Analysis of variance (ANOVA) was employed to investigate 9,000 gene expression patterns from brains of both normal mice and mice with a pharmacological model of Parkinson's disease (PD). The data set was obtained using voxelation, a method that allows high-throughput acquisition of 3D gene expression patterns through analysis of spatially registered voxels (cubes). This method produces multiple volumetric maps of gene expression analogous to the images reconstructed in biomedical imaging systems. The ANOVA model was compared to the results from singular value decomposition (SVD) by using the first 42 singular vectors of the data matrix, a number equal to the rank of the ANOVA model. The ANOVA was also compared to the results from non-parametric statistics. Lastly, images were obtained for a subset of genes that emerged from the ANOVA as significant. The results suggest that ANOVA will be a valuable framework for insights into the large number of gene expression patterns obtained from voxelation.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
This is the net price. Taxes to be calculated in checkout.
Brown, V. M., Ossadtchi, A., Khan, A. H., Cherry, S. R., Leahy, R. M., and Smith, D. J. 2002. High-throughput imaging of brain gene expression. Genome Res. 12:244-254.
Brown, V. M., Ossadtchi, A., Khan, A. H., Yee, S., Lacan, G., Melega, W. P., Cherry, S. R., Leahy, R. M., and Smith, D. J. 2002. Multiplex three dimensional brain gene expression mapping in a mouse model of Parkinson's disease. Genome Res. 12:868-884.
Peterson, A. S. 2002. Pixelating the brain. Genome Res. 12: 217-218.
Kerr, M. K., Martin, M., and Churchill, G. A. 2000. Analysis of variance for gene expression microarray data. J. Comput. Biol. 7:819-837.
Kerr, M. K. and Churchill, G. A. 2001. Statistical design and the analysis of gene expression microarray data. Genet. Res. 77: 123-128.
Kerr, M. K. and Churchill, G. A. 2001. Experimental design for gene expression microarrays. Biostatistics 2:183-201.
Sonsalla, P. K., Jochnowitz, N. D., Zeevalk, G. D., Oostveen, J. A., and Hall, E. D. 1996. Treatment of mice with methamphetamine produces cell loss in the substantia nigra. Brain Res. 738:172-175.
Melega, W. P., Raleigh, M. J., Stout, D. B., Lacan, G., Huang, S. C., and Phelps, M. E. 1997. Recovery of striatal dopamine function after acute amphetamine-and methamphetamine-induced neurotoxicity in the vervet monkey. Brain Res. 766:113-120.
Williams, R. W. 2000. Mapping genes that modulate mouse brain development: a quantitative genetic approach. Pages 21-49, in Goffinet, A. F., and Rakic, P. (eds.), Mouse Brain Development, Springer, New York.
Rosen, G. D., Williams, A. G., Capra, J. A., Connolly, M. T., Cruz, B., Lu, L., Airey, D. C., Kulkarni, K., and Williams, R. W. 2000. The Mouse Brain Library @ www.mbl.org. Int. Mouse Genome Conf. 14:166. www.mbl.org.
Nichols, T. E. and Holmes, A. P. 2002. Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum. Brain Mapp. 15:1-25.
Little, R. J. A. and Rubin, D. B. 1987. Statistical Analysis with Missing Data, John Wiley & Sons, New York, NY.
Alter, O., Brown, P. O., and Botstein, D. 2000. Singular value decomposition for genome-wide expression data processing and modeling. Proc. Natl. Acad. Sci. USA 97:10101-10106.
Frackowiak, R. S. J., Friston, K. J., Frith, C. D., Dolan, R. J., and Mazziotta, J. C. 1997. Human Brain Function, Academic Press Ltd., London, UK.
Hendler, R. W. and Shrager, R. I. 1994. Deconvolutions based on singular value decomposition and the pseudoinverse: a guide for beginners. J. Biochem. Biophys. Methods 28:1-33.
Hastie, T., Tibshirani, R., Eisen, M. B., Alizadeh, A., Levy, R., Staudt, L., Chan, W. C., Botstein, D., and Brown, P. 2000. ‘Gene shaving’ as a method for identifying distinct sets of genes with similar expression patterns. Genome Biol.
Gene Ontology Consortium. http://www.geneontology.org/.
Sinharay, S., Stern, H. S., and Russell, D. 2001. The use of multiple imputation for the analysis of missing data. Psychol. Methods 6:317-329.
About this article
Cite this article
Ossadtchi, A., Brown, V.M., Khan, A.H. et al. Statistical Analysis of Multiplex Brain Gene Expression Images. Neurochem Res 27, 1113–1121 (2002). https://doi.org/10.1023/A:1020965107124
- Parkinson's disease
- singular value decomposition