Computational Tools for Analysis and Visualization of Quality Control Issues in Metabolomic Data

***摘要*** 在所有类型的组学研究中(例如，基因组、转录组、蛋白质组、代谢组学)，技术批次效应 对质量控制和重复性提出了根本性的挑战。出现严重错误的可能性包括 然而，由于一系列可能的平台、操作员、仪器和 可能导致批量(或趋势)影响的环境因素。因此，有必要进行例行监测。 并纠正代谢组学实验室和技术平台内部和之间的批次效应。 因此，我们建议在这里开发MetaBatch算法、计算工具和Web门户。 对于MetaBatch的开发，我们将利用我们在开发MBatch方面的经验，该工具后来成为 在癌症基因组图谱(TCGA)计划的所有33个项目中，数据的质量控制是不可或缺的。我们的 第一个目标是将成功的质量控制模式从TCGA转化为代谢组学，方法是定制和 扩展MBatch流水线，用于检测、定量、诊断、解释和校正批次和 趋势效应。第二个目标是开发和整合创新的代谢组学特定算法， 包括主要的可视化资源，如我们的交互式下一代集群热图。这个 第三个目标是将MetaBatch作为开源软件和基于云的形式分发给研究社区 和Galaxy版本。第四个目标是为MetaBatch与其他应用程序集成提供插件功能 代谢组学资源，主要包括代谢组学工作台(与Shankar博士合作 Subramaniam)和其他在共同基金代谢组学计划内发展的项目。我们的第五个目标是 积极推动MetaBatch并与其他联盟成员和代谢组学广泛互动 研究社区。在MD Anderson学院和学术发展部门的积极支持下，我们将 提供文档、教程、视频、演示和培训，以加快使用速度并征求反馈 关于限制、可能的改进，以及在实际工作流程中有用的其他模块。 我们为该项目带来了各种资产，包括：作为软件起点的MBatch资源 开发；生物信息学、生物统计学、软件工程、生物学和 临床医学；具有21年临床疾病分子图谱研究经验的PI (在联合体背景下)；在批量效果分析方面的国际领先地位；具有 制作高端、高度可视化的生物信息学包和网站的记录；一个由20名分析师组成的团队 可以调用其专业知识的人；广泛的计算资源，包括最强大的 世界上以学术为基础的机器；强有力的机构支持；以及与 MD Anderson的一流基础、翻译和临床研究人员，MD Anderson是最重要的癌症之一 在这个国家的中心。我们的底线使命将是帮助研究团体努力提高精确度 以及代谢组学的可重复性，以便科学地理解和减轻疾病。 好了！

* * * Abstract * * * In omic studies of all types (e.g., genomic, transcriptomic, proteomic, metabolomic), technical batch effects pose a fundamental challenge to quality control and reproducibility. The possibilities for serious error are greatly magnified in metabolomics, however, due to a range of possible platform, operator, instrument, and environmental factors that can cause batch (or trend) effects. Hence, there is a need for routine surveillance and correction of batch effects within and across metabolomics laboratories and technological platforms. Accordingly, we propose here to develop the MetaBatch algorithms, computational tool, and web portal. For development of MetaBatch, we will leverage our experience in developing MBatch, a tool that became indispensible for quality-control of data in all 33 projects of The Cancer Genome Atlas (TCGA) program. Our first aim is to translate the successful quality control model from TCGA to metabolomics by customizing and extending the MBatch pipeline for detection, quantitation, diagnosis, interpretation, and correction of batch and trend effects. The second aim is to develop and incorporate innovative metabolomics-specific algorithms, including major visualization resources such as our interactive Next-Generation Clustered Heat Maps. The third aim is to distribute MetaBatch to the research community as open-source software and in cloud-based and Galaxy versions. The fourth aim is to provide plug-in capability for integration of MetaBatch with other metabolomic resources, prominently including Metabolomics Workbench (in collaboration with Dr. Shankar Subramaniam) and others developed within the Common Fund Metabolomics Program. Our fifth aim is to promote MetaBatch actively and interact extensively with other Consortium members and the metabolomics research community. With active support from MD Anderson Faculty and Academic Development, we will provide documentation, tutorials, videos, demonstrations, and training to accelerate use and to solicit feedback on limitations, possible improvements, and additional modules that would be useful in real-world workflows. We bring a variety of assets to the project, including: the MBatch resource as a starting point for software development; multidisciplinary expertise in bioinformatics, biostatistics, software engineering, biology, and clinical medicine; PIs with a combined 21 years of experience in molecular profiling studies of clinical disease (in a consortial context); international leadership in batch effects analysis; a software engineering team with a track record of producing high-end, highly visual bioinformatics packages and websites; a team of 20 Analysts whose expertise can be called on; extensive computing resources, including one of the most powerful academically based machines in the world; strong institutional support; and close working relationships with first-class basic, translational, and clinical researchers throughout MD Anderson, one of the foremost cancer centers in the country. Our bottom-line mission will be to aid the research community's effort to improve rigor and reproducibility in metabolomics for scientific understanding and to alleviate disease. !