An Efficient Fully Automated Method for Gridding Microarray Images

DNA microarray is a powerful tool and is widely used in genetics to monitor expression levels of thousands of genes in parallel. The gene expression process consists of three stages: gridding, segmentation and quantification. Grid- ding deals with finding areas in the microarray image which contain one spot using grid lines. This step can be done ma- nually or automatically. In this paper, we propose an efficient and simple automatic gridding method for microarray image analysis. This method was implemented using MATLAB software and found very effective for gridding arrays with low intensity, poor quality spotsand tested by a number of microarray images. Results show that this method gives high accu- racy of 76.9% improved to 98.6% when a preprocessing step is considered, rendering the method a promising technique for an efficient and automatic gridding the noisy microarray images.

[1]  A. Baxevanis,et al.  A Practical Guide to the Analysis of Genes and Proteins , 1998 .

[2]  Junior Barrera,et al.  Microarray gridding by mathematical morphology , 2001, Proceedings XIV Brazilian Symposium on Computer Graphics and Image Processing.

[3]  Yu Luo,et al.  Gridding and compression of microarray images , 2004, Proceedings. 2004 IEEE Computational Systems Bioinformatics Conference, 2004. CSB 2004..

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

[5]  Ajay N. Jain,et al.  Fully automatic quantification of microarray image data. , 2002, Genome research.

[6]  Yoganand Balagurunathan,et al.  Noise factor analysis for cDNA microarrays. , 2004, Journal of biomedical optics.

[7]  Peter Bajcsy,et al.  An Overview of DNA Microarray Grid Alignment and Foreground Separation Approaches , 2006, EURASIP J. Adv. Signal Process..

[8]  Hong Yan,et al.  Robust adaptive spot segmentation of DNA microarray images , 2003, Pattern Recognit..

[9]  Jörg Rahnenführer,et al.  Unsupervised technique for robust target separation and analysis of DNA microarray spots through adaptive pixel clustering , 2002, Bioinform..

[10]  Tinku Acharya,et al.  Image Processing: Principles and Applications , 2005, J. Electronic Imaging.

[11]  Andreas D. Baxevanis,et al.  Bioinformatics - a practical guide to the analysis of genes and proteins , 2001, Methods of biochemical analysis.

[12]  Tessamma Thomas,et al.  Automatic Gridding of DNA Microarray Images using Optimum Subimage , 2009 .

[13]  J. Todd.  Book Review: Digital image processing (second edition). By R. C. Gonzalez and P. Wintz, Addison-Wesley, 1987. 503 pp. Price: £29.95. (ISBN 0-201-11026-1) , 1988 .