Document Detail


Improving the power of sib pair quantitative trait loci detection by phenotype winsorization.
MedLine Citation:
PMID:  12037405     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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 omega and 1 - omega percentiles of the distribution were identified, and phenotypic values falling outside the boundaries of the omega and 1 - omega cutoff points were replaced by the omega and 1 - omega 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.
Authors:
José R Fernández; Carol Etzel; T Mark Beasley; Sanjay Shete; Christopher I Amos; David B Allison
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Publication Detail:
Type:  Evaluation Studies; Journal Article; Research Support, U.S. Gov't, P.H.S.    
Journal Detail:
Title:  Human heredity     Volume:  53     ISSN:  0001-5652     ISO Abbreviation:  Hum. Hered.     Publication Date:  2002  
Date Detail:
Created Date:  2002-05-30     Completed Date:  2002-10-22     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  0200525     Medline TA:  Hum Hered     Country:  Switzerland    
Other Details:
Languages:  eng     Pagination:  59-67     Citation Subset:  IM    
Copyright Information:
Copyright 2002 S. Karger AG, Basel
Affiliation:
Department of Nutrition Sciences, Division of Physiology and Metabolism, The University of Alabama at Birmingham, 35294-3360, USA. fernandj@shrp.uab.edu
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MeSH Terms
Descriptor/Qualifier:
Genetic Predisposition to Disease
Genetic Techniques
Models, Genetic
Phenotype
Quantitative Trait, Heritable*
Statistics as Topic*
Grant Support
ID/Acronym/Agency:
DK26687/DK/NIDDK NIH HHS; DK47256/DK/NIDDK NIH HHS; DK51716/DK/NIDDK NIH HHS; DK56336-01/DK/NIDDK NIH HHS; DK56366/DK/NIDDK NIH HHS; ES09912/ES/NIEHS NIH HHS; RR06009/RR/NCRR NIH HHS

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