A hierarchical refinement algorithm for fully automatic gridding in spotted DNA microarray image processing

Authors:
Yu Wang;Marc Q. Ma;Kai Zhang;Frank Y. Shih
Affiliations:
Computer Vision Laboratory, College of Computing Sciences, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA and Applied Bioinformatics Laboratory, College of Computing ...;Applied Bioinformatics Laboratory, College of Computing Sciences, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA;Computer Vision Laboratory, College of Computing Sciences, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA and Applied Bioinformatics Laboratory, College of Computing ...;Computer Vision Laboratory, College of Computing Sciences, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA
Venue:
Information Sciences: an International Journal
Year:
2007

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Abstract

Gridding, the first step in spotted DNA microarray image processing, usually requires human intervention to achieve acceptable accuracy. We present a new algorithm for automatic gridding based on hierarchical refinement to improve the efficiency, robustness and reproducibility of microarray data analysis. This algorithm employs morphological reconstruction along with global and local rotation detection, non-parametric optimal thresholding and local fine-tuning without any human intervention. Using synthetic data and real microarray images of different sizes and with different degrees of rotation of subarrays, we demonstrate that this algorithm can detect and compensate for alignment and rotation problems to obtain reliable and robust results.