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hal-00270936, version 1

Normalization for triple-target microarray experiments

Marie-Laure Martin-Magniette () 12, Julie Aubert 2, Avner Bar-Hen () 3, Samira Elftieh 1, F. Magniette, Jean-Pierre Renou 1456, Jean-Jacques Daudin 27

BMC Bioinformatics 9 (2008) 216

Résumé : Background: Most of microarray studies are made using one or two dyes labelling which allows the hybridization of one or two samples on the same slide. In such experiments, the most frequently used dyes are Cy3 and Cy5. Recently improvement of the technology (dye-labelling, scanner and, image analysis) allow to hybridize until four samples simultaneously. The two additional dyes are Alexa488 and Alexa494 but there are few results about statistical analysis of such data, in particular, about the signal distortion due to the use of four dyes. Moreover the loess correction of the global dye effect is available for only two-color experiments, and even if its application can be derived, it does not allow the simultaneous correction of the raw data. However, the triple-target technology is very promising, since it allows more flexibility in the design of experiments, an increase of the statistical power when comparing gene expressions induced by different conditions and a scaled down number of slides. normalization step for microarray Results: We propose a two-step normalization process for triple-target experiments. First the dye bleeding is evaluated and corrected if necessary. Then the signal in each channel is normalized using a generalized loess procedure to correct a global dye bias. The normalization procedure is validated using triple-self experiments and by comparing the results of triple-target and two-color experiments. Although the focus is on triple-target microarrays, the proposed method can be used to normalize p > 2 differently labelled targets co-hybridized on a same array. Conclusions: The proposed normalization procedure is effective: the technical biases are reduced and the number of false positive is under control in the analysis of differentially expressed genes, and the triple-target experiments are more powerful than the corresponding two-color experiments. There is a room for improving the microarray experiments by hybridizing simultaneously more than two samples.

  • 1 :  Unité de recherche en génomique végétale (URGV)
  • CNRS : UMR8114 – Institut national de la recherche agronomique (INRA) : UR1165 – Université d'Evry-Val d'Essonne
  • 2 :  Mathématiques et Informatique Appliquées (MIA)
  • Institut national de la recherche agronomique (INRA) : UMR0518 – AgroParisTech
  • 3 :  Mathématiques appliquées Paris 5 (MAP5)
  • CNRS : UMR8145 – Université Paris V - Paris Descartes
  • 4 :  Unité de Recherche en Genomique Végétale
  • Institut national de la recherche agronomique (INRA)
  • 5 :  Structure tissulaire et intramoléculaire (STIM)
  • Institut national de la recherche agronomique (INRA)
  • 6 :  Unité de Recherche en Génomique Végétale - INRA (URGV)
  • Institut national de la recherche agronomique (INRA)
  • 7 :  SELECT (INRIA Futurs)
  • INRIA – Université Paris XI - Paris Sud
  • Domaine : Informatique/Bio-informatique
    Sciences du Vivant/Bio-Informatique, Biologie Systémique
    Mathématiques/Statistiques
    Statistiques/Théorie
 
  • hal-00270936, version 1
  • oai:hal.archives-ouvertes.fr:hal-00270936
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  • Soumis le : Lundi 7 Avril 2008, 22:03:07
  • Dernière modification le : Mercredi 11 Juillet 2012, 11:28:16