NiChart^Engine

A software library designed to calculate NiChart pre-trained models and reference distributions from the NiChart reference dataset ¹. NiChart^Engine includes tools for image processing, data harmonization, machine learning, and centile calculation. NiChart^Engine utilizes Snakemake workflows to define multi-step image processing and data analytics pipelines.

Installation

Install NiChart^Engine within a conda environment using the following commands. NiChart^Engine uses snakemake to automate things, which is (most easily) installed with mamba.

conda install -n base -c conda-forge mamba # If needed
mamba init # If first time installing, then potentially source ~/.bashrc
mamba create -c conda-forge -c bioconda -n NiChart_Engine python=3.8 
mamba activate NiChart_Engine
pip install spare-scores NiChartHarmonize
mamba install -c conda-forge -c bioconda snakemake

Usage

Users can apply NiChart^Engine workflows to their data with just a few simple steps:

1. Copy Data: Transfer your data to the designated location within the project directory.
2. Edit Configuration File: Make any necessary adjustments to the configuration file as specified by the package documentation.
3. Run Workflow: Execute the Snakemake workflow to initiate the analysis.

Contents:

• NiChart_Data:

Workflows for consolidation of initial clinical, demographic and scanner data.

• NiChart_ImageProcessing:

Workflows for application of image processing pipelines (sMRI, DTI and/or fMRI).

• NiChart_MLAnalytics:

Workflows for application of harmonization, machine learning and centile calculation steps to calculate reference models and data distributions.

Contributing

We welcome contributions from the community! If you have bug fixes, improvements, or new features, please consider creating a pull request. Before submitting a pull request, please:

• Ensure your code adheres to the existing code style and formatting.
• Include clear documentation for your changes.
• Write unit tests for any new functionality.

License

This project is licensed under the [License Name] license. Please refer to the LICENSE file for the full license text. (Replace [License Name] with the actual license used by your project, such as MIT, Apache, or BSD)

Contact

For any inquiries, please contact guray.erus@pennmedicine.upenn.edu. (Last Updated: 5/24/2024)