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Published online 13 February 2004

Nucleic Acids Research, 2004, Vol. 32, No. 3 e29
© 2004 Oxford University Press

Reliability of gene expression ratios for cDNA microarrays in multiconditional experiments with a reference design

Rainer König*, Danila Baldessari1, Nicolas Pollet1, Christof Niehrs1 and Roland Eils

Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany and 1 Division of Molecular Embryology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany

*To whom correspondence should be addressed. Tel: +49 6221 423600; Fax: +49 6221 423620; Email: r.koenig{at}dkfz.de
Present address:
Nicolas Pollet, Transgenèse et Génétique des Amphibiens, CNRS ESA8080, IBAIC Bat. 447, Université Paris-Sud, F-91405 Orsay, France
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors

In a typical gene expression profiling experiment with multiple conditions, a common reference sample is used for co-hybridization with the samples to yield expression ratios. Differential expression for any other sample pair can then be calculated by assembling the ratios from their hybridizations with the reference. In this study we test the validity of this approach. Differential expression of a sample pair (i, j) was obtained in two ways: directly, by hybridizations of sample i versus j, and indirectly, by multiplying the expression ratios for hybridizations of sample i versus pool and pool versus sample j. We performed gene expression profiling using amphibian embryos (Xenopus laevis). Every sample combination of four different stages and a pool was profiled. Direct and indirect values were compared and used as the quality criterion for the data. Based on this criterion, 82% of all ratios were found to be sufficiently accurate. To increase the reliability of the signals, several widely used filtering techniques were tested. Filtering by differences of repeated hybridizations was found to be the optimal filter. Finally, we compared microarray-based gene expression profiles with the corresponding expression patterns obtained by whole-mount in situ hybridizations, resulting in a 90% correspondence.


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