Core C: Integrated Cancer and Aging Bioinformatics

项目摘要-核心C 要了解肝脏的衰老以及衰老在肝癌发展中的作用，需要收集、QC、 分析和集成大量高通量数据集。综合老龄化与癌症 生物信息学核心，即核心C，将通过为PPG成员提供三项关键服务来实现这一目标。 第一个关键服务将建立日常活动所需的基础设施。这将包括招聘 以及培训两名专门的博士级别的生物信息学分析师，他们将与PPG成员在所有 他们项目的各个方面，从数据管理和分析到定制工具和管道实施、数据 演示文稿和科学写作。除了关键人员外，核心还将获得所需的硬件 以存储回答特定问题所需的数据和生物信息管道。这项服务的最后一个方面是 与核心A合作，与PPG成员沟通并提供数据和分析。 第二项关键服务将是对PPG成员数据进行最先进的重点分析，这将 包括执行数据质量控制、生成已清理量化数据集、识别 改变，如肝脏衰老和肿瘤发展的核心基因或途径，并汇编分析 制作成可与PPG成员传播和分享的可视演示文稿。这其中的一个重要部分 第二个主要服务将是教育和培训PPG成员，使他们了解 分析并提供对共享服务器、教育资源和培训的访问，从而实现 PPG成员和学员执行他们自己的分析，并更深入地了解 他们的数据。 最后的关键服务将是将这些数据集整合到衰老和肿瘤的整体视图中 肝脏的发育。这将包括整合基因表达、蛋白质表达和代谢物 使用基于网络和统计的方法来测量丰度，目的是识别分子 机制随着年龄的增长而变化。此外，单细胞分析将被结合起来，不仅揭示基因的变化 表达，但也空间组织，T细胞受体多样性，以及染色质可及性的个别细胞 在肝脏里。最后，将使用机器学习方法将数据集组合成肿瘤预测模型 肿瘤的形成和预防性干预对肿瘤形成的可能影响。

PROJECT SUMMARY – CORE C Understanding aging in the liver and the role of aging in liver cancer development will require the collection, QC, analysis, and integration of a large collection of high-throughput datasets. The Integrative Aging and Cancer Bioinformatics Core, Core C, will achieve this goal by offering three key services for PPG members. The first key service will establish the infrastructure needed for day-to-day activities. This will include the hiring and training of two dedicated PhD-level bioinformatics analysts that will work closely with PPG members on all aspects of their projects from data curation and analysis to custom tool and pipeline implementation, data presentation, and scientific writing. In addition to key personnel, the core will also obtain the hardware needed to store data and bioinformatic pipelines required to answer specific questions. The final aspect of this service is to work with Core A to communicate and make available data and analyses to PPG members. The second key service will be to perform state-of-the-art focused analyses on PPG member data which will include performing data quality control, generation of cleaned quantified datasets, identifying features that are changing, such as genes or pathways central to liver aging and tumor development, and compiling the analyses into visual presentations that can be disseminated and shared with PPG members. An important part of this second key service will be to educate and train PPG members on the interpretation and limitations of the analyses and to provide access to shared servers and educational resources and trainings that would enable PPG members and trainees to perform some of their own analyses and become more intimately acquainted with their data. The final crucial service will be the integration of these datasets into a holistic view of aging and tumor development in the liver. This will include integrating gene expression, protein expression, and metabolite abundance measures using network-based and statistical approaches with the goal of identifying molecular mechanisms changing with age. Also, single-cell assays will be combined to reveal not only changes in gene expression, but also spatial organization, T-cell receptor diversity, and chromatin accessibility of individual cells in livers. Finally, machine learning approaches will be used to combine datasets into predictive models of tumor formation and possible effects of preventative interventions on tumor formation.