Thinking outside the cell: Leveraging HuBMAP data to build the human ECM atlas

NIH RePORTER · NIH · U01 · $150,000 · view on reporter.nih.gov ↗

Abstract

Abstract: NIH's Human BioMolecular Atlas Program (HuBMAP) is an ambitious endeavor striving to create a comprehensive, high-resolution atlas of the human body. It relies on collaborations among multiple research groups and the integration of diverse, complex datasets. Adhering to FAIR principles (Findability, Accessibility, Interoperability, and Reusability) is essential for enabling seamless sharing and reuse of valuable data among researchers and clinicians. This becomes increasingly important as the HuBMAP program expands, and more collaborations emerge from the project. In this proposal, we aim to enhance the data interoperability and reusability of existing mass spectrometry-based data within HuBMAP. Our proposed efforts serve as a natural extension of our current work in the parent U01 demo project (Thinking outside the cell: Leveraging HuBMAP data to build the human ECM atlas), which focuses on constructing the first extracellular matrix atlas for HuBMAP. The first aim plans to develop quality control tools and a unified proteomics data processing pipeline to examine the current landscape of HuBMAP data and facilitate comparisons across various experiments and tissue types. This effort will help us to better evaluate the data quality and identify key aspects for improvement. Our second aim concentrates on the cross-validation of diverse protein quantitation technologies currently utilized in HuBMAP. The extensive scope and depth of current HuBMAP datasets uniquely position us to compare various protein quantitation methods employed by different tissue mapping centers. This effort will help us to better understand the robustness, interchangeability, and suitability of these techniques. Collectively, our proposed research will significantly improve data interoperability and reusability within the HuBMAP project and provide guidelines for best practices in future data acquisition.

Key facts

NIH application ID
10816692
Project number
3U01HG012680-02S1
Recipient
UNIVERSITY OF ILLINOIS AT CHICAGO
Principal Investigator
Yu Gao
Activity code
U01
Funding institute
NIH
Fiscal year
2023
Award amount
$150,000
Award type
3
Project period
2022-07-01 → 2026-04-30