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  • Generalization of DNA microarray dispersion properties: microarray equivalent of t-distribution

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    Author(s)
    Novak, Jaroslav
    Kim, Seon-Young
    Xu, Jun
    Modlich, Olga
    Volsky, David
    Honys, David
    Slonczewski, Joan
    Bell, Douglas
    Blattner, Fred
    Blumwald, Eduardo
    Boerma, Marjan
    Cosio, Manuel
    Gatalica, Zoran
    Hajduch, Marian
    Hidalgo, Juan
    McInnes, Roderick
    Miller III, Merrill
    Penkowa, Milena
    Rolph, Michael
    Sottosanto, Jordan
    St-Arnaud, Rene
    Szego, Michael
    Twell, David
    Wang, Charles
    Griffith University Author(s)
    Rolph, Michael S.
    Year published
    2006
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    Abstract
    Background DNA microarrays are a powerful technology that can provide a wealth of gene expression data for disease studies, drug development, and a wide scope of other investigations. Because of the large volume and inherent variability of DNA microarray data, many new statistical methods have been developed for evaluating the significance of the observed differences in gene expression. However, until now little attention has been given to the characterization of dispersion of DNA microarray data. Results Here we examine the expression data obtained from 682 Affymetrix GeneChipsith 22 different types and we demonstrate ...
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    Background DNA microarrays are a powerful technology that can provide a wealth of gene expression data for disease studies, drug development, and a wide scope of other investigations. Because of the large volume and inherent variability of DNA microarray data, many new statistical methods have been developed for evaluating the significance of the observed differences in gene expression. However, until now little attention has been given to the characterization of dispersion of DNA microarray data. Results Here we examine the expression data obtained from 682 Affymetrix GeneChipsith 22 different types and we demonstrate that the Gaussian (normal) frequency distribution is characteristic for the variability of gene expression values. However, typically 5 to 15% of the samples deviate from normality. Furthermore, it is shown that the frequency distributions of the difference of expression in subsets of ordered, consecutive pairs of genes (consecutive samples) in pair-wise comparisons of replicate experiments are also normal. We describe a consecutive sampling method, which is employed to calculate the characteristic function approximating standard deviation and show that the standard deviation derived from the consecutive samples is equivalent to the standard deviation obtained from individual genes. Finally, we determine the boundaries of probability intervals and demonstrate that the coefficients defining the intervals are independent of sample characteristics, variability of data, laboratory conditions and type of chips. These coefficients are very closely correlated with Student's t-distribution. Conclusion In this study we ascertained that the non-systematic variations possess Gaussian distribution, determined the probability intervals and demonstrated that the Ka coefficients defining these intervals are invariant; these coefficients offer a convenient universal measure of dispersion of data. The fact that the Ka distributions are so close to t-distribution and independent of conditions and type of arrays suggests that the quantitative data provided by Affymetrix technology give "true" representation of physical processes, involved in measurement of RNA abundance.
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    Journal Title
    Biology Direct
    Volume
    1
    DOI
    https://doi.org/10.1186/1745-6150-1-27
    Copyright Statement
    © 2006 Novak et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    Subject
    Gene Expression (incl. Microarray and other genome-wide approaches)
    Biological Sciences
    Medical and Health Sciences
    Publication URI
    http://hdl.handle.net/10072/55070
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    • Journal articles

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