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Two novel quantitative trait linkage analysis statistics based on the posterior probability of linkage: application to the COGA families by Christopher W Bartlett; Veronica J Vieland is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

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## Background In this paper we apply two novel quantitative trait linkage statistics based on the posterior probability of linkage (PPL) to chromosome 4 from the GAW 14 COGA dataset. Our approaches are advantageous since they use the full likelihood, use full phenotypic information, do not assume normality at the population level or require population/sample parameter estimates; and like other forms of the PPL, they are specifically tailored to accumulate linkage evidence, either for or against linkage, across multiple sets of heterogeneous data. ## Results The first statistic uses all quantitative trait (QT) information from the pedigree (QT-posterior probability of linkage, PPL); we applied the QT-PPL to the trait ecb21 (resting electroencephalogram). The second statistic allows simultaneous incorporation of dichotomous trait data into the QT analysis via a threshold model (QTT-PPL); we applied the QTT-PPL to combined data on ecb21 and ALDX1. We obtained a QT-PPL of 96% at GABRB1 and a QT-PPL of 18% at FABP2 while the QTT-PPL was 4% and 2% at the same two loci, respectively. By comparison, the variance-components (VC) method, as implemented in SOLAR, yielded multipoint VC LOD sco

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Author

Christopher W Bartlett; Veronica J Vieland

Publisher

BioMed Central; Springer (Biomed Central Ltd.); London: BioMed Central, 2000-; Springer Science and Business Media LLC (ISSN 1471-2156)

Published

2005

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)