Conference proceeding
MACE: lossless compression and analysis of microarray images
Proceedings of the 2006 ACM symposium on applied computing, Vol.1, pp.167-172
SAC '06
04/23/2006
DOI: 10.1145/1141277.1141315
Abstract
The ubiquity of microarray expression data in state-of-the-art biology has been well established. The widespread adoption of this technology coupled with the significant volume of image-based experimental data generated per experiment (averaging 40 MB), have led to significant challenges in storage and query-retrieval of primary data from microarray experiments. Research in the yet nascent area of microarray data-compression seeks to address this problem. In this paper, we propose a conceptually novel approach that achieves significantly better lossless compression. Unlike lossy compression, our algorithm is guaranteed against loss of information that may have potential biological relevance. The proposed method supports key operations such as automated grid and spot finding, histogram-based automatic thresholding for spot segmentation, and subsequent foreground and background separation. Based on the proposed approach, we have developed a standardized format for storing microarray data that encapsulates all the relevant information, including both the Cy3 and Cy5 expression images significantly compressed. We have also developed a software application called MACE (Microarray Compression and Extraction application) to compress-decompress microarray data and generate the aforementioned format. Compression-decompression results on a wide class of microarray experiments involving different spot layouts validate the effectiveness of our approach and its potential to significantly address the aforementioned challenges in storage and management of microarray data.
Details
- Title: Subtitle
- MACE: lossless compression and analysis of microarray images
- Creators
- Robert Bierman - San Francisco State UniversityNidhi Maniyar - San Francisco State UniversityCharles Parsons - University of VermontRahul Singh - San Francisco State University
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of the 2006 ACM symposium on applied computing, Vol.1, pp.167-172
- Publisher
- ACM
- Series
- SAC '06
- DOI
- 10.1145/1141277.1141315
- Language
- English
- Date published
- 04/23/2006
- Academic Unit
- Computer Science
- Record Identifier
- 9984446528502771
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