The goal of the proposed program is to obtain in-depth profiles of how human innate and adaptive immune cells function in response to viral pathogens in tissues and to understand how the circulating responses relate to those in tissues. Using CMV as a model of infection, we aim to identify signatures for tissue-specific control of human immune responses for promoting in situ protective immunity in vaccines and immunotherapies. These efforts will generate thousands of data files representing the results of a diverse collection of assays. The Data Management and Analysis Core (DMAC) will be responsible for aggregating, annotating, organizing, analyzing, and disseminating this data. In that role the Core will serve as a centralized resource to support the shared data management and analysis needs of the Center, offering access to expertise and IT infrastructure that would be impractical to replicate in the context of individual projects. Specifically, the DMAC will: Coordinate data curation, storage, and sharing: Data files will have to be accompanied by appropriate clinical and experimental annotations to support both the program?s own analysis needs as well as requirements for submission to public NIH repositories. The DMAC will coordinate the collection and curation of this information in collaboration with the relevant projects and cores and will provide access to authenticated, network- accessible storage infrastructure for securely storing and sharing data files among investigators. Provide data analysis expertise: The DMAC will provide projects with analytical expertise to guide the execution of computational investigations. Where possible analysis tasks will be automated and standardized by leveraging (and adapting, as needed) validated computational pipelines developed to support the operation of well-established shared resources at the Columbia University Medical Center (CUMC). The Core will further utilize and enhance novel methodologies for the analysis of single-cell data and for the systems-level delineation of the regulatory programs that preside over cell-state transitions in T cells, dendritic cells, and macrophages. Facilitate access to high performance computing infrastructure: Through the Core investigators will have access to sophisticated IT infrastructure designed specifically to support the needs of biomedical research at the CUMC, including fast, network-accessible disk storage and a powerful computational cluster that is among the most advanced in the nation dedicated to biomedical research. Coordinate data dissemination: A key goal of the HIPC program is the timely dissemination of the data generated by all awardees to the research community. The process requires the compilation of comprehensive documentation to ensure that the data released are interpretable. The DMAC will be responsible for preparing all necessary data submissions, interfacing with repository personnel and ensuring that submission packages are fully annotated, per repository requirements.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
1U19AI128949-01
Application #
9248634
Study Section
Special Emphasis Panel (ZAI1)
Project Start
Project End
Budget Start
2017-01-01
Budget End
2017-12-31
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Columbia University (N.Y.)
Department
Type
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032
Kumar, Brahma V; Connors, Thomas J; Farber, Donna L (2018) Human T Cell Development, Localization, and Function throughout Life. Immunity 48:202-213
Wroblewska, Aleksandra; Dhainaut, Maxime; Ben-Zvi, Benjamin et al. (2018) Protein Barcodes Enable High-Dimensional Single-Cell CRISPR Screens. Cell 175:1141-1155.e16
Miron, Michelle; Kumar, Brahma V; Meng, Wenzhao et al. (2018) Human Lymph Nodes Maintain TCF-1hi Memory T Cells with High Functional Potential and Clonal Diversity throughout Life. J Immunol 201:2132-2140
Lavin, Yonit; Kobayashi, Soma; Leader, Andrew et al. (2017) Innate Immune Landscape in Early Lung Adenocarcinoma by Paired Single-Cell Analyses. Cell 169:750-765.e17
Granot, Tomer; Senda, Takashi; Carpenter, Dustin J et al. (2017) Dendritic Cells Display Subset and Tissue-Specific Maturation Dynamics over Human Life. Immunity 46:504-515
Hectors, Stefanie J; Wagner, Mathilde; Bane, Octavia et al. (2017) Quantification of hepatocellular carcinoma heterogeneity with multiparametric magnetic resonance imaging. Sci Rep 7:2452