Physlr:下一代物理地图

Amirhossein Afshinfard, S. Jackman, J. Wong, Lauren Coombe, Justin Chu, Vladimir Nikolić, Gokce Dilek, Yaman Malkoç, R. Warren, I. Birol
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引用次数: 5

摘要

虽然传统的物理图谱有助于构建我们今天使用的大多数参考基因组,但生成图谱的成本高得令人望而却步,而且这项技术被放弃,取而代之的是全基因组鸟枪测序(WGS)。然而,使用WGS数据生成的基因组组装通常不太连续。我们介绍Physlr,这是一种利用一些WGS技术提供的远程信息来构建下一代物理地图的工具。这些图谱在基因组组装和分析中有许多潜在的应用,包括但不限于支架。在这项研究中,我们使用来自两个人的实验链接读取数据集,使用Physlr构建染色体规模的物理图谱(52 Mbp和70 Mbp的NGA50s)。我们还展示了这些物理图谱如何帮助构建使用各种测序技术和组装工具生成的人类基因组组装。在所有实验中,Physlr与最先进的连读架子工相比,显著提高了基线组件的邻接性。
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Physlr: Next-Generation Physical Maps
While conventional physical maps helped build most of the reference genomes we use today, generating the maps was prohibitively expensive, and the technology was abandoned in favor of whole-genome shotgun sequencing (WGS). However, genome assemblies generated using WGS data are often less contiguous. We introduce Physlr, a tool that leverages long-range information provided by some WGS technologies to construct next-generation physical maps. These maps have many potential applications in genome assembly and analysis, including, but not limited to, scaffolding. In this study, using experimental linked-read datasets from two humans, we used Physlr to construct chromosome-scale physical maps (NGA50s of 52 Mbp and 70 Mbp). We also demonstrated how these physical maps can help scaffold human genome assemblies generated using various sequencing technologies and assembly tools. Across all experiments, Physlr substantially improved the contiguity of baseline assemblies over state-of-the-art linked-read scaffolders.
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