Microarray BASICA: Background Adjustment, Segmentation, Image Compression and Analysis of Microarray Images
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Microarray BASICA: Background Adjustment, Segmentation, Image Compression and Analysis of Microarray Images Jianping Hua Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA Email: [email protected]
Zhongmin Liu Advanced Digital Imaging Research, 2450 South Shore Boulevard, Suite 305, League City, TX 77573, USA Email: [email protected]
Zixiang Xiong Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA Email: [email protected]
Qiang Wu Advanced Digital Imaging Research, 2450 South Shore Boulevard, Suite 305, League City, TX 77573, USA Email: [email protected]
Kenneth R. Castleman Advanced Digital Imaging Research, 2450 South Shore Boulevard, Suite 305, League City, TX 77573, USA Email: [email protected] Received 14 March 2003; Revised 23 September 2003 This paper presents microarray BASICA: an integrated image processing tool for background adjustment, segmentation, image compression, and analysis of cDNA microarray images. BASICA uses a fast Mann-Whitney test-based algorithm to segment cDNA microarray images and performs postprocessing to eliminate the segmentation irregularities. The segmentation results, along with the foreground and background intensities obtained with the background adjustment, are then used for independent compression of the foreground and background. We introduce a new distortion measurement for cDNA microarray image compression and devise a coding scheme by modifying the embedded block coding with optimized truncation (EBCOT) algorithm (Taubman, 2000) to achieve optimal rate-distortion performance in lossy coding while still maintaining outstanding lossless compression performance. Experimental results show that the bit rate required to ensure sufficiently accurate gene expression measurement varies and depends on the quality of cDNA microarray images. For homogeneously hybridized cDNA microarray images, BASICA is able to provide from a bit rate as low as 5 bpp the gene expression data that are 99% in agreement with those of the original 32 bpp images. Keywords and phrases: microarray BASICA, segmentation, Mann-Whitney test, lossy-to-lossless compression, EBCOT.
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INTRODUCTION
The cDNA microarray technology is a hybridization-based process that can quantitatively characterize the relative abundance of gene transcripts [1, 2]. Contrary to conventional methods, microarray technology promises to monitor the transcript production of thousands of genes or even the whole genome simultaneously. It thus provides a new and powerful enabling tool for genetic research and drug discov-
ery. To produce cDNA microarrays, the mRNA of the control and test samples are first reverse-transcribed into cDNA and fluorescently labeled with different dyes (typically red and green). Then the fluorescent targets are mixed and allowed to hybridize with gene-specific cDNA clones printed in an array format on a glass microslide. Finally, by scanning the microslide with a laser and capturing the photons emitted from different dyes into different
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