As data collection costs fall and vast quantities of data are collected, data analysis time can become a bottleneck. For massively parallel analyses, cloud computing offers the short-term rental of ample processing power. Recent software innovations have reduced the effort needed to take advantage of cloud computing. To demonstrate, we replicate a voxel-wise examination of the genetic contributions to cortical development by age using evidence from 1748 MRI scans. Specifically, we employ off-the-shelf Kubernetes software that permits us to re-run our analyses using almost the same computer code as was published in the original article. Large, well funded institutions may continue to maintain their own computing clusters. However, the modest cost of renting and ease of utilizing cloud computing services makes unprecedented compute power available to all researchers, whether or not affiliated with a research institution. We expect this to spur innovation in the sophisticated modeling of large datasets.

中文翻译：

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用于 MRI 数据的 Voxel-Wise SEM 分析的云计算

随着数据收集成本的下降和大量数据的收集，数据分析时间可能成为瓶颈。对于大规模并行分析，云计算提供了充足处理能力的短期租用。最近的软件创新减少了利用云计算所需的工作量。为了证明这一点，我们使用来自 1748 年 MRI 扫描的证据复制了按年龄对皮质发育的遗传贡献的体素检查。具体来说，我们使用现成的 Kubernetes 软件，允许我们使用与原始文章中发布的几乎相同的计算机代码重新运行我们的分析。资金充足的大型机构可能会继续维护自己的计算集群。然而，云计算服务的适中租用成本和易用性使所有研究人员（无论是否隶属于研究机构）都可以获得前所未有的计算能力。我们预计这将刺激大型数据集复杂建模的创新。