Issue |
Genet. Sel. Evol.
Volume 35, Number 3, May-June 2003
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Page(s) | 281 - 304 | |
DOI | https://doi.org/10.1051/gse:2003009 |
DOI: 10.1051/gse:2003009
Comparison of three multitrait methods for QTL detection
Hélène Gilbert and Pascale Le RoyInstitut national de la recherche agronomique, Station de génétique quantitative et appliquée, 78352 Jouy-en-Josas Cedex, France
(Received 30 April 2002; accepted 18 November 2002)
Abstract
A comparison of power and accuracy of estimation of position and QTL
effects of three multitrait methods and one single trait method for
QTL detection was carried out on simulated data, taking into account
the mixture of full and half-sib families. One multitrait method was
based on a multivariate function as the penetrance function (MV). The
two other multitrait methods were based on univariate analysis of
linear combination(s) (LC) of the traits. One was obtained by a
principal component analysis (PCA) performed on the phenotypic
data. The second was based on a discriminate analysis (DA). It
calculates a LC of the traits at each position, maximising the ratio
between the genetic and the residual variabilities due to the putative
QTL. Due to its number of parameters, MV was less powerful and
accurate than the other methods. In general, DA better detected QTL,
but it had lower accuracy for the QTL effect estimation when the
detection power was low, due to higher bias than the other methods.
In this case, PCA was better. Otherwise, PCA was slightly less
powerful and accurate than DA. Compared to the single trait method,
power can be improved by 30% to 100% with multitrait methods.
Key words: multitrait / QTL / sib families / simulations
Correspondence and reprints: Hélène Gilbert
e-mail: helene.gilbert@dga.jouy.inra.fr
© INRA, EDP Sciences 2003