通过扫描统计识别染色体易位热点
Identification of cromosomal translocation hotspots via scan statistics
摘要：
在下一代测序数据的分析中，检测异常丰富的给定模式的基因组区域是一项重要的任务。最近对活化B淋巴细胞染色体易位的研究已经确定了经常易位为c-myc癌基因的区域。一个定量方法鉴定易位热点是这项研究的关键。在这里，我们通过使用一个简单的概率模型和扫描统计提供的框架来定义易位断点热点的数量和位置来改进这种分析。我们的方法的一个关键特征是，它提供了一个全球性的染色体范围内的显着性水平的聚类，而不是以前的方法基于局部标准。在生物信息学中，异常簇的检测是一个普遍存在的问题。我们希望我们的方法在其他实验方法（如ChIP-seq和4C-seq）的数据分析中有用。
英文摘要：
The detection of genomic regions unusually rich in a given pattern is an important undertaking in the analysis of next generation sequencing data. Recent studies of chromosomal translocations in activated B lymphocytes have identified regions that are frequently translocated to c-myc oncogene. A quantitative method for the identification of translocation hotspots was crucial to this study. Here we improve this analysis by using a simple probabilistic model and the framework provided by scan statistics to define the number and location of translocation breakpoint hotspots. A key feature of our method is that it provides a global chromosome-wide significance level to clustering, as opposed to previous methods based on local criteria. Whilst being motivated by a specific application, the detection of unusual clusters is a widespread problem in bioinformatics. We expect our method to be useful in the analysis of data from other experimental approaches such as of ChIP-seq and 4C-seq.
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