Computational neuroanatomy and gene expression: optimal sets of marker genes for brain regions

Abstract

The three-dimensional data-driven Allen Gene Expression Atlas of the adult mouse brain consists of numerized in-situ hybridization data for thousands of genes, co-registered to the Allen Reference Atlas. We propose quantitative criteria to rank genes as markers of a brain region, based on the localization of the gene expression and on its functional fitting to the shape of the region. These criteria lead to natural generalizations to sets of genes. We find sets of genes weighted with coefficients of both signs with almost perfect localization in all major regions of the left hemisphere of the brain, except the pallidum. Generalization of the fitting criterion with positivity constraint provides a lesser improvement of the markers, but requires sparser sets of genes.

arXiv comment6 pages, 5 figures

References in corpus (3)

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• Algorithmic choice of coordinates for injections into the brain: encoding a neuroanatomical atlas on a grid
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Cited by in corpus (5)

• Cell-type-specific transcriptomes and the Allen Atlas (II): discussion of the linear model of brain-wide densities of cell types
• Computational neuroanatomy and co-expression of genes in the adult mouse brain, analysis tools for the Allen Brain Atlas
• What does the Allen Gene Expression Atlas tell us about mouse brain evolution?
• Cell-type-specific computational neuroanatomy, simulations from the sagittal and coronal Allen Brain Atlas
• Computational neuroanatomy: mapping cell-type densities in the mouse brain, simulations from the Allen Brain Atlas