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doi:10.1534/genetics.105.047431
A more recent version of this article appeared on December 1, 2005.
Originally published as Genetics Published Articles Ahead of Print on August 22, 2005.
REGULAR RESEARCH PAPERS |
Disentangling Linkage Disequilibrium and Linkage from Dense SNP Trio Data
Geraldine M Clarke 1* and Lon R Cardon 1
1 University of Oxford
* To whom correspondence should be addressed. E-mail: gclarke{at}well.ox.ac.uk.
Submitted on June 29, 2005
Revised on August 2, 2005
Accepted on 2 August 2005
Parent-offspring trios are widely collected for disease gene mapping studies and being extensively genotyped as part of the International HapMap Project. With dense maps of markers on trios, the effects of LD and linkage can be separated allowing estimation of recombination rates in a model-free setting. Here we define a model-free multipoint method based on dense sequence polymorphism data from parent-offspring trios to estimate inter-marker recombination rates. We use simulations to show that this method has up to 92% power to detect recombination hotspots of intensity 25 times background over a region of size 10kb typed at density 1 marker per 2.5kb and almost 100% power to detect large hotspots of intensity >125 times background over regions of size 10kb typed with just 1 marker per 5kb (
=0.05). We found strong agreement at megabase scales between estimates from our method applied to HapMap trio data and estimates from the genetic map. At finer scales, using Centre D'etude du Polymorphisme Humain (CEPH) pedigree data across a 10Mb region of chromosome 20, a comparison of population recombination rate estimates obtained from our method with estimates obtained using a coalescent based approximate-likelihood method implemented in PHASE 2.0 shows detection of the same coldspots and most hotspots: the Spearman rank correlation between the estimates from our method and those from PHASE is 0.58 (p< 2.2-16).
Key Words: Linkage, Linkage Disequilibrium, Recombination
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