Core D: Integrated Computational Analysis Core

综合预防性分析核心：项目总结/摘要 调查阿尔茨海默病等疾病相关变化如何与特定风险因素联系起来 (e.g.,年龄相关变化、蛋白质聚集、血管病变等）改变空间布局 大脑中细胞类型及其基因表达谱，我们需要建立高分辨率的大脑地图， 在有和没有病理的个体中在细胞水平上的组织。建立这些地图需要适当的 病理特征的表征，以及用于数据生成和 显像为此，综合计算分析核心将与空间多组学密切合作， 核心，生物标本核心，以及成像和基因组学数据分析的各个方面的四个项目。 这包括以下内容：1）初步分析，包括图像配准，分割和基因 表达定量，2）二级分析，包括交叉样品配准和细胞类型 使用多重蛋白质表达和全基因组转录组学数据进行分配，以及3）三级 分析，包括推导概括细胞类型关键方面的离散可测量属性， 基因表达和病理组成及空间分布。通过扩大和调整现有的 为了满足这些数据分析需求，该核心集中参与每个工作流的所有分析目标， 项目，并与Spatial Multiomics Core进行持续反馈，以优化数据 生成工作流。该核心的另一个目标是集成原始数据和处理后的数据，以及 空间属性模型，导入一个名为多维老龄化地图集的可查询交互式门户， 大脑病理学（MAAP-Brain）可视化工具。这个可公开访问的门户网站，沿着 通过这个整体U19提案的教育组成部分的工作流程，将提供大脑老化， AD科学界有一个接口，可以接触项目产生的大规模数据， 其他核心最终，我们的目标是让外部研究人员能够产生或 验证了他们自己关于细胞组成和排列变化与衰老相关的假设 和人类大脑病理学

INTEGRATED COMPUTATIONAL ANALYSIS CORE: PROJECT SUMMARY/ABSTRACT To investigate how disease relevant changes, such as Alzheimer’s disease, are linked to specific risk factors (e.g., age-related changes, protein aggregates, vascular pathologies, etc.) to alter the spatial arrangement of cell types in the brain and their gene expression profiles, we need to build high-resolution maps of brain tissue at the cellular level in individuals with and without pathology. Building these maps requires proper characterization of the pathological features, as well as a reproducible workflow for data generation and imaging. To this end, the Integrated Computational Analysis Core will work closely with the Spatial Multiomics Core, the Biospecimen Core, and the four Projects on all aspects of imaging and genomics data analysis. This includes the following: 1) Primary analysis, comprising image registration, segmentation, and gene expression quantification, 2) Secondary analysis, comprising cross-sample registration and cell type assignment using multiplexed protein expression and genome-wide transcriptomics data, and 3) Tertiary analysis, involving the derivation of discrete measurable attributes summarizing key aspects of cell type, gene expression, and pathological composition and distribution in space. By scaling up and adapting existing workflows to address these data analysis needs, this Core is centrally involved in all analysis aims of each Project, as well as being engaged in continuous feedback with the Spatial Multiomics Core to optimize data generation workflows. An additional goal of this core is to integrate the raw and processed data, as well as the spatial attribute models, into a queryable, interactive portal called the Multidimensional Atlas of Aging and Pathology in the Brain (MAAP-Brain) visualizer. This publicly accessible portal, along with dissemination of workflows through the educational component of this overall U19 proposal, will provide the brain aging and AD scientific community with an interface to engage with the large-scale data generated by the Projects and other Cores. Ultimately, we aim for this dissemination effort to allow external researchers to generate or validate their own hypotheses about changes in cellular composition and arrangement associated with aging and human brain pathology.