This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Correlation Statistics for cDNA Microarray Image Analysis
July-September 2006 (vol. 3 no. 3)
pp. 232-238
In this paper, correlation of the pixels comprising a microarray spot is investigated. Subsequently, correlation statistics, namely, Pearson correlation and Spearman rank correlation, are used to segment the foreground and background intensity of microarray spots. The performance of correlation-based segmentation is compared to clustering-based (PAM, k-means) and seeded-region growing techniques (SPOT). It is shown that correlation-based segmentation is useful in flagging poorly hybridized spots, thus minimizing false-positives. The present study also raises the intriguing question of whether a change in correlation can be an indicator of differential gene expression.

[1] M. Schena, D. Shalon, R.W. Davis, and P.O. Brown, “Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray,” Science, vol. 270, pp. 467-470, 1995.
[2] D.J. Lockhart, H. Dong, M.C. Byrne, M.T. Follettie, M.V. Gallo, M.S. Chee, M. Mittman, C. Wang, M. Kobayashi, H. Horton, and E.L. Brown, “Expression Monitoring by Hybridization to High-Density Oligonucleotide Arrays,” Nature Biotechnology, vol. 14, no. 13, pp. 1675-1680, 1996.
[3] M. Schena, Microarray Biochip Technology. Eaton Publishing, 2000.
[4] K.M. Kerr and G.A. Churchill, “Experimental Design for Gene Expression Microarrays,” Biostatistics, vol. 2, pp. 183-201, 2000.
[5] B. Phimister, “Going Global,” Nature Genetics, vol. 21, no. 1, p. 1, 1999.
[6] A.K. Jain, Fundamentals of Digital Image Processing. Prentice-Hall, 1989.
[7] Y.H. Yang, M.J. Buckley, S. Dudoit, and T.P. Speed, “Comparison of Methods for Image Analysis on cDNA Microarray Data,” 2001, http://stat-www.berkeley.edu/users/terry/ zarray/Htmlimage. html.
[8] M. Eisen, “ScanAlyze,” 1999, http://rana.lbl.govEisenSoftware. htm.
[9] Y. Chen, E.R. Dougherty, and M.L. Bittner, “Ratio-Based Decisions and the Quantitative Analysis of cDNA Microarray Images,” J.Biomedical Optics, vol. 2, pp. 364-374, 1997.
[10] R. Nagarajan, “Intensity Based Segmentation of Microarray Images,” IEEE Trans. Medical Imaging, vol. 22, no. 7, pp. 882-889, 2003.
[11] S.D. Morgera, “Information Theoretic Complexity and Relation to Pattern Recognition,” IEEE Trans. Systems, Man, and Cybernetics, vol. 15, pp. 608-619, 1985.
[12] W.H. Press, B.P. Flannery, S.A. Teukolsky, and W.T. Vetterling, Numerical Recipes in C: The Art of Scientific Computing, second ed. Cambridge Univ. Press, 1992.
[13] M.J. Callow, S. Dudoit, E.L. Gong, T.P. Speed, and E.M. Rubin, “Microarray Expression Profiling Identifies Genes with Altered Expression In HDL Deficient Mice,” Genome Research, vol. 10, pp.2022-2029, 2000.
[14] Y.H. Yang, S. Dudoit, P. Luu, and T.P. Speed, “Normalization for cDNA Microarray Data,” 2000, http://stat-www.berkeley.edu/users/terry/ zarray/Htmlnormspie.html.
[15] T. Kepler, L. Crosby, and K.T. Morgan, “Normalization and Analysis of DNA Microarray Data by Self-Consistency and Local Regression,” Technical Report 00-09-055, Santa Fe Inst., 2000.
[16] G.H. Golub and C.F. Van Loan, Matrix Computations, third ed. Johns Hopkins Univ. Press, pp. 70-73, 1996.

Index Terms:
Microarrays, image segmentation, Morgera's covariance complexity, Pearson's correlation, Spearman's rank correlation.
Citation:
Radhakrishnan Nagarajan, Meenakshi Upreti, "Correlation Statistics for cDNA Microarray Image Analysis," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 3, no. 3, pp. 232-238, July-Sept. 2006, doi:10.1109/TCBB.2006.30
Usage of this product signifies your acceptance of the Terms of Use.