Data Analysis Core

数据分析核心

基本信息

批准号：
10673121
负责人：
Elana Judith Fertig
金额：
$ 22.09万
依托单位：
JOHNS HOPKINS UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-08-01 至 2026-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10673121
关键词：
Age Aging Atlases Biological Biological Assay Biological Markers Cataloging Cell Aging Cell Communication Cells Chromatin Collaborations Collection Communities Computer Analysis Computer software Computing Methodologies Data Data Analyses Data Set Disparate Environment FAIR principles Female Genetic Models Goals Heterogeneity Infrastructure Lead Longevity Maps Methods Modality Modeling Molecular Multiomic Data Mus Phenotype Process Regulation Reporter Reproducibility Research Personnel Resources Services Standardization System Technology Tissues Translating Visualization analysis pipeline computational pipelines data format data integration data management data resource data reuse data sharing data to knowledge genetic signature human data learning strategy machine learning classification male mouse genetics multiple omics novel programs senescence single cell analysis single cell technology single nucleus RNA-sequencing single-cell RNA sequencing spectrograph synergism tissue mapping transcriptome sequencing transcriptomics transfer learning

项目摘要

The Data Analysis Core (DAC) will centralize computational analysis for the JHU-Mayo-NIA Murine Senescence Mapping Program (JMN-MSMP) to generate integrated molecular and spatial maps of cellular senescence in aging murine tissues. The JMN-MSMP will generate data from bulk RNA sequencing, single cell RNA sequencing (scRNA-seq), chromatin accessibility sequencing (scATAC-seq), spatial transcriptomics, and multi-spectral imaging, among others. The DAC will provide essential expertise and services to translate this raw data into knowledge. More specifically the DAC will be responsible for the following tasks.The DAC will: 1) provide essential analysis pipelines, computational expertise, and data management services in support of the Biological Analysis Core (BAC); 2) incorporate state-of-the-art methods for analysis of data from cutting-edge technologies, as well as integration and visualization of unique data resources generated within the JMN- MSMP as these methods reach maturation; 3) lead the construction of the Atlas itself; and 4) coordinate analysis activities with the other SenNet Centers and the CODCC to standardize pipelines and contribute unique multi-omics and transfer learning expertise. The DAC will provide standardized and rigorous analysis pipelines optimized for the goals of SenNet, and use the pipelines to generate findable, accessible, interoperable, and reusable (FAIR) data.

数据分析核心（DAC）将集中用于Jhu-mayo-nia鼠的计算分析衰老映射程序（JMN-MSMP）生成细胞的集成分子和空间图衰老的鼠组织衰老。 JMN-MSMP将从大量RNA测序，单个单元格生成数据 RNA测序（SCRNA-SEQ），染色质可及性测序（SCATAC-SEQ），空间转录组学和多光谱成像等。 DAC将提供基本的专业知识和服务来翻译此事原始数据成知识。更具体地说，DAC将负责以下任务。DAC将：1）提供基本的分析管道，计算专业知识和数据管理服务，以支持生物分析核心（BAC）； 2）结合了最先进的方法，用于分析尖端的数据技术以及在JMN-中生成的独特数据资源的集成和可视化 MSMP随着这些方法成熟； 3）领导阿特拉斯本身的建设； 4）协调与其他Sennet中心和CODCC分析活动，以标准化管道并贡献独特的多媒体和转移学习专业知识。 DAC将提供标准化和严格的分析为Sennet的目标进行了优化的管道，并使用管道生成可发现的，可访问的，可互操作和可重复使用的（公平）数据。