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PROJECT SUMMARY – DATA ANALYSIS CORE Reproducible and robust computational methods, coupled with rigorous statistical analyses, are critical for the success of the Center. We will ensure a unified approach to data analysis, integration, and management that leverages the existing infrastructure and the computational strengths of our investigators. Our data analysis effort will be divided into four tiers, with increasing level of data integration as we move up the tiers. Members of the Data Analysis Core (DAC) will be involved in all phases of project planning, from design to execution, to ensure that the data flow between the DAC and the OSPs and between our Center and other HuBMAP tissue mapping centers is well coordinated. Members of the DAC have extensive experience in algorithm development, genomics and imaging data analyses, large-scale data management, and coordination of data analytic efforts within multi-project centers. We propose the following five specific aims.1) To design and implement a pipeline for tier-one analyses using both public and in-house software tools. The pipeline will handle raw data generated using all assay types by the Center. 2) To develop and deploy computational methods for tier-two analyses. These methods will be used for the discovery and taxonomy of different cell types in the heart and inference of spatial distribution of cells and gene expression patterns in the heart. 3) To develop and deploy computational methods for tier-three analyses. These methods will be used for the discovery of transcriptional regulatory pathways contributing to spatial and temporal heterogeneity of the heart, and signaling pathways mediating interactions between different cell types in heart tissue microenvironment. 4) To construct integrated multidimensional heart atlases. Using cell-centric signatures and pathway models generated in Aims 2 and 3 as anchors, we will aggregate genomic and imaging data and metadata collected throughout the project. 5) To collaborate with the HuBMAP Integration, Visualization, and Integration collaboratory (HIVE) and other research centers of the Human Biomolecular Atlas Program (HuBMAP). We will contribute to benchmarking of software generated by HuBMAP investigators, development of common data formats, and improvement of interoperability of software tools.
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Administrative Core
  • 批准号:
    10904034
  • 项目类别:
  • 资助金额:
    $92.47万
  • 财政年份:
    2023
  • 负责人:
    Kai Tan
  • 依托单位:
Data Analysis Core
  • 批准号:
    10530969
  • 项目类别:
  • 资助金额:
    $64.28万
  • 财政年份:
    2022
  • 负责人:
    Kai Tan
  • 依托单位:
Data Analysis Unit
  • 批准号:
    10016229
  • 项目类别:
  • 资助金额:
    $41.95万
  • 财政年份:
    2018
  • 负责人:
    Kai Tan
  • 依托单位:
Tools for annotating mutations in the 3D cancer genome
国内基金
海外基金
基于ATAC-seq与DNA甲基化测序探究染色质可及性对莲两生态型地下茎适应性分化的作用机制
利用ATAC-seq联合RNA-seq分析TOP2A介导的HCC肿瘤细胞迁移侵 袭的机制研究
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    柳静
  • 依托单位:
面向图神经网络ATAC-seq模体识别的最小间隔单细胞聚类研究
  • 批准号:
    62302218
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    30.00万元
  • 批准年份:
    2023
  • 负责人:
    张双全
  • 依托单位:
基于ATAC-seq策略挖掘穿心莲基因组中调控穿心莲内酯合成的增强子