False-positive rates in two-point parametric linkage analysis

BMC Proceedings

Proceedings

Cheryl D Cropp¹  Claire L Simpson¹  Joan E Bailey-Wilson¹  Silke Szymczak² 

[1] Statistical Genetics Section, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, 333 Cassell Drive, Suite 1200, 21224, Baltimore, MD, USA;Statistical Genetics Section, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, 333 Cassell Drive, Suite 1200, 21224, Baltimore, MD, USA;Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel, Am Botanischen Garten 11, 24118, Kiel, Germany;

关键词: Linkage Analysis;    Minor Allele Frequency;    Causal Variant;    Whole Exome Sequencing;    Binary Trait;   

DOI  :  10.1186/1753-6561-8-S1-S110

来源: Springer

【 摘 要 】

Two-point linkage analyses of whole genome sequence data are a promising approach to identify rare variants that segregate with complex diseases in large pedigrees because, in theory, the causal variants have been genotyped. We used whole genome sequence data and simulated traits provided by Genetic Analysis Workshop 18 to evaluate the proportion of false-positive findings in a binary trait using classic two-point parametric linkage analysis. False-positive genome-wide significant log of odds (LOD) scores were identified in more than 80% of 50 replicates for a binary phenotype generated by dichotomizing a quantitative trait that was simulated with a polygenic component (that was not based on any of the provided whole genome sequence genotypes). In contrast, when the trait was truly nongenetic (created by randomly assigning affected-unaffected status), the number of false-positive results was well controlled. These results suggest that when using two-point linkage analyses on whole genome sequence data, one should carefully examine regions yielding significant two-point LOD scores with multipoint analysis and that a more stringent significance threshold may be needed.

【 授权许可】

Unknown   
© Szymczak et al.; licensee BioMed Central Ltd. 2014. This article is published under license to 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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.