Fast and accurate mapping of Complete Genomics reads.
Fast and accurate mapping of Complete Genomics reads.
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快速准确地绘制完整基因组读数。
DOI：
10.1016/j.ymeth.2014.10.012
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Alkan,Can
中科院分区：
文献类型：
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作者：
Lee,Donghyuk;Hormozdiari,Farhad;Xin,Hongyi;Hach,Faraz;Mutlu,Onur;Alkan,Can
由于高通量测序（HTS）对大量人类基因组测序的能力，基因组学的许多最新进展和个性化医疗的期望成为可能。目前有几十种不同的测序技术，每种HTS平台都有不同的优势和偏见。这种多样性使得使用不同的技术来纠正缺点成为可能；但由于数据类型和误差模型的差异，也需要针对每个平台开发不同的算法。在分析用于重测序应用的HTS数据时，需要解决的第一个问题是读取映射阶段，在这个阶段，已经为最流行的HTS方法开发了许多工具，但对于Complete Genomics （CG）平台，仍然缺乏公开可用和开源的比对工具。不幸的是，基于Burrows-Wheeler的方法对于CG数据不实用，因为该方法生成的读取具有间隙性。在这里，我们为CG技术提供了一个基于种子-扩展范式的敏感读取映射器（sirFAST），可以快速将CG读取映射到参考基因组。我们使用模拟和公开可用的真实数据集来评估sirFAST的性能和准确性，显示出较高的精度和召回率。
Many recent advances in genomics and the expectations of personalized medicine are made possible thanks to power of high throughput sequencing (HTS) in sequencing large collections of human genomes. There are tens of different sequencing technologies currently available, and each HTS platform have different strengths and biases. This diversity both makes it possible to use different technologies to correct for shortcomings; but also requires to develop different algorithms for each platform due to the differences in data types and error models. The first problem to tackle in analyzing HTS data for resequencing applications is the read mapping stage, where many tools have been developed for the most popular HTS methods, but publicly available and open source aligners are still lacking for the Complete Genomics (CG) platform. Unfortunately, Burrows-Wheeler based methods are not practical for CG data due to the gapped nature of the reads generated by this method. Here we provide a sensitive read mapper (sirFAST) for the CG technology based on the seed-and-extend paradigm that can quickly map CG reads to a reference genome. We evaluate the performance and accuracy of sirFAST using both simulated and publicly available real data sets, showing high precision and recall rates.