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Background correction of two-colour cDNA microarray data using spatial smoothing methods

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Abstract

The analysis of two-colour cDNA microarray data usually involves subtracting background values from foreground values prior to normalization and further analysis. This approach has the advantage of reducing bias and the disadvantage of blowing up the variance of lower abundant spots. Whenever background subtraction is considered, it implicitly assumes locally constant background values. In practice, this assumption is often not met, which casts doubts on the usefulness of simple background subtraction. In order to improve background correction, we propose local background smoothing within the pre-processing pipeline of cDNA microarray data prior to background correction. For this purpose, we employ a geostatistical framework with ordinary kriging using both isotropic and anisotropic models of spatial correlation and 2-D locally weighted regression. We show that application of local background smoothing prior to background correction is beneficial in comparison to using raw background estimates. This is done using data of a self-versus-self experiment in Arabidopsis where subsets of differentially expressed genes were simulated. Using locally smoothed background values in conjunction with existing background correction methods increases the power, increases the accuracy and decreases the number of false positive results.

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Acknowledgments

We thank Caroline Gouhier-Darimont and Philippe Reymond (Department of Plant Molecular Biology, University of Lausanne, 1015 Lausanne, Switzerland) for providing the self-vs-self dataset. This work was funded by the Deutsche Forschungsgemeinschaft (DFG) within the priority program SPP1149-Heterosis in Plants (grant-no. PI 377/7-3). Prof. Uwe Jensen and two anonymous reviewers are thanked for helpful and constructive comments on earlier versions of the paper.

Conflict of interest statement

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Bioinformatics Unit, Institute for Crop Production and Grassland Research, University of Hohenheim, Fruwirthstrasse 23, 70599, Stuttgart, Germany

    André Schützenmeister & Hans-Peter Piepho

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  1. André Schützenmeister
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  2. Hans-Peter Piepho
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Correspondence to Hans-Peter Piepho.

Additional information

Communicated by M. Frisch.

Contribution to the special issue “Heterosis in Plants”.

The R-code that we used is available from the authors upon request.

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Schützenmeister, A., Piepho, HP. Background correction of two-colour cDNA microarray data using spatial smoothing methods. Theor Appl Genet 120, 475–490 (2010). https://doi.org/10.1007/s00122-009-1210-3

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