Quantitative Trait Loci: A Meta-analysis

Corresponding author: Bruno Goffinet, INRA, Laboratoire de Biométrie et d'Intelligence Artificielle, Centre de Recherches de Toulouse, F-31326 Castanet-Tolosan Cedex, France., goffinet{at}toulouse.inra.fr (E-mail)

Communicating editor: C. HALEY

This article presents a method to combine QTL results from different independent analyses. This method provides a modified Akaike criterion that can be used to decide how many QTL are actually represented by the QTL detected in different experiments. This criterion is computed to choose between models with one, two, three, etc., QTL. Simulations are carried out to investigate the quality of the model obtained with this method in various situations. It appears that the method allows the length of the confidence interval of QTL location to be consistently reduced when there are only very few "actual" QTL locations. An application of the method is given using data from the maize database available online at http://www.agron.missouri.edu/.

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