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Multipoint linkage disequilibrium mapping approach: Incorporating evidence of linkage and linkage disequilibrium from unlinked region

Authors :
Fang-Chi Hsu
Kung Yee Liang
Terri H. Beaty
Source :
Genetic Epidemiology. 25:1-13
Publication Year :
2003
Publisher :
Wiley, 2003.

Abstract

Gene mapping for complex diseases is still a challenge in genetic studies. For family-based studies, the single-locus methods for detecting linkage and linkage disequilibrium (LD) one at a time may not capture the assumed interaction between multiple causal genes efficiently. We propose a multipoint LD approach for assessing the evidence of linkage and LD in a targeted chromosomal region by incorporating evidence from an unlinked region using the case-parent trio design. The paternal and maternal preferential transmission statistics defined in Liang et al. ([2001] Am. J. Hum. Genet. 68:937–950) are the primary statistics for this approach. Our generalized estimating equation (GEE) method builds on a model using the expected preferential transmission statistic from the targeted region conditional on this same statistic from the unlinked region. The major assumption is that there is no more than one trait locus in both the targeted region and unlinked region. The map position of an unobserved trait locus and its confidence interval can be calculated. Finally, we apply this approach to the African-American families drawn from the Collaborative Study on the Genetics of Asthma (CSGA). Previous analysis using this GEE approach developed by Liang et al. ([2001] Am. J. Hum. Genet. 68:937–950) suggested strong evidence of linkage and LD on chromosome 11, but only marginal evidence on chromosome 8. While conditioning on marker D11S937 on chromosome 11, a separate trait locus on chromosome 8 was estimated at , with a 95% confidence interval of (8.75, 14.59), and the test statistic shows significant evidence of linkage and LD (P-value=0.0198) in this region of chromosome 8. Genet Epidemiol 25:1–13, 2003. © 2003 Wiley-Liss, Inc.

Details

ISSN :
10982272 and 07410395
Volume :
25
Database :
OpenAIRE
Journal :
Genetic Epidemiology
Accession number :
edsair.doi.dedup.....a46930949ee9324853deeac3c32e0888
Full Text :
https://doi.org/10.1002/gepi.10241