Abstract
We review quantitative methods and software developed to analyze genome-scale, brain-wide spatially-mapped gene-expression data. We expose new methods based on the underlying high-dimensional geometry of voxel space and gene space, and on simulations of the distribution of co-expression networks of a given size. We apply them to the Allen Atlas of the adult mouse brain, and to the coexpression network of a set of genes related to nicotine addiction retrieved from the NicSNP database. The computational methods are implemented in BrainGeneExpressionAnalysis (BGEA), a Matlab toolbox available for download.
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Grange, P., Hawrylycz, M., & Mitra, P. P. (2013, March 1). Computational neuroanatomy and co-expression of genes in the adult mouse brain, analysis tools for the Allen Brain Atlas. Quantitative Biology. Higher Education Press. https://doi.org/10.1007/s40484-013-0011-5
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