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August 1997 Statistical issues in the search for genes affecting quantitative traits in experimental populations
R. W. Doerge, B. S. Weir, Z-B. Zeng
Statist. Sci. 12(3): 195-219 (August 1997). DOI: 10.1214/ss/1030037909


This article reviews key contributions in the area of statistics as applied to the use of molecular marker technology and quantitative genetics in the search for genes affecting quantitative traits responsible for specific diseases and economically important agronomic traits. Since an exhaustive literature review is not possible, the limited scope of this work is to encourage further statistical work in this vast field by first reviewing human and domestic species literature, and then concentrating on the statistical developments for experimental breeding populations. Substantial gains have been made over the years by both plant and animal breeders toward a long-term goal of locating genes affecting quantitative traits (quantitative trait loci, QTLs) for the eventual characterization and manipulation of these genes in order to develop improved agronomically important traits. Our main concern is that the care and expense that are required in generating both genetic marker data and quantitative trait data should be accompanied by equal care in the statistical analysis of the data. Through an example using an $F_2$ male genetic map of mouse chromosome 10, and quantitative trait values measured on weight gain, we implement much of the reviewed methodology for the purpose of detecting or locating a QTL having an effect on weight gain.


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R. W. Doerge. B. S. Weir. Z-B. Zeng. "Statistical issues in the search for genes affecting quantitative traits in experimental populations." Statist. Sci. 12 (3) 195 - 219, August 1997.


Published: August 1997
First available in Project Euclid: 22 August 2002

Digital Object Identifier: 10.1214/ss/1030037909

Keywords: interval mapping , interval testing , mixture distribution , multiple markers , QTL , single markers

Rights: Copyright © 1997 Institute of Mathematical Statistics


Vol.12 • No. 3 • August 1997
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