- Fork and Branch: `git checkout -b feature/your-feature-name`
- Ensure that your changes align with the project's coding standards.
- Validate your modifications with appropriate tests.
- Commit your changes, ensuring your commit messages are descriptive.
- Push your updates to your fork.
- Submit a pull request on the primary HiTIPS repository detailing your changes.

## 📜 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.


