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PVT: An Efficient Computational Procedure to Speed up Next-generation Sequence Analysis

机译:PVT:加快下一代序列分析的有效计算程序

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摘要

BackgroundHigh-throughput Next-Generation Sequencing (NGS) techniques are advancing genomics and molecular biology research. This technology generates substantially large data which puts up a major challenge to the scientists for an efficient, cost and time effective solution to analyse such data. Further, for the different types of NGS data, there are certain common challenging steps involved in analysing those data. Spliced alignment is one such fundamental step in NGS data analysis which is extremely computational intensive as well as time consuming. There exists serious problem even with the most widely used spliced alignment tools. TopHat is one such widely used spliced alignment tools which although supports multithreading, does not efficiently utilize computational resources in terms of CPU utilization and memory. Here we have introduced PVT (Pipelined Version of TopHat) where we take up a modular approach by breaking TopHat’s serial execution into a pipeline of multiple stages, thereby increasing the degree of parallelization and computational resource utilization. Thus we address the discrepancies in TopHat so as to analyze large NGS data efficiently.
机译:背景技术高通量下一代测序(NGS)技术正在推动基因组学和分子生物学研究。这项技术会生成大量的数据,这给科学家们带来了巨大的挑战,他们需要一种高效,成本和时间有效的解决方案来分析此类数据。此外,对于不同类型的NGS数据,在分析这些数据时涉及某些共同的挑战性步骤。拼接对齐是NGS数据分析中的此类基本步骤之一,这是计算量巨大且耗时的。即使使用最广泛使用的拼接对准工具,也存在严重的问题。 TopHat是这样一种广泛使用的拼接对齐工具,尽管它支持多线程,但在CPU利用率和内存方面不能有效地利用计算资源。在这里,我们介绍了PVT(TopHat的管道版本),在其中我们采用了模块化方法,将TopHat的串行执行分解为多个阶段的管道,从而提高了并行化程度和计算资源的利用率。因此,我们解决了TopHat中的差异,以便有效地分析大型NGS数据。

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