Abstract #300104

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JSM 2002 Abstract #300104
Activity Number: 191
Type: Invited
Date/Time: Tuesday, August 13, 2002 : 10:30 AM to 12:20 PM
Sponsor: Section on Physical & Engineering Sciences*
Abstract - #300104
Title: Compressing Microarray Images for Statistical Analysis
Author(s): Rebecka Jornsten*+ and Bin Yu
Affiliation(s): University of California, Berkeley and University of California, Berkeley
Address: 415 Evans Hall, Berkeley, California, 94720,
Keywords: Lossless/lossy compression ; Multi-level data structure ; Segmentation ; Bit-plane separation ; Progressive coding/transmission.
Abstract:

The Microarray image technology is a powerful tool for monitoring the expression of thousands of genes simultaneously. Each microarray experiment produces large amounts of image data, and though the cost of storage is rapidly decreasing, transmission still presents a significant bottleneck. Hence, we have developed a compression scheme for microarray images which can be either lossless or progressively lossy. Our scheme has a multi-level coded data structure, allowing fast decoding and reprocessing of image subsets. The minimum decodable bitrate depends on the initial choice of parameters, but we find that a compression ratio of 8:1 minimally affects downstream processing. The lossless compression ratio is 1.83:1, comparable to state-of-the-art lossless schemas, yet with the added flexibility of a progressive scheme.

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Revised March 2002