在资源有限的情况下，为了分析严重急性呼吸综合征冠状病毒2型（SARS-CoV-2）的大量基因组数据，实施一种特定的云资源存在挑战。为克服这个问题，我们重新利用了最初用于癌症基因组研究的云平台（https://cgc.sbgenomics.com），以便将其用于SARS-CoV-2的研究，构建了适用于病毒和变体鉴定的云工作流程（COWID）。COWID是基于通用工作流程语言的工作流程，它发挥了测序技术在可靠的SARS-CoV-2鉴定中的全部潜力，并利用云计算实现了高效的并行处理。通过提供可扩展的鉴定和可靠的变异结果，COWID优于其他同类方法，并且没有假阳性结果。COWID通常在仅需花费0.01美元的情况下，每处理一份原始测序数据样本仅需5分钟。COWID的源代码公开可用（https://github.com/hendrick0403/COWID），并且可以在任何联网的计算机上访问。COWID旨在用户友好，不需要先前的编程知识即可使用。因此，COWID是一种可在疫情期间使用的高效工具。发表于牛津大学出版社，2023年。

Implementing a specific cloud resource to analyze extensive genomic data on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a challenge when resources are limited. To overcome this, we repurposed a cloud platform initially designed for use in research on cancer genomics (https://cgc.sbgenomics.com) to enable its use in research on SARS-CoV-2 to build Cloud Workflow for Viral and Variant Identification (COWID). COWID is a workflow based on the Common Workflow Language that realizes the full potential of sequencing technology for use in reliable SARS-CoV-2 identification and leverages cloud computing to achieve efficient parallelization. COWID outperformed other contemporary methods for identification by offering scalable identification and reliable variant findings with no false-positive results. COWID typically processed each sample of raw sequencing data within 5 min at a cost of only US$0.01. The COWID source code is publicly available (https://github.com/hendrick0403/COWID) and can be accessed on any computer with Internet access. COWID is designed to be user-friendly; it can be implemented without prior programming knowledge. Therefore, COWID is a time-efficient tool that can be used during a pandemic.Published by Oxford University Press 2023.