Linkage disequilibrium mapping and other applications

聚结过程是一种用来模拟种群谱系的随机过程，近年来在人类遗传学研究中得到了广泛的应用。我们开发了一种方法，该方法使用结合重组的凝聚过程（Larribe等人，2002年，Larribe 2004年）来估计影响疾病的基因突变的位置，例如进行遗传精细作图。在最近使用复合可能性策略提高了估计的稳定性之后（Larribe和Morgan， 2004），我们建议在复杂遗传疾病的背景下发展该方法，这是当今人类遗传学的主要兴趣。目标是建模不完全外显率和表型率的参数，并将它们作为估计中的干扰参数，以类似于我们处理未知谱系的方式。此外，我们希望发展该方法，使其能够同时估计两个突变的位置。最后，我们希望通过对疾病突变随时间的频率进行建模，直到观察到的序列具有共同的祖先，来纠正确定偏差（病例和对照的不平等抽样）。

The coalescent process, a stochastic process used to simulate population genealogies, has attracted much attention recently, mostly due to the numerous applications in human genetics research. We have developed a method, which uses the coalescent process with recombination (Larribe et al. 2002, Larribe 2004) to estimate the location of a genetic mutation influencing a disease, e.g. to do genetic fine mapping. After having recently improved the stability of the estimates using a composite likelihood strategy (Larribe and Morgan, 2004), we propose to develop the method in the context of complex genetic disease, which is of major interest in human genetics today. The goal is to model parameters of incomplete penetrance and phenocopy rate, and treat them as nuisance parameters in the estimation, in a similar way as we do with unknown genealogies. Morover, we would like to develop the method so that it is capable of estimating the position of two mutations simultaneously. Finally, we want to correct for the ascertainment biases (unequal sampling of cases and controls), by modelling the frequency of the disease mutation over time, from today back until the observed sequences have a common ancestor.