Vol. 60, No. 1, 2005
Issue release date: 2005
Hum Hered 2005;60:36–42
Original Paper
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Empirical Bayes Method for Incorporating Data from Multiple Genome Scans

Beasley T.M.a · Wiener H.b · Zhang K.a · Bartolucci A.A.a · Amos C.I.e · Allison D.a, c
Departments of aBiostatistics, Section of Statistical Genetics, bEpidemiology, and cNutrition Sciences and Clinical Nutrition Research Center, The University of Alabama at Birmingham, Birmingham, Ala.; eDepartment of Epidemiology, University of Texas, M.D. Anderson Cancer Center, Houston, Tex., USA
email Corresponding Author

 goto top of outline Key Words

  • Empirical Bayes
  • Genome scan
  • Data sharing

 goto top of outline Abstract

Individual genome scans tend to have low power and can produce markedly biased estimates of QTL effects. Further, the confidence interval for their location is often prohibitively large for subsequent fine mapping and positional cloning. Given that a large number of genome scans have been conducted, not to mention the large number of variables and subsets tested, it is difficult to confidently rule out type 1 error as an explanation for significant effects even when there is apparent replication in a separate data set. We adapted Empirical Bayes (EB) methods [1] to analyze data from multiple genome scans simultaneously and alleviate each of these problems while still allowing for different QTL population effects across studies. We investigated the effects of using the EB method to include data from background studies to update the results of a single study of interest via simulation and demonstrated that it has a stable confidence level over a wide range of parameters defining the background studies and increased the power to detect linkage, even when some of the background studies were null or had QTL effect at other markers. This EB method for incorporating data from multiple studies into genome scan analyses seems promising.

Copyright © 2005 S. Karger AG, Basel

 goto top of outline References
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  12. Tang R: Fitting and evaluating certain two-level hierarchical models. PhD dissertation, Harvard University, Cambridge, MA, 2002.
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 goto top of outline Author Contacts

T. Mark Beasley, PhD
Department of Biostatistics, University of Alabama at Birmingham
1665 University Boulevard
Birmingham, AL 35294 (USA)
Tel. +1 205 975 4957, Fax +1 205 975 2540, E-Mail MBeasley@ms.soph.uab.edu

 goto top of outline Article Information

Received: February 28, 2005
Accepted: June 22, 2005
Published online: August 31, 2005
Number of Print Pages : 7
Number of Figures : 5, Number of Tables : 0, Number of References : 14

 goto top of outline Publication Details

Human Heredity (International Journal of Human and Medical Genetics)

Vol. 60, No. 1, Year 2005 (Cover Date: 2005)

Journal Editor: Devoto, M. (Wilmington, Del.)
ISSN: 0001–5652 (print), 1423–0062 (Online)

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

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