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

Bohland, J. W., Bokil, H., Pathak, S. D., Lee, C. K., Ng, L., Lau, C., Kuan, C., Hawrylycz, M., Mitra, P. P. (February 2010) Clustering of spatial gene expression patterns in the mouse brain and comparison with classical neuroanatomy. Methods, 50 (2). pp. 105-112.

URL: https://www.ncbi.nlm.nih.gov/pubmed/19733241
DOI: 10.1016/j.ymeth.2009.09.001

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. © 2009 Elsevier Inc. All rights reserved.

Item Type: Paper
Uncontrolled Keywords: Brain Atlas Clustering Exploratory data analysis Gene expression Mouse Neuroanatomy Singular value decomposition
Subjects: bioinformatics > genomics and proteomics > annotation > gene expression profiling annotation
bioinformatics > genomics and proteomics
bioinformatics > genomics and proteomics > Mapping and Rendering
bioinformatics > quantitative biology
CSHL Authors:
Communities: CSHL labs > Mitra lab
Depositing User: CSHL Librarian
Date: February 2010
Date Deposited: 27 Sep 2011 15:20
Last Modified: 03 Feb 2017 16:06
Related URLs:
URI: http://repository.cshl.edu/id/eprint/15361

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