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Statistical Applications in Genetics and Molecular Biology

Editor-in-Chief: Sanguinetti, Guido

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Volume 3, Issue 1


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Volume 1 (2002)

Saturation and Quantization Reduction in Microarray Experiments using Two Scans at Different Sensitivities

Jorge García de la Nava / Sacha van Hijum
  • Department of Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, The Netherlands
  • Other articles by this author:
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/ Oswaldo Trelles
Published Online: 2004-06-08 | DOI: https://doi.org/10.2202/1544-6115.1057

We present a mathematical model to extend the dynamic range of gene expression data measured by laser scanners. The strategy is based on the rather simple but novel idea of producing two images with different scanner sensitivities, obtaining two different sets of expression values: the first is a low-sensitivity measure to obtain high expression values which would be saturated in a high-sensitivity measure; the second, by the converse strategy, obtains additional information about the low-expression levels. Two mathematical models based on linear and gamma curves are presented for relating the two measurements to each other and producing a coherent and extended range of values. The procedure minimizes the quantization relative error and avoids the collateral effects of saturation. Since most of the current scanner devices are able to adjust the saturation level, the strategy can be considered as a universal solution, and not dependent on the image processing software used for reading the DNA chip. Various tests have been performed, on both proprietary and public domain data sets, showing a reduction of the saturation and quantization effects, not achievable by other methods, with a more complete description of gene-expression data and with a reasonable computational complexity.

Keywords: microarray; preprocessing; saturation; quantization

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Published Online: 2004-06-08

Citation Information: Statistical Applications in Genetics and Molecular Biology, Volume 3, Issue 1, Pages 1–16, ISSN (Online) 1544-6115, DOI: https://doi.org/10.2202/1544-6115.1057.

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