Data Analysis Core

数据分析核心

• 批准号: 10701912
• 负责人: GEORGE A KUCHEL
• 金额: $ 33.88万
• 依托单位: UNIVERSITY OF CONNECTICUT SCH OF MED/DNT
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10701912
• 关键词: Address; Affect; Age; Aging; Atlases; Benchmarking; Biological; Biological Markers; Cells; Charge; Classification; Clinical Data; Collaborations; Common Data Element; Communities; Complement; Complex; Computer Analysis; Computing Methodologies; Cytometry; Data; Data Analyses; Data Coordinating Center; Data Set; Development; Ensure; Evaluation; FAIR principles; Fatty acid glycerol esters; Genomics; Heterogeneity; Histopathology; Image; Individual; Kidney; Lead; Leadership; Linear Models; Maps; Methods; Modality; Output; Pancreas; Pathway Analysis; Patients; Pattern; Placenta; Policies; Population; Procedures; Process; Proteins; Proteomics; Quality Control; RLK5-associated protein phosphatase; Reproducibility; Research; Resolution; Sampling; Secure; Site; Standardization; Testing; Tissues; United States National Institutes of Health; analysis pipeline; computerized data processing; data integration; data management; data sharing; data sharing networks; deep learning; design; high dimensionality; imaging Segmentation; neural network; prospective; senescence; single nucleus RNA-sequencing; single-cell RNA sequencing; spatial integration; tissue mapping; transcriptome; transcriptomics

The KAPP-Sen Data Analysis core will curate, process, share, and analyze the rich expression and imaging datasets from the KAPP-Sen projects on kidney, fat, pancreas, and placenta tissues. Our team (led by Drs. Ucar and Chuang) has broad and extensive expertise in management, integration, and interpretation of complex high-resolution cellular datasets which will allow us to centralize the output of the core teams. The core will be in charge of processing of datasets, analyses and integration, including the construction of senescence maps. The Data Analysis Core will interact closely with the Biospecimen Core and the Biological Analysis Core to systematically receive, assess, organize, and share data from the contributing sites to ensure FAIR (findability, accessibility, interoperability, and reusability) principles throughout this project. Pipelines and analysis methods will be developed with a focus on reproducibility of workflows and robustness of results. Our team has broad and extensive expertise in management, integration, and interpretation of complex high-resolution cellular datasets which will allow us to centralize the output of the core teams. This centralization will maximize the value of the data generated for the KAPP-Sen, for the overall SenNet, and for the broader research community.

Kapp-Sen数据分析核心将管理、处理、共享和分析丰富的表达 来自Kapp-Sen项目的肾脏、脂肪、胰腺和胎盘组织的成像数据集。 我们的团队(由Ucar博士和庄博士领导)在管理方面拥有广泛而广泛的专业知识， 集成和解释复杂的高分辨率细胞数据集，这将使我们能够 集中核心团队的产出。 该核心将负责数据集的处理、分析和集成，包括 衰老图谱的构建。 数据分析核心将与Biosecimen核心和Bio 分析核心，用于系统地接收、评估、组织和共享来自贡献者的数据 站点确保公平(可发现性、可访问性、互操作性和可重用性)原则 贯穿整个项目。将开发管道和分析方法，重点是 工作流程的重复性和结果的稳健性。 我们的团队在管理、集成和解释方面拥有广泛而广泛的专业知识 复杂的高分辨率细胞数据集，将使我们能够集中核心的输出 团队。这种集中化将最大化为Kapp-Sen生成的数据的价值， 整个Sennet，以及更广泛的研究社区。