Core D

项目摘要/摘要 迫切需要确定能够定义细胞状态和预测疾病的分子特征 C9orf72相关的肌萎缩侧索硬化症和额颞叶痴呆(C9ALS/FTD)的进展 一个系统级别。这个P01申请建议研究c9ALS/FTD的病理机制 新的治疗靶点和确定用于诊断和预测疾病的生物标记物。功能性 基因组学方法，如项目1-3中采用的方法，将产生数十万个数据点 需要复杂的分析方法来进行生物学解释。采用基于网络的 方法是一个自然的步骤，因为大多数生物系统都可以准确地建模和表示 使用这些方法。因此，生物信息学和生物统计核心(核心D)将支持 研究人员正在开发多组学数据分析和转录组数据集成的策略 在项目1-3中生成的蛋白质组数据，以及将其他最先进的数据分析应用于个人 项目。核心D还将继续协助项目1和项目3，通过执行电力分析来处理样本 建议项目中所述的尺寸。此外，核心D将促进数据的统一标准 通过通用数据字典和Web服务器进行报告，以实现 调查人员。具体而言，核心D将在项目1-3以及核心B和C中与调查人员合作，以 制定一套适用于数据协调和标准的标准化描述符和参数集 原始数据和已处理数据的格式。具体目标如下：具体目标1.提供 转录组学和蛋白质组学研究的标准化数据共享和分析框架。至 在所有项目之间提供基础设施和协调，核心D将：1)设计和维护网络门户 在安全的Web服务器上；2)与调查人员合作开发一组标准化的描述符和参数 适用于数据协调；以及3)执行功率分析，以证明样本大小并协助 具有混杂变量的临床信息的统计建模。具体目标2.构建多尺度 基因/蛋白质网络，并与单细胞转录组学相结合，以确定改变的核心网络 在C9ALS/FTD中。为支持所有项目的生物信息学分析，核心D将进行数据集成。 具体目标3.确定网络的优先顺序并从生物信息学的角度验证转录和蛋白质组 通过与外部已发布和未发布的数据集集成进行发现。确定关键驱动因素的优先顺序 C9ALS和生物信息学验证结果，Core D将：1)开发和实施生物信息学 使用包含人类的多个数据集验证项目主要发现的方法 神经退行性疾病病例和相应的小鼠模型；以及2)定义c9ALS的核心调节因子 通过整合项目1-3中产生的多维数据。

PROJECT SUMMARY/ABSTRACT There is a critical need to identify the molecular signatures that can define cell states and predict disease progression in C9orf72-associated amyotrophic lateral sclerosis and frontotemporal dementia (c9ALS/FTD) at a systems level. This P01 application proposes to investigate c9ALS/FTD pathomechanisms that can inform new therapeutic targets and identify biomarkers for diagnosing and prognosticating disease. Functional genomics approaches such as those taken in Projects 1-3 will generate hundreds of thousands of data points requiring sophisticated analytical methods for their biological interpretation. The adoption of network-based approaches has been a natural step as most biological systems can be accurately modeled and represented using these methods. The Bioinformatics and Biostatistics Core (Core D) will therefore support investigators in developing strategies for multi-omics data analysis and data integration of transcriptomic and proteomic data generated in Projects 1-3, and in applying additional state of the art data analytics to individual projects. Core D will also continue to assist Projects 1 and 3 by performing power analysis to address sample sizes as described in the proposed projects. In addition, Core D will promote uniform standards for data reporting through a common data dictionary and a web server to enable data exchange among the investigators. Specifically, Core D will work with investigators across Projects 1-3 and Cores B and C to develop a standardized set of descriptors and parameters appropriate for data harmonization and standard formats for raw and processed data. The Specific Aims are the following: Specific Aim 1. Provide a framework for standardized data-sharing and analyses of transcriptomics and proteomics studies. To provide infrastructure and harmonization among all projects, Core D will: 1) design and maintain a web-portal on a secure web server; 2) work with investigators to develop a standardized set of descriptors and parameters appropriate for data harmonization; and 3) perform power analysis to justify sample size and assist with statistical modeling of clinical information with confounding variables. Specific Aim 2. Construct multi-scale gene/protein networks and integrate with single-cell transcriptomics to identify core networks altered in c9ALS/FTD. To support bioinformatic analyses for all Projects, Core D will carry-out data integration. Specific Aim 3. Prioritize networks and bioinformatically validate the transcriptomic and proteomic discoveries by integrating with external published and unpublished datasets. To prioritize key drivers of c9ALS and bioinformatically validate the findings, Core D will: 1) develop and implement bioinformatic approaches to validate major findings of the Projects with multiple datasets encompassing human neurodegenerative disease cases and corresponding mouse models; and 2) define core regulators of c9ALS by integrating multi-dimensional data generated in Projects 1-3.