Gridding spot centers of smoothly distorted microarray images

We use an optimization technique to accurately locate a distorted grid structure in a microarray image. By assuming that spot centers deviate smoothly from a checkerboard grid structure, we show that the process of gridding spot centers can be formulated as a constrained optimization problem. The constraint is equal to the variations of the transform parameter. We demonstrate the accuracy of our algorithm on two sets of microarray images. One set consists of some images from the Stanford Microarray Database; we compare our centers with those annotated in the Database. The other set consists of oligonucleotide images, and we compare our results with those obtained by GenePix Pro 5.0. Our experiments were performed completely automatically.

[1]  Ronald W. Davis,et al.  Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray , 1995, Science.

[2]  I. Miller Probability, Random Variables, and Stochastic Processes , 1966 .

[3]  Y. Tu,et al.  Quantitative noise analysis for gene expression microarray experiments , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[4]  R. Fabbri,et al.  Towards non-parametric gridding of microarray images , 2002, 2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628).

[5]  Y. Chen,et al.  Ratio-based decisions and the quantitative analysis of cDNA microarray images. , 1997, Journal of biomedical optics.

[6]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[7]  D. Lockhart,et al.  Expression monitoring by hybridization to high-density oligonucleotide arrays , 1996, Nature Biotechnology.

[8]  Yehezkel Lamdan,et al.  Affine invariant model-based object recognition , 1990, IEEE Trans. Robotics Autom..

[9]  Haim J. Wolfson,et al.  Geometric hashing: an overview , 1997 .

[10]  Anil K. Jain Fundamentals of Digital Image Processing , 2018, Control of Color Imaging Systems.

[11]  S. P. Fodor,et al.  High density synthetic oligonucleotide arrays , 1999, Nature Genetics.

[12]  Charles L. Kooperberg,et al.  Improved Background Correction for Spotted DNA Microarrays , 2002, J. Comput. Biol..

[13]  M. Bittner,et al.  Expression profiling using cDNA microarrays , 1999, Nature Genetics.

[14]  Isidore Rigoutsos,et al.  A Bayesian Approach to Model Matching with Geometric Hashing , 1995, Computer Vision and Image Understanding.

[15]  Terence P. Speed,et al.  Comparison of Methods for Image Analysis on cDNA Microarray Data , 2002 .

[16]  F. Dehne,et al.  Hypercube algorithms for parallel processing of pointer-based quadtrees , 1995 .

[17]  Jens Michael Carstensen,et al.  Bayesian Grid Matching , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Dana H. Ballard,et al.  Computer Vision , 1982 .

[19]  Y. J. Tejwani,et al.  Robot vision , 1989, IEEE International Symposium on Circuits and Systems,.

[20]  P. Brown,et al.  DNA arrays for analysis of gene expression. , 1999, Methods in enzymology.

[21]  T. Speed,et al.  Statistical issues in cDNA microarray data analysis. , 2003, Methods in molecular biology.

[22]  G. Gibson,et al.  Microarray Analysis , 2020, Definitions.

[23]  E. Winzeler,et al.  Genomics, gene expression and DNA arrays , 2000, Nature.

[24]  M. Morley,et al.  Making and reading microarrays , 1999, Nature Genetics.

[25]  Jeremy Buhler,et al.  Dapple: Improved Techniques for Finding Spots on DNA Microarrays , 2000 .

[26]  Yali Amit,et al.  Graphical Templates for Model Registration , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  Charles A. Bouman,et al.  A multiscale random field model for Bayesian image segmentation , 1994, IEEE Trans. Image Process..

[28]  David Botstein,et al.  The Stanford Microarray Database: data access and quality assessment tools , 2003, Nucleic Acids Res..