brainglobe-atlasapi

The BrainGlobe Atlas API (brainglobe-atlasapi) provides a common interface for programmers to download and process brain atlas data from multiple sources.

Atlases available

A number of atlases are in development, but those available currently are: | Atlas Name | Resolution | Ages | Reference Images | Name in API & More Info | | --- | --- | --- | --- | --- | | Allen Mouse Brain Atlas | 10, 25, 50, and 100 micron | P56 | STPT | | | Allen Human Brain Atlas | 500 micron | Adult | MRI | | | Max Planck Zebrafish Brain Atlas | 1 micron | 6 dpf | FISH | | | Enhanced and Unified Mouse Brain Atlas | 10, 25, 50, and 100 micron | P56 | STPT | | | Smoothed version of the Kim et al. mouse reference atlas | 10, 25, 50 and 100 micron | P56 | STPT | | | Gubra's LSFM mouse brain atlas | 20 micron | 8 to 10 weeks post natal | LSFM | | | 3D version of the Allen mouse spinal cord atlas | 20 x 10 x 10 micron | Adult | Nissl | | | AZBA: A 3D Adult Zebrafish Brain Atlas | 4 micron | 15-16 weeks post natal | LSFM | | | Waxholm Space atlas of the Sprague Dawley rat brain | 39 micron | P80 | MRI | | | 3D Edge-Aware Refined Atlases Derived from the Allen Developing Mouse Brain Atlases | 16, 16.75, and 25 micron | E13, E15, E18, P4, P14, P28 & P56 | Nissl | | | Princeton Mouse Brain Atlas | 20 micron | >P56 (older animals included) | LSFM | | | Kim Lab Developmental CCF v1.0 | 20, 31.5, 34, 37.5, 40, and 50 micron | E11.5, E13.5, E15.5, E18.5, P04, P14, P56 | LSFM and MRI (adc, dwi, fa, T2) | | | Kim Lab Developmental CCF v001 | 10 micron | P56 | STPT, LSFM (iDISCO) and MRI (a0, adc, dwo, fa, MTR, T2) | | | Blind Mexican Cavefish Brain Atlas | 2 micron | 6 dpf | IHC | | | BlueBrain Barrel Cortex Atlas | 10 and 25 micron | P56 | STPT | | | UNAM Axolotl Brain Atlas | 40 micron | ~ 3 months post hatching | MRI | | | Prairie Vole Brain Atlas | 25 micron | Unknown | LSFM | | | Gubra's stereotaxic MRI mouse brain atlas | 25 micron | 10 week old | MRI | | | Gubra's LSFM mouse brain atlas v2 | 25 micron | 10 week old | LSFM | | | MRI mouse lemur brain atlas | 91 micron | 15–58 months | MRI | | | Australian Mouse Brain Atlas | 15 micron | 12 week old | MRI | | | Cat brain atlas | 500 micron | Adult | MRI | | | Eurasian blackcap atlas | 25 micron| Adult | STPT | | | BlueBrain CCFv3 Augmented | 10 and 25 micron | P56 | Nissl | | | Kocher Bumblebee Brain Atlas | 2.542 x 1.2407 x 1.2407 micron | Adult Worker | Confocal | | | Drosophila wing disc instar3 atlas| 2 micron | 3rd Instar Larvae | Confocal | |

Acronyms: - dpf: Days Post Fertilisation - E: Embryonic day - FISH: Fluorescent In Situ Hybridisation - IHC: Immunohistochemistry - LSFM: Light Sheet Fluorescent Microscopy - MRI: Magnetic Resonance Imaging - P: Post natal day - STPT: Serial Two Photon Tomography

Installation

brainglobe-atlasapi can be installed from PyPI with:

bash pip install brainglobe-atlasapi

Usage

Full information can be found in the documentation

Python API

List of atlases

To see a list of atlases use brainglobe_atlasapi.show_atlases

```python from brainglobeatlasapi import showatlases show_atlases()

Brainglobe Atlases

╭──────────────────────────────────┬────────────┬───────────────┬──────────────╮

│ Name │ Downloaded │ Local version │ Latest │

│ │ │ │ version │

├──────────────────────────────────┼────────────┼───────────────┼──────────────┤

│ allenhuman500um │ ✔ │ 0.1 │ 0.1 │

│ mpinzfish1um │ ✔ │ 0.3 │ 0.3 │

│ allenmouse50um │ ✔ │ 0.3 │ 0.3 │

│ kimunified25um │ ✔ │ 0.1 │ 0.1 │

│ allenmouse25um │ ✔ │ 0.3 │ 0.3 │

│ allenmouse10um │ ✔ │ 0.3 │ 0.3 │

│ examplemouse100um │ --- │ --- │ 0.3 │

╰──────────────────────────────────┴────────────┴───────────────┴──────────────╯

