Originally published as Genetics Published Articles Ahead of Print on June 18, 2006.

Genetics, Vol. 173, 2371-2381, August 2006, Copyright © 2006
doi:10.1534/genetics.105.052506

Relaxed Significance Criteria for Linkage Analysis

Lin Chen and John D. Storey¹

Department of Biostatistics, University of Washington, Seattle, Washington 98195

¹ Corresponding author: Department of Biostatistics, University of Washington, Seattle, WA 98195.
E-mail: jstorey{at}u.washington.edu

Linkage analysis involves performing significance tests at many loci located throughout the genome. Traditional criteria for declaring a linkage statistically significant have been formulated with the goal of controlling the rate at which any single false positive occurs, called the genomewise error rate (GWER). As complex traits have become the focus of linkage analysis, it is increasingly common to expect that a number of loci are truly linked to the trait. This is especially true in mapping quantitative trait loci (QTL), where sometimes dozens of QTL may exist. Therefore, alternatives to the strict goal of preventing any single false positive have recently been explored, such as the false discovery rate (FDR) criterion. Here, we characterize some of the challenges that arise when defining relaxed significance criteria that allow for at least one false positive linkage to occur. In particular, we show that the FDR suffers from several problems when applied to linkage analysis of a single trait. We therefore conclude that the general applicability of FDR for declaring significant linkages in the analysis of a single trait is dubious. Instead, we propose a significance criterion that is more relaxed than the traditional GWER, but does not appear to suffer from the problems of the FDR. A generalized version of the GWER is proposed, called GWER_k, that allows one to provide a more liberal balance between true positives and false positives at no additional cost in computation or assumptions.

This article has been cited by other articles:

				A. O. Bergland, A. Genissel, S. V. Nuzhdin, and M. Tatar Quantitative Trait Loci Affecting Phenotypic Plasticity and the Allometric Relationship of Ovariole Number and Thorax Length in Drosophila melanogaster Genetics, September 1, 2008; 180(1): 567 - 582. [Abstract] [Full Text] [PDF]

				R. Higdon, G. van Belle, and E. Kolker A note on the false discovery rate and inconsistent comparisons between experiments Bioinformatics, May 15, 2008; 24(10): 1225 - 1228. [Abstract] [Full Text] [PDF]

				J. P. Kenney-Hunt, B. Wang, E. A. Norgard, G. Fawcett, D. Falk, L. S. Pletscher, J. P. Jarvis, C. Roseman, J. Wolf, and J. M. Cheverud Pleiotropic Patterns of Quantitative Trait Loci for 70 Murine Skeletal Traits Genetics, April 1, 2008; 178(4): 2275 - 2288. [Abstract] [Full Text] [PDF]

				J. M. Cheverud, R. Hager, C. Roseman, G. Fawcett, B. Wang, and J. B. Wolf Genomic imprinting effects on adult body composition in mice PNAS, March 18, 2008; 105(11): 4253 - 4258. [Abstract] [Full Text] [PDF]

				R. Hager, J. M. Cheverud, and J. B. Wolf Maternal Effects as the Cause of Parent-of-Origin Effects That Mimic Genomic Imprinting Genetics, March 1, 2008; 178(3): 1755 - 1762. [Abstract] [Full Text] [PDF]

				M. P. Boer, D. Wright, L. Feng, D. W. Podlich, L. Luo, M. Cooper, and F. A. van Eeuwijk A Mixed-Model Quantitative Trait Loci (QTL) Analysis for Multiple-Environment Trial Data Using Environmental Covariables for QTL-by-Environment Interactions, With an Example in Maize Genetics, November 1, 2007; 177(3): 1801 - 1813. [Abstract] [Full Text] [PDF]

International Access Link

Online ISSN: 1943-2361  Print ISSN: 0016-6731
Copyright 2009 by the Genetics Society of America
phone: 412-268-1812   fax: 412-268-1813   email: genetics-gsa{at}andrew.cmu.edu