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arXiv 1402.0640q-bio.GN
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使用基于压缩的距离测量的下一代测序数据的无比对比较

Alignment-free comparison of next-generation sequencing data using compression-based distance measures

Ngoc Hieu Tran, Xin Chen

发表信息：
BMC Research Notes, 2014
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摘要：

来自下一代测序（NGS）技术的大量短读段数据对基因组序列比较领域提出了新的挑战。由于短读段组装的挑战性问题，多序列比对方法几乎不适用于NGS数据。因此，需要开发无干扰的方法来比较短读段的NGS样品。最近，已经提出了新的基于$k$聚体的距离测量，例如{ \it CV树}、$d_{2}^{S}$、{ \it共系}来解决该问题。然而，这些距离在很大程度上取决于参数$k$，并且如何选择最佳的$k$并不简单，因为它可能取决于序列数据的不同方面。因此，在本文中，我们考虑一种替代的无参数方法：基于压缩的距离测量。这些措施在以前的研究中对长基因组序列表现出令人印象深刻的性能，但它们尚未在NGS短读段上进行测试。在这项研究中，我们进行了广泛的验证，并表明，基于压缩的距离是高度一致的那些距离从$k$ -mer为基础的方法，从基于压缩的方法，并从现有的基准文献。此外，由于这些措施是无参数的，不需要优化，他们仍然表现出一贯良好的多种类型的序列数据，不同种类的物种和分类水平。基于压缩的距离测量是无装配、无装配、无参数的，因此代表了用于比较长基因组序列和短读段的NGS样品的有用工具。

英文摘要：

Enormous volumes of short reads data from next-generation sequencing (NGS) technologies have posed new challenges to the area of genomic sequence comparison. The multiple sequence alignment approach is hardly applicable to NGS data due to the challenging problem of short read assembly. Thus alignment-free methods need to be developed for the comparison of NGS samples of short reads. Recently, new $k$-mer based distance measures such as {\it CVTree}, $d_{2}^{S}$, {\it co-phylog} have been proposed to address this problem. However, those distances depend considerably on the parameter $k$, and how to choose the optimal $k$ is not trivial since it may depend on different aspects of the sequence data. Hence, in this paper we consider an alternative parameter-free approach: compression-based distance measures. These measures have shown impressive performance on long genome sequences in previous studies, but they have not been tested on NGS short reads. In this study we perform extensive validation and show that the compression-based distances are highly consistent with those distances obtained from the $k$-mer based methods, from the alignment-based approach, and from existing benchmarks in the literature. Moreover, as these measures are parameter-free, no optimization is required and they still perform consistently well on multiple types of sequence data, for different kinds of species and taxonomy levels. The compression-based distance measures are assembly-free, alignment-free, parameter-free, and thus represent useful tools for the comparison of long genome sequences and NGS samples of short reads.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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