Supplement: Enhancing Community Contributions to Bioconductor With Build System Containerization and a GPU for Testing

项目总结/摘要 “Bioconductor：基因组学的开源，开放开发计算资源”是 本申请的父母补助金补充资金。Bioconductor是一个开源的，开放的 用于分析和理解基因组的软件和数据的开发生态系统- 规模实验该系统主要基于R语言，但具有广泛的 互操作性能力，并结合了在许多其他 语言生物导体资源被要求在科学和工业场所， 从BioConductor的云分发系统流出的流量约为1 TB， 软件和数据。该系统为基因组表示提供基础设施， 变异体、基因组序列和基因模型的表示 生物体，用于许多阵列和测序平台的分析软件，以及注释和 实验档案，每天检查所有的一致性和可移植性。这一要求 用于补充资金，解决了构建和分发的工程要求 系统，它已经有了十多年的现有结构，并增加了对图形化的支持。 构建和测试系统中的处理单元。我们的计划包括集装箱化的工作， 升级建立和检查系统，改进记录方法 生态系统建设过程中的资源使用和不利事件。实质上，拟议的 这项工作将使Bioconductor项目更全面地接受“基础设施即代码” 纪律，以简化响应吞吐量要求的重新部署和重新缩放，并 改进系统问题自动发现和报告。因为， 基因组数据科学界在复杂性方面不断多样化， 生成的数据量以及使用的硬件平台数量也是如此。 由于工作量不断增加，拟议的工作无法在初步供资计划下完成。

PROJECT SUMMARY/ABSTRACT "Bioconductor: An Open-Source, Open-Development Computing Resource for Genomics" is the parent grant of this application for supplemental funds. Bioconductor is an open source, open development ecosystem of software and data for the analysis and comprehension of genome- scale experiments. The system is primarily rooted in the R language but has extensive interoperability capabilities and incorporates tools developed in numerous other languages. Bioconductor resources are requested at scientific and industrial sites throughout the world, with an outflow from Bioonductor's cloud distribution systems of approximately 1TB of software and data per day. The system provides infrastructure for genome representation and representation of variants, genomic sequences and gene models for numerous model organisms, analytical software for many array and sequencing platforms, and annotation and experiment archives, all checked for consistency and portability on a daily basis. This request for supplemental funds addresses engineering requirements of the build and distribution system, which has had its present structure for over ten years, and adds support for graphical processing units in the build and test system. Our plan includes work on containerization and upscaling of the build and check system, and enhancement of the methods of recording resource use and adverse events in ecosystem build processes. In essence, the proposed work will allow the Bioconductor project to more fully embrace an "Infrastructure as Code" discipline to simplify redeployment and rescaling in response to throughput requirements, and to improve automatic discovery and reporting of system problems. Because the requirements of the genomic data science community are continually diversifying in terms of complexity and volume of data being generated, and the number of hardware platforms in use is likewise growing, the work proposed cannot be accomplished under the initial funding plan.