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Record number 407211
Title Partial least square regression applied to the QTLMAS 2010 dataset
Author(s) Coster, A.; Calus, M.P.L.
Source In: Proceedings of the 14th European workshop on QTL mapping and marker assisted selection (QTL-MAS), Poznan, Poland, 17-18 May 2010. - - p. S7 - S7.
Event 14th QTL-MAS Workshop, 2010-05-17/2010-05-18
Department(s) Animal Breeding and Genetics
LR - Backoffice
Publication type Contribution in proceedings
Publication year 2010
Abstract Detection of genomic regions affecting traits is a goal in many genetic studies. Studies applying distinct methods for detection of these regions, called quantitative trait loci (QTL), have been described, ranging from single marker regression [1] to methods that enable to fit several markers simultaneously [2,3]. Simultaneously fitting all markers leads to more accurate detection of QTL compared to independent fitting of single markers in a regression model when there is linkage disequilibrium (LD) between the genomic regions that affect the trait but comes at the cost of increased computational requirements [2]. Partial least square regression (PLSR) is one method for simultaneously fitting multiple markers and was applied by Bjornstad et al. for detection of QTL [3]. An interesting characteristic of PLSR its straightforward application of to simultaneous analysis of data of multiple traits [3]. The objectives of this study were to use PLSR to search for QTL and to estimate breeding values in the dataset of the QTLMAS 2010 workshop
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