Free Access
Genet. Sel. Evol.
Volume 38, Number 2, March-April 2006
Page(s) 167 - 182
Published online 24 February 2006
Genet. Sel. Evol. 38 (2006) 167-182
DOI: 10.1051/gse:2005034

The efficiency of mapping of quantitative trait loci using cofactor analysis in half-sib design

Goutam Sahanaa, Dirk Jan de Koningb, Bernt Guldbrandtsena, Peter Sørensena and Mogens Sandø Lunda

a  Department of Genetics and Biotechnology, Danish Institute of Agricultural Sciences, Research Centre Foulum, Tjele, 8830, Denmark
b  Division of Genetics and Genomics, Roslin Institute, Roslin, Midlothian, EH25 9PS, UK

(Received 30 August 2005; accepted 14 November 2005; published online 24 February 2006)

Abstract - This simulation study was designed to study the power and type I error rate in QTL mapping using cofactor analysis in half-sib designs. A number of scenarios were simulated with different power to identify QTL by varying family size, heritability, QTL effect and map density, and three threshold levels for cofactor were considered. Generally cofactor analysis did not increase the power of QTL mapping in a half-sib design, but increased the type I error rate. The exception was with small family size where the number of correctly identified QTL increased by 13% when heritability was high and 21% when heritability was low. However, in the same scenarios the number of false positives increased by 49% and 45% respectively. With a liberal threshold level of 10% for cofactor combined with a low heritability, the number of correctly identified QTL increased by 14% but there was a 41% increase in the number of false positives. Also, the power of QTL mapping did not increase with cofactor analysis in scenarios with unequal QTL effect, sparse marker density and large QTL effect (25% of the genetic variance), but the type I error rate tended to increase. A priori, cofactor analysis was expected to have higher power than individual chromosome analysis especially in experiments with lower power to detect QTL. Our study shows that cofactor analysis increased the number of false positives in all scenarios with low heritability and the increase was up to 50% in low power experiments and with lower thresholds for cofactors.

Key words: cofactor analysis / quantitative trait loci / power / false positives

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© INRA, EDP Sciences 2006