Linkage and heritability analysis of migraine symptom groupings: A comparison of three different clustering methods on twin data
Chen, Carla C.M., Mengersen, Kerrie L., Keith, Jonathan M., Martin, Nicholas G., & Nyholt, Dale R. (2009) Linkage and heritability analysis of migraine symptom groupings: A comparison of three different clustering methods on twin data. Human Genetics, 125(5-6), pp. 591-604.
Migraine is a painful disorder for which the etiology remains obscure. Diagnosis is largely based on International Headache Society criteria. However, no feature occurs in all patients who meet these criteria, and no single symptom is required for diagnosis. Consequently, this definition may not accurately reflect the phenotypic heterogeneity or genetic basis of the disorder. Such phenotypic uncertainty is typical for complex genetic disorders and has encouraged interest in multivariate statistical methods for classifying disease phenotypes. We applied three popular statistical phenotyping methods—latent class analysis, grade of membership and grade of membership “fuzzy” clustering (Fanny)—to migraine symptom data, and compared heritability and genome-wide linkage results obtained using each approach. Our results demonstrate that different methodologies produce different clustering structures and non-negligible differences in subsequent analyses. We therefore urge caution in the use of any single approach and suggest that multiple phenotyping methods be used.
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|Item Type:||Journal Article|
|Keywords:||Linkage, Heritability, Migraine, clustering methods|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology
Current > Institutes > Institute of Health and Biomedical Innovation
Past > Schools > Mathematical Sciences
|Copyright Owner:||Copyright 2009 Springer|
|Copyright Statement:||The original publication is available at SpringerLink http://www.springerlink.com|
|Deposited On:||29 Jan 2010 00:03|
|Last Modified:||20 May 2015 00:09|
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