Abstract
A new method is presented for use in simulating samples of disease and normal chromosomes bearing multiple linked genetic markers under a neutral model of mutation, genetic drift, and recombination. The method accounts for the potential effects of investigator sampling bias by allowing for ascertainment of chromosomes according to disease status and of markers according to a pre-specified polymorphism cutoff level. The method was implemented in a computer program and applied to study the general effects of disease mutation age (or frequency), levels of marker polymorphism, and sample size, on pairwise LD between markers and a disease mutation. It is shown that the average pairwise LD between a marker and a disease mutation is lower for older, or more prevalent, disease mutations, as expected. The marker polymorphism cutoff level also has an important influence on LD. Potential applications of the method for predicting the power of genome-wide marker-disease association studies are discussed.
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Wang, Y., Rannala, B. (2004). Simulating a Coalescent Process with Recombination and Ascertainment. 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_7
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DOI: https://doi.org/10.1007/978-3-540-24719-7_7
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