Next-generation sequencing has made major strides in the past decade. Studies based on large sequencing data sets are growing in number, and public archives for raw sequencing data have been doubling in size every 18 months. Leveraging these data requires researchers to use large-scale computational resources. Cloud computing, a model whereby users rent computers and storage from large data centres, is a solution that is gaining traction in genomics research. Here, we describe how cloud computing is used in genomics for research and large-scale collaborations, and argue that its elasticity, reproducibility and privacy features make it ideally suited for the large-scale reanalysis of publicly available archived data, including privacy-protected data.

下一代测序在过去十年中取得了重大进展。基于大型测序数据集的研究数量不断增加，原始测序数据的公共档案的规模每 18 个月就会翻一番。利用这些数据需要研究人员使用大规模的计算资源。云计算是一种用户从大型数据中心租用计算机和存储的模式，是一种在基因组学研究中越来越受欢迎的解决方案。在这里，我们描述了云计算如何在基因组学中用于研究和大规模协作，并认为其弹性、可重复性和隐私特性使其非常适合对公开可用的存档数据（包括受隐私保护的数据）进行大规模重新分析。