Genet. Sel. Evol.
Volume 40, Number 2, March-April 2008
|Page(s)||145 - 159|
|Published online||27 February 2008|
Measuring connectedness among herds in mixed linear models: From theory to practice in large-sized genetic evaluationsMarie-Noëlle Fouilloux1, Virginie Clément2 and Denis Laloë3
1 Institut de l'Élevage, Station de génétique quantitative et appliquée, INRA, 78352 Jouy-en-Josas, France
2 Institut de l'Élevage, Station d'amélioration génétique des animaux, INRA, 31326 Castanet-Tolosan, France
3 Station de génétique quantitative et appliquée UR337, INRA, 78352 Jouy-en-Josas, France
(Received 8 February 2007; accepted 16 October 2007; published online 27 February 2008)
Abstract - A procedure to measure connectedness among groups in large-sized genetic evaluations is presented. It consists of two steps: (a) computing coefficients of determination (CD) of comparisons among groups of animals; and (b) building sets of connected groups. The CD of comparisons were estimated using a sampling-based method that estimates empirical variances of true and predicted breeding values from a simulated n-sample. A clustering method that may handle a large number of comparisons and build compact clusters of connected groups was developed. An aggregation criterion (Caco) that reflects the level of connectedness of each herd was computed. This procedure was validated using a small beef data set. It was applied to the French genetic evaluation of the beef breed with most records and to the genetic evaluation of goats. Caco was more related to the type of service of sires used in the herds than to herd size. It was very sensitive to the percentage of missing sires. Disconnected herds were reliably identified by low values of Caco. In France, this procedure is the reference method for evaluating connectedness among the herds involved in on-farm genetic evaluation of beef cattle (IBOVAL) since 2002 and for genetic evaluation of goats from 2007 onwards.
Key words: connectedness / clustering / BLUP / accuracy
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© INRA, EDP Sciences 2008