```

Using the atlases

All the features of each atlas can be accessed via the BrainGlobeAtlas class.

e.g. for the 25um Allen Mouse Brain Atlas:

python from brainglobe_atlasapi.bg_atlas import BrainGlobeAtlas atlas = BrainGlobeAtlas("allen_mouse_25um")

The various files associated with the atlas can then be accessed as attributes of the class:

```python

reference image

referenceimage = atlas.reference print(referenceimage.shape)

(528, 320, 456)

annotation image

annotationimage = atlas.annotation print(annotationimage.shape)

(528, 320, 456)

a hemispheres image (value 1 in left hemisphere, 2 in right) can be generated

hemispheresimage = atlas.hemispheres print(hemispheresimage.shape)

(528, 320, 456)

```

Brain regions

There are multiple ways to work with individual brain regions. To see a dataframe of each brain region, with it's unique ID, acronym and full name, use atlas.lookup_df:

```python atlas.lookup_df.head(8)

acronym id name

0 root 997 root

1 grey 8 Basic cell groups and regions

2 CH 567 Cerebrum

3 CTX 688 Cerebral cortex

4 CTXpl 695 Cortical plate

5 Isocortex 315 Isocortex

6 FRP 184 Frontal pole, cerebral cortex

7 FRP1 68 Frontal pole, layer 1

```

Each brain region can also be access by the acronym, e.g. for primary visual cortex (VISp):

```python from pprint import pprint VISp = atlas.structures["VISp"] pprint(VISp)

{'acronym': 'VISp',

'id': 385,

'mesh': None,

'meshfilename': PosixPath('/home/user/.brainglobe/allenmouse25umv0.3/meshes/385.obj'),

'name': 'Primary visual area',

'rgb_triplet': [8, 133, 140],

'structureidpath': [997, 8, 567, 688, 695, 315, 669, 385]}

```

Note on coordinates in brainglobe-atlasapi

Working with both image coordinates and cartesian coordinates in the same space can be confusing! In brainglobe-atlasapi, the origin is always assumed to be in the upper left corner of the image (sectioning along the first dimension), the "ij" convention. This means that when plotting meshes and points using cartesian systems, you might encounter confusing behaviors coming from the fact that in cartesian plots one axis is inverted with respect to ij coordinates (vertical axis increases going up, image row indexes increase going down). To make things as consistent as possible, in brainglobe-atlasapi the 0 of the meshes coordinates is assumed to coincide with the 0 index of the images stack, and meshes coordinates increase following the direction stack indexes increase. To deal with transformations between your data space and brainglobe-atlasapi, you might find the brainglobe-space package helpful.

Seeking help or contributing

We are always happy to help users of our tools, and welcome any contributions. If you would like to get in contact with us for any reason, please see the contact page of our website. To contribute to brainglobe-atlasapi, please see the BrainGlobe developer's guide.

Citation

If you find the BrainGlobe Atlas API useful, please cite the paper in your work:

Claudi, F., Petrucco, L., Tyson, A. L., Branco, T., Margrie, T. W. and Portugues, R. (2020). BrainGlobe Atlas API: a common interface for neuroanatomical atlases. Journal of Open Source Software, 5(54), 2668, https://doi.org/10.21105/joss.02668

Don't forget to cite the developers of the atlas that you used!

---

Atlas Generation and Adding a New Atlas

For full instructions to add a new BrainGlobe atlas, please see here.

The brainglobe_atlasapi.atlas_generation submodule contains code for the generation of cleaned-up data, for the main brainglobe_atlasapi module. This code was previously the bg-atlasgen module.

To contribute

1. Fork this repo
2. Clone your repo
3. Run git clone https://github.com/brainglobe/brainglobe-atlasapi
4. Install an editable version of the package; by running pip install -e . within the cloned directory
5. Create a script to package your atlas, and place into brainglobe_atlasapi/atlas_generation/atlas_scripts. Please see other scripts for examples.

Your script should contain everything required to run. The raw data should be hosted on a publicly accessible repository so that anyone can run the script to recreate the atlas.

If you need to add any dependencies, please add them as an extra in the pyproject.toml file, e.g.:

python [project.optional-dependencies] allenmouse = ["allensdk"] newatlas = ["dependency_1", "dependency_2"]