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This article is part of the supplement: Genetic Analysis Workshop 17: Unraveling Human Exome Data

Open Access Proceedings

Linkage analysis merging replicate phenotypes: an application to three quantitative phenotypes in two African samples

Anthony L Hinrichs1*, Robert C Culverhouse23 and Brian K Suarez14

Author Affiliations

1 Department of Psychiatry, Washington University School of Medicine, 660 South Euclid Ave., Campus Box 8134, St. Louis, MO 63110, USA

2 Department of Medicine, Washington University School of Medicine, 660 South Euclid Ave., St. Louis, MO 63110, USA

3 Division of Biostatistics, Washington University School of Medicine, 660 South Euclid Ave., St. Louis, MO 63110, USA

4 Department of Genetics, Washington University School of Medicine, 660 South Euclid Ave., St. Louis, MO 63110, USA

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BMC Proceedings 2011, 5(Suppl 9):S81  doi:10.1186/1753-6561-5-S9-S81

Published: 29 November 2011

Abstract

We report two approaches for linkage analysis of data consisting of replicate phenotypes. The first approach is specifically designed for the unusual (in human data) replicate structure of the Genetic Analysis Workshop 17 pedigree data. The second approach consists of a standard linkage analysis that, although not specifically tailored to data consisting of replicate genotypes, was envisioned as providing a sounding board against which our novel approach could be assessed. Both approaches are applied to the analysis of three quantitative phenotypes (Q1, Q2, and Q4) in two sets of African families. All analyses were carried out blind to the generating model (i.e., the “answers”). Using both methods, we found numerous significant linkage signals for Q1, although population colocalization was absent for most of these signals. The linkage analysis of Q2 and Q4 failed to reveal any strong linkage signals.