Core D

项目总结/摘要 目前迫切需要确定可以定义细胞状态和预测疾病的分子特征 C9 orf 72相关肌萎缩侧索硬化和额颞叶痴呆（c9 ALS/FTD）的进展 系统级。本P01申请建议研究c9 ALS/FTD病理机制， 新的治疗靶点，并确定用于诊断和治疗疾病的生物标志物。功能 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对其进行生物学解释。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学核心（核心D）将支持 研究人员在开发多组学数据分析和转录组学和 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 项目核心项目D还将继续协助项目1和项目3，进行功效分析， 如项目中所述。此外，Core D将推动数据的统一标准 通过公共数据字典和网络服务器进行报告，以实现 investigators.具体而言，核心D将与项目1-3以及核心B和C的调查人员合作， 制定一套适合数据统一和标准化的标准化描述符和参数 原始数据和处理数据的格式。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。到 为所有项目提供基础设施和协调，核心D将：1）设计和维护门户网站 在安全的网络服务器上; 2）与调查人员合作，制定一套标准化的描述符和参数 适用于数据协调;以及3）进行功效分析，以证明样本量的合理性，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 c9ALS/FTD。为了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。优先考虑网络和生物信息学验证转录组和蛋白质组 通过与外部已发布和未发布的数据集集成来发现。确定关键驱动因素的优先次序， c9 ALS和生物信息学验证的结果，核心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结果的方法 神经变性疾病病例和相应的小鼠模型;和2）定义c9 ALS的核心调节物 通过整合项目1-3中生成的多维数据。

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.