siibra

Software interfaces for interacting with brain atlases - Python client

https://github.com/fzj-inm1-bda/siibra-python

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Software interfaces for interacting with brain atlases - Python client

README.rst

|License| |PyPI version| |doi| |Python versions| |Documentation Status|

==============================================================
siibra - Software interface for interacting with brain atlases
==============================================================

Copyright 2018-2025, Forschungszentrum Jülich GmbH

*Authors: Big Data Analytics Group, Institute of Neuroscience and
Medicine (INM-1), Forschungszentrum Jülich GmbH*

.. intro-start

``siibra-python`` is a Python client to a brain atlas framework that integrates brain parcellations and reference spaces at different spatial scales, and connects them with a broad range of multimodal regional data features. 
It aims to facilitate programmatic and reproducible incorporation of brain parcellations and brain region features from different sources into neuroscience workflows.

``siibra`` provides structured access to parcellation schemes in different brain reference spaces, including volumetric reference templates at  macroscopic and microscopic resolutions as well as surface representations. 
It supports both discretely labelled and statistical (probabilistic) parcellation maps, which can be used to assign brain regions to spatial locations and image signals, to retrieve region-specific neuroscience datasets from multiple online repositories, and to sample information from high-resolution image data. 
The datasets anchored to brain regions address features of molecular, cellular and architecture as well as connectivity, and are complemented with live queries to external repositories as well as dynamic extraction from "big" image volumes such as the 20 micrometer BigBrain model.

``siibra`` hides much of the complexity that would be required to collect and interact with the individual parcellations, templates and data repositories.
By encapsulating many aspects of interacting with different maps and reference templates spaces, it also minimizes common errors like misinterpretation of coordinates from different reference spaces, confusing label indices of brain regions, or using inconsistent versions of parcellation maps. 
It aims to provide a safe way of using maps defined across multiple spatial scales for reproducible analysis.

.. intro-end

.. about-start

``siibra`` was developed in the frame of the `Human Brain Project `__ for accessing the `EBRAINS
human brain atlas `__. 
It stores most of its contents as sustainable and open datasets in the `EBRAINS Knowledge Graph `__, and is designed to support the `OpenMINDS metadata standards `__. 
Its functionalities include common actions known from the interactive viewer ``siibra-explorer`` `hosted at EBRAINS `__. 
In fact, the viewer is a good resource for exploring ``siibra``\ ’s core functionalities interactively: Selecting different parcellations, browsing and searching brain region hierarchies, downloading maps, identifying brain regions, and accessing multimodal features and connectivity information associated with brain regions. 
Feature queries in ``siibra`` are parameterized by data modality and anatomical location, while the latter could be a brain region, brain parcellation, or location in reference space. 
Beyond the explorative focus of ``siibra-explorer``, the Python library supports a range of data analysis functions suitable for typical neuroscience workflows.

.. about-end

.. getting-started-start

Installation
============

``siibra`` is available on pypi. 
To install the latest released version, simply run ``pip install siibra``. 
The installation typically takes about 2 minutes on a standard computer where Python is already installed.
In order to work with the latest version from github, use ``pip install git+https://github.com/FZJ-INM1-BDA/siibra-python.git@main``.

``siibra-python`` should be installable on recent versions of Windows, Linux and Mac OS in a recent Python 3 environment.
We run continuous integration tests for versions 3.7 - 3.12 on recent Ubuntu images. 

The library requires a couple of open source packages, namely:
```
anytree >= 2.12.1
nibabel >= 5.3.2
appdirs >= 1.4.4
scikit-image >= 0.25.0
requests >= 2.32.3
neuroglancer-scripts >= 1.2.0
nilearn >= 0.11.0
filelock >= 3.16.1
ebrains-drive >= 0.6.0
```

You can also install a docker image with all dependencies included:
.. code-block:: sh

  docker run -dit \
        -p 10000:8888 \
        --rm \
        --name siibra \
        docker-registry.ebrains.eu/siibra/siibra-python:latest



Documentation & Help
====================

``siibra-python``\ ’s documentation is hosted on https://siibra-python.readthedocs.io.
The documentation includes a catalogue of documented code examples that walk you through the different concepts and functionalities.
These examples use real data and include both the code and the produced expected outputs.
They can be accessed at https://siibra-python.readthedocs.io/en/latest/examples.html, and are
automatically tested and updated whenever a new version of ``siibra-python`` is published.
As a new user, it is recommended to go through these examples - they are easy and will quickly provide you with the right code snippets that get you started.
The documentation on readthedocs further includes introductory explanations and an API reference.

