序列普查方法的覆盖统计
Coverage statistics for sequence census methods
摘要：
背景：我们研究基因组测序实验中片段覆盖率的统计特性。在经典Lander-Waterman模型的扩展中，我们考虑了碎片长度分布的影响。我们还介绍了覆盖函数的形状的概念，它可以被用来检测覆盖的畸变。这些问题背后的概率理论是必不可少的构建模型，目前的高通量测序实验，样品制备方案和测序技术的细节可以影响片段长度分布。结果如下：我们表明，无论片段长度分布和温和的假设下，片段的起始位点是泊松分布，在测序实验中产生的片段可以被视为从一个二维空间泊松过程。然后，我们研究了覆盖函数的跳跃骨架，并证明了诱导树是Galton-Watson树，其参数可以计算。结论：我们的研究结果扩展了鸟枪测序的标准分析，专注于在个别网站的覆盖率统计，并提供了一个空模型，用于检测偏离随机覆盖率在高通量序列普查为基础的实验。通过专注于片段，我们也被引导到一种新的方法，用于可视化应该是独立感兴趣的测序数据。
英文摘要：
Background: We study the statistical properties of fragment coverage in genome sequencing experiments. In an extension of the classic Lander-Waterman model, we consider the effect of the length distribution of fragments. We also introduce the notion of the shape of a coverage function, which can be used to detect abberations in coverage. The probability theory underlying these problems is essential for constructing models of current high-throughput sequencing experiments, where both sample preparation protocols and sequencing technology particulars can affect fragment length distributions. Results: We show that regardless of fragment length distribution and under the mild assumption that fragment start sites are Poisson distributed, the fragments produced in a sequencing experiment can be viewed as resulting from a two-dimensional spatial Poisson process. We then study the jump skeleton of the the coverage function, and show that the induced trees are Galton-Watson trees whose parameters can be computed. Conclusions: Our results extend standard analyses of shotgun sequencing that focus on coverage statistics at individual sites, and provide a null model for detecting deviations from random coverage in high-throughput sequence census based experiments. By focusing on fragments, we are also led to a new approach for visualizing sequencing data that should be of independent interest.
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