Metadata-Version: 2.1
Name: panpipelines
Version: 0.9.2
Summary: MRI Processing Pipelines for PAN Healthy Minds for Life Study
Project-URL: Homepage, https://github.com/MRIresearch/PANpipelines
Project-URL: Bug Tracker, https://github.com/MRIresearch/PANpipelines/issues
Author-email: Chidi Ugonna <chidiugonna@arizona.edu>
License: MIT License
        
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License-File: LICENSE
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.9
Requires-Dist: nibabel==5.2.0
Requires-Dist: nilearn==0.10.2
Requires-Dist: nipype==1.8.6
Requires-Dist: nitransforms==23.0.1
Requires-Dist: numpy==1.26.3
Requires-Dist: pandas==2.1.4
Requires-Dist: pybids==0.16.4
Requires-Dist: pydicom==2.4.4
Requires-Dist: scipy==1.11.4
Requires-Dist: templateflow==23.1.0
Requires-Dist: xnat==0.5.3
Description-Content-Type: text/markdown

# PANpipelines
---
This repository contains all the necessary scripts for reproducing the steps taken to preprocess and analyze MRI data collected during the Precision Aging Network (PAN) project.

## The panpipelines package
The PAN Pipelines use a set of python modules packaged under the main `panpipelines` package to run all the preprocessing and analysis workflows which are based on NiPype. 

## Installation
It is recommended that a python environment manager like `conda` or `virtualenv` is used to install the **panpipelines** package. Assuming you have created a conda environment called `panpython` then the package can be installed as follows:

```
conda activate panpython
pip install panpipelines
```
## Deployment
For an example of using the package to process MRI data please refer to the `./deployment` folder. All the necessary parameters for running the pipelines are described in a **config** file in the `./config` subdirectory which is passed as a parameter to the main module `pan_processing.py`. In the example provided this file is name `panpipeconfig_slurm.config`.

