The Effect of Microarray Image Compression on Expression-Based Classification

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Type: Journal Publication


Abstract: Current gene-expression microarrays carry enormous amounts of information. Compression is necessary for efficient distribution and storage. This paper examines JPEG2000 compression of cDNA microarray images and addresses the accuracy of classification and feature selection based on decompressed images. Among other options, we choose JPEG2000 because it is the latest international standard for image compression and offers lossy-to-lossless compression while achieving high lossless compression ratios on microarray images. The performance of JPEG2000 has been tested on three real data sets at different compression ratios, ranging from lossless to 45:1. The effects of JPEG2000 compression/decompression on differential expression detection and phenotype classification have been examined. There is less than a 4% change in differential detection at compression rates as high as 20:1, with detection accuracy suffering less than 2% for moderate to high intensity genes, and there is no significant effect on classification at rates as high as 35:1. The supplementary material is available at

Cited as: Q. Xu, J. Hua, Z. Xiong, M.L. Bittner, and E. R. Dougherty, "The Effect of Microarray Image Compression on Expression-Based Classification", Signal, Image and Video Processing February 2009, Volume 3, Issue 1, pp 53-61

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