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dc.contributor.authorCho, Kellyen_US
dc.contributor.authorDupuis, Joséeen_US
dc.date.accessioned2012-01-11T15:51:11Z
dc.date.available2012-01-11T15:51:11Z
dc.date.copyright2009en_US
dc.date.issued2009-8-10en_US
dc.identifier.citationCho, Kelly, Josée Dupuis. "Handling linkage disequilibrium in qualitative trait linkage analysis using dense SNPs: a two-step strategy" BMC Genetics 10:44. (2009)en_US
dc.identifier.issn1471-2156en_US
dc.identifier.urihttp://hdl.handle.net/2144/3068
dc.description.abstractBACKGROUND. In affected sibling pair linkage analysis, the presence of linkage disequilibrium (LD) has been shown to lead to overestimation of the number of alleles shared identity-by-descent (IBD) among sibling pairs when parents are ungenotyped. This inflation results in spurious evidence for linkage even when the markers and the disease locus are not linked. In our study, we first theoretically evaluate how inflation in IBD probabilities leads to overestimation of a nonparametric linkage (NPL) statistic under the assumption of linkage equilibrium. Next, we propose a two-step processing strategy in order to systematically evaluate approaches to handle LD. Based on the observed inflation of expected logarithm of the odds ratio (LOD) from our theoretical exploration, we implemented our proposed two-step processing strategy. Step 1 involves three techniques to filter a dense set of markers. In step 2, we use the selected subset of markers from step 1 and apply four different methods of handling LD among dense markers: 1) marker thinning (MT); 2) recursive elimination; 3) SNPLINK; and 4) LD modeling approach in MERLIN. We evaluate relative performance of each method through simulation. RESULTS. We observed LOD score inflation only when the parents were ungenotyped. For a given number of markers, all approaches evaluated for each type of LD threshold performed similarly; however, RE approach was the only one that eliminated the LOD score bias. Our simulation results indicate a reduction of approximately 75% to complete elimination of the LOD score inflation while maintaining the information content (IC) when setting a tolerable squared correlation coefficient LD threshold (r2) above 0.3 for or 2 SNPs per cM using MT. CONCLUSION. We have established a theoretical basis of how inflated IBD information among dense markers overestimates a NPL statistic. The two-step processing strategy serves as a useful framework to systematically evaluate relative performance of different methods to handle LD.en_US
dc.description.sponsorshipNational Center for Research Resources Shared Instrumentation grant (ISI0RR163736-01A1)en_US
dc.language.isoenen_US
dc.publisherBioMed Centralen_US
dc.rightsCopyright 2009 Cho and Dupuis; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/2.0en_US
dc.titleHandling Linkage Disequilibrium in Qualitative Trait Linkage Analysis Using Dense SNPs: A Two-Step Strategyen_US
dc.typearticleen_US
dc.identifier.doi10.1186/1471-2156-10-44en_US
dc.identifier.pubmedid19664279en_US
dc.identifier.pmcid2731784en_US


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Copyright 2009 Cho and Dupuis; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's license is described as Copyright 2009 Cho and Dupuis; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.