If you run into issues, please open a ticket on `EBRAINS support `__ or file bugs and
feature requests on `github `__.

.. getting-started-end

.. contribute-start

How to contribute
=================

If you want to contribute to ``siibra``, feel free to fork it and open a pull request with your changes.
You are also welcome to contribute to discussions in the issue tracker and of course to report issues you are facing.
If you find the software useful, please reference this repository URL in publications and derived work.
You can also star the project to show us that you are using it.

.. contribute-end

.. acknowledgments-start

Acknowledgements
================

This software code is funded from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3).

.. acknowledgments-end

.. howtocite-start

How to cite
===========
Please cite the version used according to the citation file
or all versions by
`Timo Dickscheid, Xiayun Gui, Ahmet Nihat Simsek, Vadim Marcenko,
Louisa Köhnen, Sebastian Bludau, & Katrin Amunts. (2023). siibra-python -
Software interface for interacting with brain atlases. Zenodo.
https://doi.org/10.5281/zenodo.7885728`.

.. howtocite-ends


.. |License| image:: https://img.shields.io/badge/License-Apache%202.0-blue.svg
   :target: https://opensource.org/licenses/Apache-2.0
.. |PyPI version| image:: https://badge.fury.io/py/siibra.svg
   :target: https://pypi.org/project/siibra/
.. |Python versions| image:: https://img.shields.io/pypi/pyversions/siibra.svg
   :target: https://pypi.python.org/pypi/siibra
.. |Documentation Status| image:: https://readthedocs.org/projects/siibra-python/badge/?version=latest
   :target: https://siibra-python.readthedocs.io/en/latest/?badge=latest
.. |doi| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.7885728.svg
   :target: https://doi.org/10.5281/zenodo.7885728


Versioning
==========
Given a version number MAJOR.MINOR.PATCH, increments imply:
   - MAJOR: incompatible API changes
   - MINOR: a functionality in a backward compatible manner is added
   - PATCH: backward compatible bug fixes and new configuration added such as new maps or features

Pre-release
-----------
For x.y.z, a full release,
- `x.y.z-alpha.t` is the development prerelease. By changing `t`, different siibra-configurations are targeted.

Owner

Citation (CITATION.cff)

cff-version: 1.2.0

title: "siibra-python"

abstract: |
  siibra is a Python client to a brain atlas framework that integrates brain
  parcellations and reference spaces at different spatial scales, and connects
  them with a broad range of multimodal regional data features. It aims to
  facilitate programmatic and reproducible incorporation of brain parcellations
  and brain region features from different sources into neuroscience workflows.

message: "If you use this software, please cite it as below."

license: Apache-2.0

repository-code: https://github.com/FZJ-INM1-BDA/siibra-python

version: v1.0.1-alpha.8

date-released: 2025-06-03

doi: 10.5281/zenodo.7885728

contact:
  - given-names: Timo
    family-names: Dickscheid
    email: t.dickscheid@fz-juelich.de
    affiliation: INM-1, Forschungszentrum Juelich, Germany

authors:
  - family-names: Dickscheid
    given-names: Timo
    orcid: https://orcid.org/0000-0002-9051-3701
  - family-names: Gui
    given-names: Xiaoyun
  - family-names: Simsek
    given-names: Ahmet Nihat 
  - family-names: Koehnen
    given-names: Louisa
  - family-names: Marcenko
    given-names: Vadim
  - family-names: Schiffer
    given-names: Christian
  - family-names: Bludau
    given-names: Sebastian
  - family-names: Amunts
    given-names: Katrin

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