Sam2bam：用于NGS数据预处理工具的高性能框架
Sam2bam: High-Performance Framework for NGS Data Preprocessing Tools
摘要：
本文介绍了一个高通量的软件工具框架，称为{ \it sam 2bam}，使用户能够显着加快下一代测序数据的预处理。sam 2bam在单节点多核大内存系统上特别高效。与事实上的标准工具相比，它可以将单节点系统上标记重复读取的数据预处理的运行时间减少156- 186倍。sam 2bam由并行软件组件组成，可以充分利用多个处理器、可用内存、高带宽存储和硬件压缩加速器（如果可用）。sam 2bam提供了从SAM到BAM的已知基因组文件格式之间的文件格式转换，作为基本功能。诸如分析、过滤和转换输入数据的附加特征由{ \it插件}工具提供，例如，重复标记，可以在运行时附加到sam 2bam。我们证明了sam 2bam可以将NGS数据预处理的运行时间从大约两个小时减少到大约一分钟，用于使用高达130 GB内存的16核单节点系统上的全外显子组数据集。sam 2bam可以将全基因组测序数据的运行时间从大约20小时减少到大约9分钟，使用高达711 GB的内存。
英文摘要：
This paper introduces a high-throughput software tool framework called {\it sam2bam} that enables users to significantly speedup pre-processing for next-generation sequencing data. The sam2bam is especially efficient on single-node multi-core large-memory systems. It can reduce the runtime of data pre-processing in marking duplicate reads on a single node system by 156-186x compared with de facto standard tools. The sam2bam consists of parallel software components that can fully utilize the multiple processors, available memory, high-bandwidth of storage, and hardware compression accelerators if available. The sam2bam provides file format conversion between well-known genome file formats, from SAM to BAM, as a basic feature. Additional features such as analyzing, filtering, and converting the input data are provided by {\it plug-in} tools, e.g., duplicate marking, which can be attached to sam2bam at runtime. We demonstrated that sam2bam could significantly reduce the runtime of NGS data pre-processing from about two hours to about one minute for a whole-exome data set on a 16-core single-node system using up to 130 GB of memory. The sam2bam could reduce the runtime for whole-genome sequencing data from about 20 hours to about nine minutes on the same system using up to 711 GB of memory.
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