JSM 2005 Online Program

Abstract #304557

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	482
Type:	Contributed
Date/Time:	Thursday, August 11, 2005 : 8:30 AM to 10:20 AM
Sponsor:	Biometrics Section
Abstract - #304557
Title:	Don't Use the Bootstrap for QTL Mapping
Author(s):	Ani Manichaikul*+ and Karl W. Broman
Companies:	Johns Hopkins University and Johns Hopkins University
Address:	615 N Wolfe St, Baltimore, MD, 21205, United States
Keywords:	bootstrap ; confidence interval ; genetics ; linkage mapping ; QTL
Abstract:	The aim of many genetic studies is to locate the genomic regions (called quantitative trait loci, QTLs) that contribute to variation in a quantitative trait (such as time-to-death following bacterial infection). Confidence intervals (CIs) for the locations of QTLs are particularly important for the design of further experiments to identify the gene or genes responsible for the effect. While likelihood support intervals are the most widely used method to obtain CIs for QTL location, use of the nonparametric bootstrap also has been recommended. Through extensive computer simulation, we show that bootstrap confidence intervals are poorly behaved ,and so should not be used in this context. Likelihood support intervals, on the other hand, behave appropriately. The profile likelihood (or LOD curve) for QTL location has a tendency to peak at genetic markers, and so the distribution of the maximum likelihood estimate (MLE) of QTL location has the unusual feature of point masses at genetic markers. This is the primary cause of the poor behavior of the bootstrap.

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