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Quantitative Trait Loci: A Meta-analysis

Authors :
Sophie Gerber
Bruno Goffinet
Unité de Biométrie et Intelligence Artificielle (UBIA)
Institut National de la Recherche Agronomique (INRA)
Unité de recherches forestières (BORDX PIERR UR )
Source :
Genetics, Genetics, Genetics Society of America, 2000, 155, pp.463-473
Publication Year :
2000
Publisher :
Oxford University Press (OUP), 2000.

Abstract

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/.

Details

ISSN :
19432631 and 00166731
Volume :
155
Database :
OpenAIRE
Journal :
Genetics
Accession number :
edsair.doi.dedup.....cf499724ece96d8787db288968f6964b
Full Text :
https://doi.org/10.1093/genetics/155.1.463