用于下一代测序数据快速校准的分布式系统。

Jaydeep K Srimani, Po-Yen Wu, John H Phan, May D Wang
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引用次数: 2

摘要

我们开发了一个可扩展的分布式计算系统,使用伯克利网络计算开放接口(BOINC)来快速准确地对齐下一代测序(NGS)数据。与传统的基因组微阵列技术相比,NGS技术由于其高灵敏度而成为一种有前途的基因表达分析平台。然而,尽管有这些好处,NGS数据集可能非常大,需要大量的计算资源来获得序列比对结果。此外,随着数据和对准算法变得越来越普遍,有必要研究多种对准参数对各种NGS系统的影响。我们通过(1)计算简单的时序结果来验证分布式软件系统,以显示使用多台计算机获得的加速,(2)使用模拟NGS数据优化校准参数,以及(3)使用最佳参数计算单个生物样品的NGS表达水平,并将这些表达水平与微阵列样品的表达水平进行比较。结果表明,分布式比对系统实现了近似线性的加速,能够正确地将序列数据分配给多个计算客户端,并收集来自多个计算客户端的比对结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A distributed system for fast alignment of next-generation sequencing data.

We developed a scalable distributed computing system using the Berkeley Open Interface for Network Computing (BOINC) to align next-generation sequencing (NGS) data quickly and accurately. NGS technology is emerging as a promising platform for gene expression analysis due to its high sensitivity compared to traditional genomic microarray technology. However, despite the benefits, NGS datasets can be prohibitively large, requiring significant computing resources to obtain sequence alignment results. Moreover, as the data and alignment algorithms become more prevalent, it will become necessary to examine the effect of the multitude of alignment parameters on various NGS systems. We validate the distributed software system by (1) computing simple timing results to show the speed-up gained by using multiple computers, (2) optimizing alignment parameters using simulated NGS data, and (3) computing NGS expression levels for a single biological sample using optimal parameters and comparing these expression levels to that of a microarray sample. Results indicate that the distributed alignment system achieves approximately a linear speed-up and correctly distributes sequence data to and gathers alignment results from multiple compute clients.

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