Summary
Calibration of microarray measurements aims at removing systematic biases from the probe-level data to get expression estimates that linearly correlate with the transcript abundance in the studied samples. The improvement of calibration methods is an essential prerequisite for estimating absolute expression levels, which, in turn, are required for quantitative analyses of transcriptional regulation, for example, in the context of gene profiling of diseases. We address hybridization on microarrays as a reaction process in a complex environment and express the measured intensities as a function of the input quantities of the experiment. Popular calibration methods such as MAS5, dChip, RMA, gcRMA, vsn, and PLIER are briefly reviewed and assessed in light of the hybridization model and of previous benchmark studies. We present our hook method, a new calibration approach that is based on a graphical summary of the actual hybridization characteristics of a particular microarray. Although single-chip related, hook performs as well as the multi-chip-related gcRMA, presently one of the best state-of-the-art methods for estimating expression values. The hook method, in addition, provides a set of chip summary characteristics that evaluate the performance of a given hybridization. The algorithm of the method is briefly described and its performance is exemplified.
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Acknowledgments
We thank Anke Wendschlag for performing some of the data calculations. The work was supported by the Deutsche Forschungsgemeinschaft under grant no. BIZ 6/4. H. Berger was supported by the Molecular Mechanisms in Malignant Lymphomas Network Project of the Deutsche Krebshilfe (grant no. 70-3173-Tr3) to which we are grateful for using the MMML gene expression data.
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Binder, H., Preibisch, S., Berger, H. (2009). Calibration of Microarray Gene-Expression Data. In: Grützmann, R., Pilarsky, C. (eds) Cancer Gene Profiling. Methods in Molecular Biology, vol 576. Humana Press. https://doi.org/10.1007/978-1-59745-545-9_20
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DOI: https://doi.org/10.1007/978-1-59745-545-9_20
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