Abstract
There is currently great interest in the genetics community in identifying the genes that are involved in complex (multifactorial) diseases. One standard approach uses family-based ”linkage” methods to identify regions of the genome that harbor susceptibility genes, and then population-based ”linkage-disequilibrium” (LD) methods to search more narrowly for the culprit genes. Many of the important statistical issues involved in the first phase of this process, linkage mapping, have been addressed, but data analysis for LD-mapping remains extremely challenging. In this article we describe our work on developing a full statistical framework for LD mapping based on a population genetics model known as the coalescent.
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Zöllner, S., Pritchard, J.K. (2004). A Coalescent-Based Approach for Complex Disease Mapping. In: Istrail, S., Waterman, M., Clark, A. (eds) Computational Methods for SNPs and Haplotype Inference. RSNPsH 2002. Lecture Notes in Computer Science(), vol 2983. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24719-7_10
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DOI: https://doi.org/10.1007/978-3-540-24719-7_10
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