Inclusion of unaffected sibs increases power in model-free linkage analysis of a behavioral trait View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2005-12

AUTHORS

Sabine Plancoulaine, Alexandre Alcaïs, Yue Chen, Laurent Abel, France Gagnon

ABSTRACT

Study design strategies are of critical importance in the search for genes underlying complex diseases. Two important design choices in planning gene mapping studies are the analytic strategy to be used, which will have an impact on the type of data to be collected, and the choice of genetic markers. In the present paper, we used the simulated behavioral trait data provided in the Genetic Analysis Workshop 14 to: 1) investigate the usefulness of incorporating unaffected sibs in model-free linkage analysis and, 2) compare linkage results of genome scans using a 7-cM microsatellite map with a 3-cM single nucleotide polymorphisms map. To achieve these aims, we used the maximum-likelihood-binomial method with two different coding approaches. We defined the unaffected sibs as those totally free of phenotypes correlated to the disease. Without prior knowledge of the answers, we were able to correctly localize 2 out of 5 loci (LOD > 3) in a sample of 200 families that included the unaffected sibs but only one locus when based on an affected-only strategy, using either microsatellite or SNPs genome scan. LOD scores were considerably higher using the analytic strategy which incorporated the unaffected sibs. In conclusion, including unaffected sibs in model-free linkage analysis of complex binary traits is helpful, at least when complete parental data are available, whereas there are no striking advantages in using single nucleotide polymorphisms over microsatellite map at marker densities used in the current study. More... »

PAGES

s22

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Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1471-2156-6-s1-s22

DOI

http://dx.doi.org/10.1186/1471-2156-6-s1-s22

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1007259280

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/16451631


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