Anatomic Gene Expression Atlas (AGEA)
What is AGEA?
The Allen Institute has built a data-driven three-dimensional atlas of the adult C57Bl/6J mouse brain based on the ISH gene expression images of the Allen Mouse Brain Atlas. The project is called AGEA which stands for Anatomic Gene Expression Atlas. Essentially, AGEA characterizes the multi-scale spatial relationship in the mouse brain as derived from gene expression data without a prior knowledge of classical anatomy. In the AGEA online application, you can:
- View and navigate 3D spatial relationship maps (Correlation mode);
- Explore a transcriptome based spatial organization of the brain (Clusters mode) and,
- Search for genes with local regionality as defined by AGEA (Gene Finder mode).
The application is loaded by clicking on the AGEA tab from the Mouse Brain Atlas and looks like the following image.
The upper panels of images are orthogonal views of a 3D Nissl reference atlas volume. The reference space was divided into 200 um volumes or voxels that demonstrate a unique gene expression profile. The cross hairs in the top panel of images select for a seed voxel from which to compare to gene expression profiles to all other voxels in the brain. For more detailed information on how AGEA was constructed please see the user guide or Ng L, Bernard A, Lau C, Overly CC, Dong HW, Kuan C, Pathak S, Sunkin SM, Dang C, Bohland JW, Bokil H, Mitra PP, Puelles L, Hohmann J, Anderson DJ, Lein ES, Jones AR, Hawrylycz M (2009) An anatomic gene expression atlas of the adult mouse brain. Nature Neuroscience 12(3): 356-362.
The AGEA Viewer
This section describes the controls of the Correlation, Cluster and Gene Finder modes of AGEA.
A. Seed Selector panel: Use this area to select the seed voxel as marked by the red crosshairs. Either click or click and drag to navigate to a different correlation map.
B. Map panel: This area displays the three orthogonal views of the currently selected correlation map in coronal, sagittal and horizontal planes. The green crosshair marks the
currently selected voxel. Either click or click and drag to move to a new 3D location. Note that this volume can be navigated in 3D for any selected voxel location from A.
1. Permalink/Zoom: Clicking on “Permalink” creates an URL in the address bar that effectively save information about your current viewing state. This URL can be saved for latter access to
directly take you back to the current view and color scale settings. Clicking the arrows will toggle between zooming the images to fit in the window and a higher resolution more zoomed
mode. At a fixed zoom level, you may need to use the browser scroll bars to view all the images.
2. Mode Selector: Click on Correlation, Clusters or Gene Finder to switch the viewer to different modes.
3. Position/ARA: The position of the crosshairs in the seed selector in millimeters from bregma. Click on the icon next to the position to view the closest coronal section of the Allen
4. Lock/Sync: The icon on the left locks the planes shown in the selected expression map B to the same position as the seed map A. Click to toggle the locking behavior. Conversely, click
on the right icon to move the seed voxel to the current selected map voxel.
5. ARA Label: The structure or structural grouping from the Allen Reference Atlas to which the seed voxel (indicated by red crosshairs) belongs. Click on the name to get information about
6. ARA Blend: This icon toggles blending Allen Reference Atlas structural delineations on the Seed Selector images for direct anatomic comparison. A 1 mm grid is also included with the
reference atlas colors. The darker lines indicate the origin of the coordinate system, which is at bregma.
7. Position/ARA: The position of the crosshairs in the correlation map in millimeters from bregma. Click on the icon next to the position to view the closest coronal section of the
8. Color scale control: Use to adjust the false color mapping of the correlation map to threshold the images for regions of higher significance. All voxels with correlation within the
select range are rescaled to span the color scale.
9. ARA Label: The structure or structural grouping to which the selected voxel (indicated by green crosshairs) belongs. Click on the name to get information about the structure.
10. Correlation: Value of the correlation at the currently selected voxel with respect to the seed voxel selected in panel A. This shows numerically how well the target voxel is correlated with
11. Nissl Blend: This icon toggles blending the Nissl reference atlas volume on the correlation map. As with (6), a 1 mm grid is shown, and the brighter lines indicate the origin.
12. Download: Click to download the currently selected correlation map as raw flat file with numbers saved as floats.
Using Correlation Mode
In Correlation mode, the lower panels show orthogonal views of the selected spatial relationship map. The correlation values in the bottom figures can be interpreted as a measure of average co-expression between two voxels. The higher the correlation value between voxels, the more common it is for genes from the seed voxel to be co-expressed. Higher correlation between two voxels indicates more spatial correlation of expression and thus potentially higher possibility that the spatial regions spanned by the voxels are anatomically related. This may indicate that the voxels compared share common cell types or represent a coherent functional map. The correlation map can also be used to locate coexpressing areas in other brain regions. In the above figure, the map indicates that there is higher coexpression with layer 5 than other layers of the cerebral cortex.
When a seed voxel is selected using the crosshairs in the top panels, you can find correlations between the seed voxel and other voxels in the brain by selecting a distinct voxel in the lower panels using those crosshairs. The correlation between the regions will be displayed below the lower panels (section 10).
Selecting Clusters mode switches the lower panels to view a data-driven hierarchical binary-tree spatial organization of the brain computed from the AGEA correlation maps. To construct the decomposition all 51,533 voxels were assigned to the root node of the tree. As we descend the tree, a node is bifurcated into two nodes to achieve maximal dissimilarity between two groups of voxels based on correlation values. The final bi-tree consists of 103,065 nodes with a maximum depth of 53 levels and 51,533 leaf nodes (one for each voxel in the brain). Effective visualization of this large data structure is via an easy-to-use tree depth slider mechanism to navigate the bi-tree, providing 3D context and visualizing the multi-scale partitioning.
The voxels of a node are visualized with a systematic color coding scheme. Each leaf node is
assigned a global ordering such that each internal node of the tree represents voxels with a
contiguously clustered ordering. All voxels of a node are then assigned a color based on the ‘jet’
color scheme where the leaf node with low order number is assigned shades of blues. The colors
then run through green, yellow and orange. Finally, higher order voxels are assigned shades of
reds. Two example node visualizations are shown in Figure 3 for the root node (a) consisting of
all voxels of the brain and (b) for a node overlapping the thalamus. Schematic coloring of the
voxels by global ordering essentially provides a preview to the sub-tree organization. For the root
node Figure 3(a), coarse parcellation into gross anatomical structures can be observed while in
Figure 3(b), the arrangement of the colors indicates medial-lateral and rostral-caudal suborganization
in the thalamus.
AGEA Gene Finder
Figure 4: Gene Finder correlation map with seed voxel in the parafascicular nucleus of the thalamus. A fixed
AGEA correlation domain is shown in the lower panel. Genes exhibiting the highest specificity to the correlated portion
around the seed can be found through the “Find Genes” button shown. The construction of the domain of search and
ranking method is described in the text permalink.
The Gene Finder search facility is among the most powerful aspects of AGEA’s functionality. It
enables users to search a local anatomic region of interest for genes within the ABA database
that exhibits localized enrichment. Finding genes with highly localized expression patterns is of
neuroscientific interest to study structural relationships and/or provide evidence for refinement of