Meta-analysis of genetic-linkage analysis of quantitative-trait loci

Carol J. Etzel, Rudy Guerra

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

Meta-analysis is an important tool in linkage analysis. The pooling of results across primary linkage studies allows greater statistical power to detect quantitative-trait loci (QTLs) and more-precise estimation of their genetic effects and, hence, yields conclusions that are stronger relative to those of individual studies. Previous methods for the meta-analysis of linkage studies have been proposed, and, although some methods address the problem of between-study heterogeneity, most methods still require linkage analysis at the same marker or set of markers across studies, whereas others do not result in an estimate of genetic variance. In this study, we present a meta-analytic procedure to evaluate evidence from several studies that report Haseman-Elston statistics for linkage to a QTL at multiple, possibly distinct, markers on a chromosome. This technique accounts for between-study heterogeneity and estimates both the location of the QTL and the magnitude of the genetic effect more precisely than does an individual study. We also provide standard errors for the genetic effect and for the location (in cM) of the QTL, using a resampling method. The approach can be applied under other conditions, provided that the various studies use the same linkage statistic.

Original languageEnglish (US)
Pages (from-to)56-65
Number of pages10
JournalAmerican journal of human genetics
Volume71
Issue number1
DOIs
StatePublished - 2002

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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