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Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering.

Ji S - BMC Bioinformatics (2013)

Bottom Line: Our results show that the developing brain anatomy is largely preserved in the reduced gene expression space.To provide a quantitative analysis, we cluster the reduced data into groups and measure the consistency with neuroanatomy at multiple levels.Dimensionality reduction and visual exploration facilitate the study of this relationship.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Computer Science, Old Dominion University, 4700 Elkhorn Avenue, Suite 3300, Norfolk, VA 23529-0162, USA. sji@cs.odu.edu

ABSTRACT

Background: The structured organization of cells in the brain plays a key role in its functional efficiency. This delicate organization is the consequence of unique molecular identity of each cell gradually established by precise spatiotemporal gene expression control during development. Currently, studies on the molecular-structural association are beginning to reveal how the spatiotemporal gene expression patterns are related to cellular differentiation and structural development.

Results: In this article, we aim at a global, data-driven study of the relationship between gene expressions and neuroanatomy in the developing mouse brain. To enable visual explorations of the high-dimensional data, we map the in situ hybridization gene expression data to a two-dimensional space by preserving both the global and the local structures. Our results show that the developing brain anatomy is largely preserved in the reduced gene expression space. To provide a quantitative analysis, we cluster the reduced data into groups and measure the consistency with neuroanatomy at multiple levels. Our results show that the clusters in the low-dimensional space are more consistent with neuroanatomy than those in the original space.

Conclusions: Gene expression patterns and developing brain anatomy are closely related. Dimensionality reduction and visual exploration facilitate the study of this relationship.

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Related in: MedlinePlus

Visualization of the Allen Developing Mouse Brain Atlas data for age E11.5 after projecting to 2-D space using t-SNE (left column) and PCA (right column) at multiple levels of the ontology. The three rows correspond to Levels 1, 3, and 5. Each point corresponds to a brain voxel, which is displayed using the structure abbreviation and color of its Reference Atlas annotation. The structure abbreviations can be seen by zooming into each figure, and the structure name can be found in Figure 3.
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Figure 4: Visualization of the Allen Developing Mouse Brain Atlas data for age E11.5 after projecting to 2-D space using t-SNE (left column) and PCA (right column) at multiple levels of the ontology. The three rows correspond to Levels 1, 3, and 5. Each point corresponds to a brain voxel, which is displayed using the structure abbreviation and color of its Reference Atlas annotation. The structure abbreviations can be seen by zooming into each figure, and the structure name can be found in Figure 3.

Mentions: To visually explore the relationship between spatial gene expression patterns and brain neuroanatomy, we project the high-dimensional, voxel-level gene expression vectors onto 2-D space using t-SNE and PCA. In PCA, the data matrices are centered by subtracting the mean. To investigate this relationship at multiple levels of the ontology, we display each projected data point using its Level 1, Level 3, and Level 5 annotations, where the structure abbreviation is used as the marker that is color-coded according to its Reference Atlas ontology color. The full names of structures can be found in Figure 3. We show the results generated by t-SNE and PCA using Level 1, Level 3, and Level 5 annotations in Figures 4 and 5 for ages E11.5 and P28, respectively. The complete set of visualization results for all other ages are included in the Additional file 1.


Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering.

Ji S - BMC Bioinformatics (2013)

Visualization of the Allen Developing Mouse Brain Atlas data for age E11.5 after projecting to 2-D space using t-SNE (left column) and PCA (right column) at multiple levels of the ontology. The three rows correspond to Levels 1, 3, and 5. Each point corresponds to a brain voxel, which is displayed using the structure abbreviation and color of its Reference Atlas annotation. The structure abbreviations can be seen by zooming into each figure, and the structure name can be found in Figure 3.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3750329&req=5

Figure 4: Visualization of the Allen Developing Mouse Brain Atlas data for age E11.5 after projecting to 2-D space using t-SNE (left column) and PCA (right column) at multiple levels of the ontology. The three rows correspond to Levels 1, 3, and 5. Each point corresponds to a brain voxel, which is displayed using the structure abbreviation and color of its Reference Atlas annotation. The structure abbreviations can be seen by zooming into each figure, and the structure name can be found in Figure 3.
Mentions: To visually explore the relationship between spatial gene expression patterns and brain neuroanatomy, we project the high-dimensional, voxel-level gene expression vectors onto 2-D space using t-SNE and PCA. In PCA, the data matrices are centered by subtracting the mean. To investigate this relationship at multiple levels of the ontology, we display each projected data point using its Level 1, Level 3, and Level 5 annotations, where the structure abbreviation is used as the marker that is color-coded according to its Reference Atlas ontology color. The full names of structures can be found in Figure 3. We show the results generated by t-SNE and PCA using Level 1, Level 3, and Level 5 annotations in Figures 4 and 5 for ages E11.5 and P28, respectively. The complete set of visualization results for all other ages are included in the Additional file 1.

Bottom Line: Our results show that the developing brain anatomy is largely preserved in the reduced gene expression space.To provide a quantitative analysis, we cluster the reduced data into groups and measure the consistency with neuroanatomy at multiple levels.Dimensionality reduction and visual exploration facilitate the study of this relationship.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Computer Science, Old Dominion University, 4700 Elkhorn Avenue, Suite 3300, Norfolk, VA 23529-0162, USA. sji@cs.odu.edu

ABSTRACT

Background: The structured organization of cells in the brain plays a key role in its functional efficiency. This delicate organization is the consequence of unique molecular identity of each cell gradually established by precise spatiotemporal gene expression control during development. Currently, studies on the molecular-structural association are beginning to reveal how the spatiotemporal gene expression patterns are related to cellular differentiation and structural development.

Results: In this article, we aim at a global, data-driven study of the relationship between gene expressions and neuroanatomy in the developing mouse brain. To enable visual explorations of the high-dimensional data, we map the in situ hybridization gene expression data to a two-dimensional space by preserving both the global and the local structures. Our results show that the developing brain anatomy is largely preserved in the reduced gene expression space. To provide a quantitative analysis, we cluster the reduced data into groups and measure the consistency with neuroanatomy at multiple levels. Our results show that the clusters in the low-dimensional space are more consistent with neuroanatomy than those in the original space.

Conclusions: Gene expression patterns and developing brain anatomy are closely related. Dimensionality reduction and visual exploration facilitate the study of this relationship.

Show MeSH
Related in: MedlinePlus