The Allen Brain Atlas (ABA, www.brain-map.org) is a genome wide, spatially registered collection of cellular resolution in situ hybridization gene expression image data of the C57Bl/6J mouse brain. Derived from the ABA, the Anatomic Gene Expression Atlas (AGEA, http://mouse.brain-map.org/agea) has demonstrated both laminar and areal spatial gene expression correlations in the mouse cortex. While the mouse cortex is lissencephalic, its curvature and substantial bending in boundary areas renders it difficult to visualize and analyze laminar versus areal effects in a rectilinear coordinate framework. In context of human and non-human primate cortex, surface-based representation has proven useful for understanding relative locations of laminar, columnar, and areal features. In this paper, we describe a methodology for constructing surface-based flatmaps of the mouse cortex that enables mapping of gene expression data from individual genes in the ABA, or probabilistic expression maps from the AGEA, to identify and visualize genetic relationships between layers and areas.
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