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Joint linkage and association analysis for identification of potentially causal polymorphisms in GAW15 data
In a small chromosomal region, a number of polymorphisms may be both linked to and associated with a disease. Potentially directly associated causal loci may be distinguished from indirectly associated loci by determining which associations can explain the observed linkage signal. We apply methods f...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367610/ https://www.ncbi.nlm.nih.gov/pubmed/18466534 |
Sumario: | In a small chromosomal region, a number of polymorphisms may be both linked to and associated with a disease. Potentially directly associated causal loci may be distinguished from indirectly associated loci by determining which associations can explain the observed linkage signal. We apply methods for testing whether association with a particular polymorphism or haplotype can explain an observed linkage signal to the Genetic Analysis Workshop 15 simulated (Problem 3) data, to try to identify potentially causal polymorphisms. We compare the power of several methods for testing the null hypothesis that association with a particular variant can explain the observed linkage signal, and discuss scenarios under which the various methods may be advantageous. |
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