Core 2: Computational Core

计算共享研究核心 项目总结： 该中心将通过使用全基因组分析肿瘤的基因类型来剖析肿瘤的克隆异质性 测序、整个外显子组测序、RNA测序和单细胞RNA测序； 开发用于分析它们的基因和表型的软件。因为这两个科学项目都将 需要重叠的数据集和软件，统一它们的管理将提高效率并实现 更强的实施实施最佳实践的框架的能力。因此，我们将创建一个计算性 共享研究核心，通过管理存储、分析和 数据的传播。它将以一种可重现、安全并保护患者隐私的方式完成这项工作。它 还将开发、存档和传播基于贝叶斯统计的新型计算工具， 数学和计算机科学。 在我们开发这个核心时，我们同意了以下原则，这些原则将指导它的缺失。1)诚信， 数据的安全性和保密性是最重要的。2)确保研究的重现性需要积极的 在研究过程的所有步骤中都做出了努力。3)前处理和标准化分析的集中化可以 加快研究。4)以符合或符合以下方式的方式公开传播数据和代码 超过社会标准是推动研究进步的必要手段。这些值编码为 我们已经确定的五个目标和操作程序。 核心的具体目标是：1)数据管理、存储和分发。我们将维护和 分发由岩心和项目产生的原始和经处理的基因组数据。2)数据预处理。 我们将标准化检查原始数据(DNA-Seq，RNA-Seq， 和单细胞RNA-Seq)转化为有意义的措施，可在项目中进行分析。3)发展和 应用新的计算方法。我们的核心将开发新的工具，这些工具将应用于 项目。我们将开发基于贝叶斯的Sniper(结构网络集成PhEnotypeR) 将基因和通路水平的信息整合到表型中的结构网络建模方法 签名。然后我们可以使用癌症IPM，一个微分方程来模拟这些表型的进化 基于进化论的模型。最后，我们将应用和优化SuperSeeker，它询问肿瘤 亚克隆结构进化与系统发育。4)管道开发。为了处理和分析数据，我们 将使用我们开发的专家系统Betsy，它可以创建管道。这既加速了研究，也促进了 通过自动执行数据分析来提高重复性。此外，Betsy自动记录每个 进行了详细的分析。5)计算环境的标准化。我们将创建并分发 Docker Containers中的标准化计算环境。

COMPUTATIONAL SHARED RESEARCH CORE Project Summary: This Center will dissect the clonal heterogeneity of tumors by profiling their genotypes using whole genome sequencing, whole exome sequencing, RNA sequencing, and single cell RNA sequencing; and also by developing software for the analysis of their genotypes and phenotypes. Because both scientific projects will require overlapping sets of data and software, unifying their management will provide efficiencies and enable a greater ability to implement frameworks that enforce best practices. Therefore, we will create a Computational Shared Research Core to enhance synergy among projects by managing the storage, analysis, and dissemination of data. It will do this in a manner that is reproducible, secure, and maintains patient privacy. It will also develop, archive, and disseminate novel computational tools based on Bayesian statistics, mathematics, and computer science. As we developed this Core, we agreed upon the following principles that will guide its missing. 1) The integrity, security, and privacy of the data is paramount. 2) Ensuring the reproducibility of research requires an active effort at all steps of the research process. 3) Centralization of preprocessing and standardized analyses can accelerate research. And 4) public dissemination of data and code in a manner that is consistent with or exceeds community standards is necessary to promote the progress of research. These values are encoded in the five aims and operating procedures that we have established. The specific aims for the core are: 1) Data management, storage, and distribution. We will maintain and distribute the raw and processed genomic data generated by the cores and projects. 2) Data preprocessing. We will standardize the procedures to check the quality of and preprocess the raw data (DNA-Seq, RNA-Seq, and single cell RNA-Seq) into meaningful measures that can be analyzed in the projects. 3) Development and application of novel computational methods. Our Core will develop novel tools that will be applied to both projects. We will develop SNIPER (Structural Network Integrative PhEnotypeR), based on a Bayesian structural network modeling approach, to integrate gene- and pathway-level information into phenotypic signatures. We can then model the evolution of these phenotypes using Cancer IPM, a differential equation model based on evolutionary theory. Finally, we will apply and optimize SuperSeeker, which interrogates tumor subclone structure evolution and phylogeny. 4) Pipeline development. To process and analyze the data, we will use an expert system we developed, BETSY, that creates pipelines. This both accelerates research and promotes reproducibility by automating the analysis of the data. Further, BETSY automatically documents each analysis in detail. 5) Standardization of computational environment. We will create and distribute standardized computing environments in Docker containers.