Developing new statistical approaches for finely spaced markers arising in the context of genome wide association studies

最近，大量的基因数据已经变得可用。可以使用这些数据来寻找患有某种疾病的人和没有患这种疾病的人之间的基因差异。这样做的目的是找到潜在致病原因的基因位置。一种方法是考虑一小段称为单倍型的DNA，并构建样本中每个单倍型如何通过进化事件从共同祖先产生的可信历史。我们的工作可能会带来一种改进的疾病图谱方法，以便为潜在的治疗提供信息。我们还想调查对人类胎儿发育有影响的基因异常，以及胎儿存活到出生的可能性，我们希望识别与此相关的以前未被怀疑的基因。人类同一段DNA可能有不同数量的副本。我们想要调查这种现象，并编写软件来寻找这种现象的例子。我们还想编写软件来评估拥有特定数量的此类切片是否会影响人们是否有可能患上某种特定的疾病。

Recently large volumes of genetic data have become available. It is possible to use these data to look for genetic differences between people with a certain disease and people without the disease. The aim of doing this is to find the genetic location of the potential cause of the disease. One way of doing this is to consider small segments of DNA called haplotypes and to construct plausible histories of how each haplotype in a sample arose from a common ancestor through evolutionary events. Our work could lead to an improved methodology for disease mapping in order to inform potential therapies.We also want to investigate genetic abnormalities which have an effect on human foetal development and the probability that a foetus will survive until it is born and we hope to identify previously unsuspected genes involved in this.Humans can have different numbers of copies of the same section of DNA. We want to investigate this phenomenon and write software to find instances of this. We also want to write software to assess whether having specific numbers of copies of such sections influences whether or not people are likely to have a particular disease.