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Vol. 53, No. 2, 2002
Issue release date: May 2002
Section title: Original Paper
Hum Hered 2002;53:59–67
(DOI:10.1159/000057984)

Improving the Power of Sib Pair Quantitative Trait Loci Detection by Phenotype Winsorization

Fernàndez J.R. · Etzel C. · Beasley T.M. · Shete S. · Amos C.I. · Allison D.B.
aDepartment of Nutrition Sciences, Division of Physiology and Metabolism, bDepartment of Biostatistics, cClinical Nutrition Research Center, The University of Alabama at Birmingham, Birmingham, Ala., dUniversity of Texas, M.D. Anderson Cancer Center, Houston, Tex., USA

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Article / Publication Details

First-Page Preview
Abstract of Original Paper

Published online: 5/17/2002

Number of Print Pages: 9
Number of Figures: 2
Number of Tables: 6

ISSN: 0001-5652 (Print)
eISSN: 1423-0062 (Online)

For additional information: http://www.karger.com/HHE

Abstract

Objectives: In sib pair studies, quantitative trait loci (QTL) identification may be adversely affected by non-normality in the phenotypic distribution, particularly when subjects falling in the tails of the distribution bias the trait mean or variance. We evaluated the robustness and power of reducing the influence of subjects with extreme phenotypic values by Winsorizing non-normal distributions in three versions of Haseman-Elston regression-based methods of QTL linkage analysis. Methods: Data were simulated for normal and non-normal distributions. Phenotypic values that correspond to cutoff points at the ω and 1 – ω percentiles of the distribution were identified, and phenotypic values falling outside the boundaries of the ω and 1 – ω cutoff points were replaced by the ω and 1 – ω values, respectively. One million replications were performed for the three tests of linkage for Winsorized and non-Winsorized data. Results: Winsorization reduced conservatism in the tails of the empirical type I error rate for the vast majority of the tests of linkage, increased the power of QTL detection in non-normal data and created a slight negative bias in symmetrical phenotypic distributions. Conclusions: Winsorizing can improve the power of QTL detection with certain non-normal distributions but can also introduce bias into the estimate of the QTL effect.


  

Author Contacts

Dr. José R. Fernàndez
Division of Physiology and Metabolism
Department of Nutrition Sciences, University of Alabama at Birmingham
Webb 435 – 1530 3rd Avenue S, Birmingham, AL 35294-3360 (USA)
Tel. +1 205 934 2029, Fax +1 205 934 7050, E-Mail fernandj@shrp.uab.edu

  

Article Information

Received: Received: September 28, 2001
Revision received: December 18, 2001
Accepted: December 20, 2001
Number of Print Pages : 9
Number of Figures : 2, Number of Tables : 6, Number of References : 23

  

Publication Details

Human Heredity (International Journal of Human and Medical Genetics)
Founded 1950 as Acta Genetica et Statistica Medica by Gunnar Dahlberg; Continued by M. Hauge (1965–1983)

Vol. 53, No. 2, Year 2002 (Cover Date: Released May 2002)

Journal Editor: J. Ott, New York, N.Y.
ISSN: 0001–5652 (print), 1423–0062 (Online)

For additional information: http://www.karger.ch/journals/hhe


Article / Publication Details

First-Page Preview
Abstract of Original Paper

Published online: 5/17/2002

Number of Print Pages: 9
Number of Figures: 2
Number of Tables: 6

ISSN: 0001-5652 (Print)
eISSN: 1423-0062 (Online)

For additional information: http://www.karger.com/HHE


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