quickBAM: a parallelized BAM file access API for high-throughput sequence analysis informatics.
quickBAM: a parallelized BAM file access API for high-throughput sequence analysis informatics.
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DOI：
10.1093/bioinformatics/btad463
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发表时间：
2023-08-01
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--
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在时间紧迫的临床环境中，如精准医疗，需要尽快处理基因组数据，以便及时做出基于数据的治疗决策。虽然测序通量在过去十年中急剧增加，但生物信息学分析通量却无法跟上计算机硬件改进的步伐，因此现在已成为主要瓶颈。今天的现代计算机硬件能够具有比当前基因组信息学算法通常可以利用的高得多的性能，因此为性能的显著改善提供了机会。从BAM文件中检索原始测序数据例如在几乎所有序列分析工具中是必要且耗时的步骤，然而用于BAM访问的现有编程库没有充分利用存储设备的并行输入/输出能力。为了刺激新一代更快的序列分析工具的发展，我们开发了quickBAM，这是一个软件库，通过利用目前广泛使用的商品存储硬件中的并行性来加速测序数据访问。我们证明了移植到quickBAM的分析软件始终优于其当前版本，在某些情况下，使用相同的存储解决方案，在3分钟内完成分析，而原始版本需要1.5小时。开源并可在https：//gitlab.com/yiq/quickbam/免费获得，我们设想quickBAM将实现新一代高性能信息学工具，如果它们当前被数据访问检查，则直接提高它们的性能，或者允许数据访问跟上算法和计算技术的进一步优化。
In time-critical clinical settings, such as precision medicine, genomic data needs to be processed as fast as possible to arrive at data-informed treatment decisions in a timely fashion. While sequencing throughput has dramatically increased over the past decade, bioinformatics analysis throughput has not been able to keep up with the pace of computer hardware improvement, and consequently has now turned into the primary bottleneck. Modern computer hardware today is capable of much higher performance than current genomic informatics algorithms can typically utilize, therefore presenting opportunities for significant improvement of performance. Accessing the raw sequencing data from BAM files, e.g. is a necessary and time-consuming step in nearly all sequence analysis tools, however existing programming libraries for BAM access do not take full advantage of the parallel input/output capabilities of storage devices. In an effort to stimulate the development of a new generation of faster sequence analysis tools, we developed quickBAM, a software library to accelerate sequencing data access by exploiting the parallelism in commodity storage hardware currently widely available. We demonstrate that analysis software ported to quickBAM consistently outperforms their current versions, in some cases finishing an analysis in under 3 min while the original version took 1.5 h, using the same storage solution. Open source and freely available at https://gitlab.com/yiq/quickbam/, we envision that quickBAM will enable a new generation of high-performance informatics tools, either directly boosting their performance if they are currently data-access bottlenecked, or allow data-access to keep up with further optimizations in algorithms and compute techniques.
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影响因子：
5.8
作者：
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通讯作者：
Salit M
DOI：
10.14694/edbk_174176
发表时间：
2017-01-01
期刊：
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影响因子：
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作者：
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通讯作者：
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影响因子：
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作者：
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影响因子：
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