Clustering of spatial gene expression patterns in the mouse brain and comparison with classical neuroanatomy Export

@article{citeulike:5758961, abstract = {Spatial gene expression profiles provide a novel means of exploring the structural organization of the brain. Computational analysis of these patterns is made possible by genome-scale mapping of the C57BL/6J mouse brain in the Allen Brain Atlas. Here we describe methodology used to explore the spatial structure of gene expression patterns across a set of 3041 genes chosen on the basis of consistency across experimental observations ( N  = 2). The analysis was performed on smoothed, co-registered 3D expression volumes for each gene obtained by aggregating cellular resolution image data. Following dimensionality and noise reduction, voxels were clustered according to similarity of expression across the gene set. We illustrate the resulting parcellations of the mouse brain for different numbers of clusters ( K ) and quantitatively compare these parcellations with a classically-defined anatomical reference atlas at different levels of granularity, revealing a high degree of correspondence. These observations suggest that spatial localization of gene expression offers substantial promise in connecting knowledge at the molecular level with higher-level information about brain organization.}, author = {Bohland, Jason W. and Bokil, Hemant and Pathak, Sayan D. and Lee, Chang-Kyu and Ng, Lydia and Lau, Christopher and Kuan, Chihchau and Hawrylycz, Michael and Mitra, Partha P.}, citeulike-article-id = {5758961}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.ymeth.2009.09.001}, citeulike-linkout-1 = {http://linkinghub.elsevier.com/retrieve/pii/S1046202309002035}, day = {03}, doi = {10.1016/j.ymeth.2009.09.001}, issn = {10462023}, journal = {Methods}, keywords = {brain\_region, gene\_expression}, month = {September}, posted-at = {2009-11-07 00:33:55}, priority = {2}, title = {Clustering of spatial gene expression patterns in the mouse brain and comparison with classical neuroanatomy}, url = {http://dx.doi.org/10.1016/j.ymeth.2009.09.001}, year = {2009} }

TY - JOUR ID - citeulike:5758961 L3 - citeulike-article-id:5758961 N2 - Spatial gene expression profiles provide a novel means of exploring the structural organization of the brain. Computational analysis of these patterns is made possible by genome-scale mapping of the C57BL/6J mouse brain in the Allen Brain Atlas. Here we describe methodology used to explore the spatial structure of gene expression patterns across a set of 3041 genes chosen on the basis of consistency across experimental observations ( N  = 2). The analysis was performed on smoothed, co-registered 3D expression volumes for each gene obtained by aggregating cellular resolution image data. Following dimensionality and noise reduction, voxels were clustered according to similarity of expression across the gene set. We illustrate the resulting parcellations of the mouse brain for different numbers of clusters ( K ) and quantitatively compare these parcellations with a classically-defined anatomical reference atlas at different levels of granularity, revealing a high degree of correspondence. These observations suggest that spatial localization of gene expression offers substantial promise in connecting knowledge at the molecular level with higher-level information about brain organization. JF - Methods SN - 10462023 TI - Clustering of spatial gene expression patterns in the mouse brain and comparison with classical neuroanatomy KW - brain_region KW - gene_expression AU - Bohland, Jason AU - Bokil, Hemant AU - Pathak, Sayan AU - Lee, Chang-Kyu AU - Ng, Lydia AU - Lau, Christopher AU - Kuan, Chihchau AU - Hawrylycz, Michael AU - Mitra, Partha PY - 2009/09/03/ UR - http://dx.doi.org/10.1016/j.ymeth.2009.09.001 ER -