Gene expressions

siibra can query gene expression data from the Allen brain atlas. The gene expressions are linked to atlas regions by coordinates of their probes in MNI space. When querying feature by a region, siibra automatically builds a region mask to filter the probes.

Hint

This feature is used by the JuGEx toolbox, which provides an implementation for differential gene expression analysis between two different brain regions as proposed by Bludau et al.

import siibra
from nilearn import plotting

We select a brain region and query for expression levels of GABARAPL2.

region = siibra.get_region("julich 2.9", "V1")
features = siibra.features.get(
    region, siibra.features.molecular.GeneExpressions,
    gene=siibra.vocabularies.GENE_NAMES.GABARAPL2
)
print(features[0])
# Take a peek at how the data looks
features[0].data.head()

Traceback (most recent call last):
  File "/home/docs/checkouts/readthedocs.org/user_builds/siibra-python/checkouts/doc_test_ng_resolve/examples/03_data_features/004_gene_expressions.py", line 40, in <module>
    features = siibra.features.get(
               ^^^^^^^^^^^^^^^^^^^^
  File "/home/docs/checkouts/readthedocs.org/user_builds/siibra-python/checkouts/doc_test_ng_resolve/siibra/features/feature.py", line 593, in _match
    live_instances = feature_type._livequery(concept, **kwargs)
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/docs/checkouts/readthedocs.org/user_builds/siibra-python/checkouts/doc_test_ng_resolve/siibra/features/feature.py", line 494, in _livequery
    features = q.query(concept)
               ^^^^^^^^^^^^^^^^
  File "/home/docs/checkouts/readthedocs.org/user_builds/siibra-python/checkouts/doc_test_ng_resolve/siibra/livequeries/allen.py", line 144, in query
    raise InvalidAllenAPIResponseException(
siibra.livequeries.allen.InvalidAllenAPIResponseException: The service "web API of the Allen Brain Atlas for the human microarray expression" is not available at the moment, therefore siibra is not able to fetch gene expression features. This is a known issue which we are investigating: https://github.com/FZJ-INM1-BDA/siibra-python/issues/636.

Since gene expressions are spatial features, let’s check the reference space of the results.

space = features[0].anchor.space
print(space)

Plot the locations of the probes that were found, together with the region mask of V1.

all_coords = [p.coordinate for p in features[0].anchor.location]
mask = region.get_regional_mask(space)
display = plotting.plot_roi(mask.fetch())
display.add_markers(all_coords, marker_size=5)

Estimated memory usage: 722 MB