Halvade: scalable sequence analysis with MapReduce.
Halvade: scalable sequence analysis with MapReduce.
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DOI：
10.1093/bioinformatics/btv179
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发表时间：
2015-08-01
期刊：
影响因子：
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通讯作者：
Fostier J
中科院分区：
文献类型：
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作者：
Decap D;Reumers J;Herzeel C;Costanza P;Fostier J
动机：测序后DNA分析通常由读段作图和变异识别组成。特别是对于全基因组测序，这个计算步骤非常耗时，即使在多核机器上使用多线程也是如此。结果如下：我们提出了Halvade，一个框架，使排序管道并行执行的多节点和/或多核计算基础设施，以一种高效的方式。例如，已经根据GATK最佳实践建议实施了用于变异识别的DNA测序分析管道，支持全基因组和全外显子组测序。Halvade使用总共360个CPU核心的15节点计算机集群，在不到3小时的时间内以非常高的并行效率处理NA 12878数据集（人类，100 bp双端读段，50×覆盖率）。即使在单个多核机器上，与使用多线程运行单个工具相比，Halvade也获得了显著的加速。可用性和实现：Halvade是用Java编写的，使用Hadoop MapReduce 2.0 API。它支持广泛的Hadoop发行版，包括Cloudera和Amazon EMR。它的源代码可以在GPL许可下在http://bioinformatics.intec.ugent.be/halvade上获得。联系方式：jan.fostier@ intec.ugent.be补充信息：补充数据可在生物信息学在线获得。
Motivation: Post-sequencing DNA analysis typically consists of read mapping followed by variant calling. Especially for whole genome sequencing, this computational step is very time-consuming, even when using multithreading on a multi-core machine. Results: We present Halvade, a framework that enables sequencing pipelines to be executed in parallel on a multi-node and/or multi-core compute infrastructure in a highly efficient manner. As an example, a DNA sequencing analysis pipeline for variant calling has been implemented according to the GATK Best Practices recommendations, supporting both whole genome and whole exome sequencing. Using a 15-node computer cluster with 360 CPU cores in total, Halvade processes the NA12878 dataset (human, 100 bp paired-end reads, 50× coverage) in <3 h with very high parallel efficiency. Even on a single, multi-core machine, Halvade attains a significant speedup compared with running the individual tools with multithreading. Availability and implementation: Halvade is written in Java and uses the Hadoop MapReduce 2.0 API. It supports a wide range of distributions of Hadoop, including Cloudera and Amazon EMR. Its source is available at http://bioinformatics.intec.ugent.be/halvade under GPL license. Contact: jan.fostier@intec.ugent.be Supplementary information: Supplementary data are available at Bioinformatics online.