Skip to main content

Tool for automated MEG data quality control

Project description

MEGqc

MEGqc is an open-source, BIDS-aligned toolbox for automated MEG quality assessment (QA) and explicit quality control (QC) summarization.

It is designed for large cohorts and reproducible workflows, and provides both:

  • interactive HTML reports for human inspection, and
  • machine-readable derivatives for downstream automation.

What MEGqc Provides

  • QA-first quality profiling of raw MEG signal quality before exclusion decisions.
  • Multi-metric coverage including:
    • standard deviation (STD),
    • peak-to-peak amplitude (PtP),
    • power spectral density (PSD),
    • ECG/EOG-related contamination,
    • high-frequency muscle burden,
    • optional head-motion summaries.
  • Multi-scale reporting across recording, channel, epoch, subject, dataset group, and multi-sample comparisons.
  • QC support layer with configurable module-level criteria and a Global Quality Index (GQI).
  • Reproducible execution with profile-aware outputs and saved settings provenance.
  • Three usage modes: CLI, GUI, and programmatic dispatchers.

Requirements

  • Python 3.10
  • MEG data organized according to BIDS/MEG-BIDS.

Installation

Option 1: Installer-based (recommended for most users)

Download the installer bundle from the MEGqc releases and follow the platform-specific instructions in the installation guide.

Option 2: CLI-based (Conda + pip)

conda create -n megqc-py310 python=3.10 pip -y
conda activate megqc-py310
pip install meg-qc

For detailed installation instructions, see the CLI installation guide.

Quick Start (CLI)

  1. Export default config:
get-megqc-config --target_directory ./config
  1. Run QA/QC calculation:
run-megqc --inputdata /path/to/bids_dataset --config ./config/settings.ini
  1. Build plotting reports:
run-megqc-plotting --inputdata /path/to/bids_dataset
  1. Recompute GQI summaries (optional):
globalqualityindex --inputdata /path/to/bids_dataset
  1. Run full pipeline in one command (calculation + plotting):
run-megqc --inputdata /path/to/bids_dataset --config ./config/settings.ini --run-all

Launch GUI

megqc

The GUI uses the same backend logic as CLI dispatchers and writes the same derivative/report outputs.

Typical Outputs

MEGqc writes outputs under BIDS derivatives (default):

  • derivatives/Meg_QC/calculation/ — metric tables + JSON summaries
  • derivatives/Meg_QC/reports/ — interactive HTML reports
  • derivatives/Meg_QC/summary_reports/ — QC summaries including GQI artifacts

Documentation

Source Code

https://github.com/ANCPLabOldenburg/MEGqc

License

MIT License.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

meg_qc-0.7.6.tar.gz (499.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

meg_qc-0.7.6-py3-none-any.whl (508.7 kB view details)

Uploaded Python 3

File details

Details for the file meg_qc-0.7.6.tar.gz.

File metadata

  • Download URL: meg_qc-0.7.6.tar.gz
  • Upload date:
  • Size: 499.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.11

File hashes

Hashes for meg_qc-0.7.6.tar.gz
Algorithm Hash digest
SHA256 6516616af58195195a1d8a3f03e81fc513b1cae5396c41169128b986c86dda30
MD5 42b3d4acfb7c7c88bb9dac03b0d478e1
BLAKE2b-256 1ad236f183e0e42a4a987dba5aed13c742d9044f83970ca90e14a5179a32898a

See more details on using hashes here.

File details

Details for the file meg_qc-0.7.6-py3-none-any.whl.

File metadata

  • Download URL: meg_qc-0.7.6-py3-none-any.whl
  • Upload date:
  • Size: 508.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.11

File hashes

Hashes for meg_qc-0.7.6-py3-none-any.whl
Algorithm Hash digest
SHA256 1f28a22a7e8ca86e41544dead32670780c631f6b2ad98877321564a446d62c58
MD5 3119e19bf06f5587ad158bc39fceb70c
BLAKE2b-256 2eb908d0d4479ba4544b18fbbea7ef733ad8a76280fd3f8bb6baa528615635b4

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page