Fine-scale mapping of disease genes with multiple mutations via spatial clustering techniques
Fine-scale mapping of disease genes with multiple mutations via spatial clustering techniques
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DOI：
10.1086/380415
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发表时间：
2003-12-01
影响因子：
9.8
通讯作者：
Thomas, D
中科院分区：
文献类型：
--
作者：
Molitor, J;Marjoram, P;Thomas, D
我们提出了一种基于风险将单倍型放入簇来执行精细定位的方法。每一簇都有一个单倍型“中心”。集群分配是根据单倍型中心定义的，每个单倍型被分配给具有“最近”中心的集群。两个单倍型的接近程度由相似性度量确定，该相似性度量测量特定簇的假定功能突变位置周围的共享片段的长度。我们的方法允许丢失标记信息，但仍然可以估计完整单倍型的风险，而不需要求助于一次一个标记的分析。通过在单倍型空间上采样来消除单倍型分析中可能出现的维度问题，从而允许估计单倍型风险，而无需明确地将参数分配给要估计的每个单倍型。通过这种方式，我们能够处理任意大小的单倍型。此外，我们的聚类方法有可能允许我们检测多种功能突变的存在。
We present a method to perform fine mapping by placing haplotypes into clusters on the basis of risk. Each cluster has a haplotype "center." Cluster allocation is defined according to haplotype centers, with each haplotype assigned to the cluster with the "closest" center. The closeness of two haplotypes is determined by a similarity metric that measures the length of the shared segment around the location of a putative functional mutation for the particular cluster. Our method allows for missing marker information but still estimates the risks of complete haplotypes without resorting to a one-marker-at-a-time analysis. The dimensionality issues that can occur in haplotype analyses are removed by sampling over the haplotype space, allowing for estimation of haplotype risks without explicitly assigning a parameter to each haplotype to,be estimated. In this way, we are able to handle haplotypes of arbitrary size., Furthermore, our clustering approach has the potential to allow us to detect the presence of multiple functional mutations.