[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

# Welcome!

Hello everyone, and welcome to the MEGqc documentation.
[**MEGqc**](https://github.com/ANCPLabOldenburg/MEGqc) is a Python-based pipeline for quality assessment and quality control of MEG data. It was developed by the [**Applied Neurocognitive Psychology Lab (ANCP Lab)**](https://uol.de/en/applied-neurocognitive-psychology). To ensure standardization of the pipeline, MEGqc software is tailored to the [**BIDS standards**](extra/bids.md).

This documentation includes an [installation guide](./book/installation.md) and a [tutorial](./book/tutorial.md) covering installer-based, CLI-based, and programmatic workflows. It also includes an overview of [HTML reports](./book/report.md) — from subject-level QA reports to dataset-level and cross-dataset analyses — and the [Global Quality Index](./extra/gqi.md).


```{admonition} Windows update!
:class: tip

Currently, MEGqc runs smoothly both on Windows (x86), Linux (x86) and macOS (ARM)! 🚀

```

## User-friendly
To run the quality control calculations and create the reports you just need to:
- Install the GUI (CLI version also available)
- Provide data for evaluation (we offer a [dummy dataset](./extra/openneuro.md))
- Set analysis parameters (if desired, default parameters are available)
- Run the analysis

```{warning}

Currently, MEGqc runs smoothly with `.fif` files from Neuromag / Elekta / MEGIN systems, as well as BabyMEG systems.  
It also supports `.ctf` data formats, typically stored in folders with the `.ds` extension.

```

## Requirements for this tutorial
This documentation will help you to install and run MEGqc without a deep technical knowledge. While no advanced programming knowledge is required, it's helpful to be familiar with the following concepts:
- Basic understanding of **MEG data** and common artifacts.
- Basic knowledge of the [BIDS structure](extra/bids.md)
- Basic understanding of [BASH commands](https://peerherholz.github.io/Python_for_Psychologists_Winter2021/introduction/intro_to_shell.html) (for CLI users).

## I've got a question!
If you have any questions or encounter difficulties while working with MEGqc, please don't hesitate to get in touch with us. You can send an e-mail to karel.mauricio.lopez.vilaret@uni-oldenburg.de or check a `New Issue` in the [MEGqc github](https://github.com/ANCPLabOldenburg/MEGqc/issues).

## Acknowledgements
This tutorial was made possible through the dedicated work of the [Jupyter community](https://jupyter.org/community), specifically, the [Executable/Jupyter Book](https://executablebooks.org/en/latest/).