Post-Hybridization Quality Measures for Oligos in Genome-Wide Microarray Experiments

  • Florian Battke
  • Carsten Müller-Tidow
  • Hubert Serve
  • Kay Nieselt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5251)

Abstract

High-throughput microarray experiments produce vast amounts of data. Quality control methods for every step of such experiments are essential to ensure a high biological significance of the conclusions drawn from the data. This issue has been addressed for most steps of the typical microarray pipeline, but the quality of the oligonucleotide probes designed for microarrays has only been evaluated based on their a priori properties, such as sequence length or melting temperature predictions. We introduce new oligo quality measures that can be calculated using expression values collected in direct as well as indirect design experiments. Based on these measures, we propose combined oligo quality scores as a tool for assessing probe quality, optimizing array designs and data normalization strategies. We use simulated as well as biological data sets to evaluate these new quality scores. We show that the presented quality scores reliably identify high-quality probes. The set of best-quality probes converges with increasing number of arrays used for the calculation and the measures are robust with respect to the chosen normalization method.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Florian Battke
    • 1
  • Carsten Müller-Tidow
    • 2
  • Hubert Serve
    • 3
  • Kay Nieselt
    • 1
  1. 1.Center for Bioinformatics Tübingen, Department of Information and Cognitive SciencesUniversity of TübingenTübingenGermany
  2. 2.IZKF - Inderdisciplinary Center for Clinical Research at the University of MünsterMünsterGermany
  3. 3.Department of Internal Medicine IIUniversity Hospital, Johann Wolfgang Goethe-UniversityFrankfurt am MainGermany

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