The Bioinformatics and Biostatistics Core will provide systems and bioinformatics computing infrastructure necessary for tracking, storing, integrating, and biostatistical analysis of the data generated in Research Projects 1-3. To accomplish this we will implement a custom database that supports the storage and organization of the immunological data, patient phenotypes, test results, 'omics data, SOPs, and other resources generated by this project. The system will be based on the Open Science Data Framework (OSDF), a scalable file system that will accommodate all information specific to this U19. We will also scale up our high-capacity data storage infrastructure to store, manage, and share these data. The proposed experiments in the Research Projects are complex, often involving clustered and longitudinal data, and correlated predictors and to appropriately assess the evidence in the data advanced statistical methods will be utilized. We will provide biostatistics expertise for design of experiments and ensure that they are unconfounded, optimally efficient, and appropriately powered. The Core biostatistics experts will help investigators summarize, analyze, interpret, and present the results. Finally, we will provide rapid data release and dissemination to the scientific community. Primary data such as sequence will be deposited in public archives such as the NCBI Short Read Archive (SRA), and the derived results such as genome assemblies, sequence variants, and expression data in NCBI Genbank, dbSNP, and the Gene Expression Omnibus (GEO). In addition to deposition of data to public archives, we will build a website for the scientific community to access all raw and custom data sets, analysis tools and standard operating procedure documents.

Public Health Relevance

The Bioinformatics and Biostatistics Core will provide systems and bioinformatics computing infrastructure necessary for tracking, storing, integrating, and biostatistical analysis of the data generated in Research Projects 1-3. To accomplish this we will implement a custom database that supports the storage and organization of the immunological data, patient phenotypes, test results, 'omics data, SOPs, and other resources generated by this project. The system will be based on the Open Science Data Framework (OSDF), a scalable file system that will accommodate all information specific to this U19. We will also scale up our high-capacity data storage infrastructure to store, manage, and share these data. The proposed experiments in the Research Projects are complex, often involving clustered and longitudinal data, and correlated predictors and to appropriately assess the evidence in the data advanced statistical methods will be utilized. We will provide biostatistics expertise for design of experiments and ensure that they are unconfounded, optimally efficient, and appropriately powered. The Core biostatistics experts will help investigators summarize, analyze, interpret, and present the results. Finally, we will provide rapid data release and dissemination to the scientific community. Primary data such as sequence will be deposited in public archives such as the NCBI Short Read Archive (SRA), and the derived results such as genome assemblies, sequence variants, and expression data in NCBI Genbank, dbSNP, and the Gene Expression Omnibus (GEO). In addition to deposition of data to public archives, we will build a website for the scientific community to access all raw and custom data sets, analysis tools and standard operating procedure documents. This Bioinformatics and Biostatistical Core will provide the infrastructure for computational storage, as well as data processing, and data integration and statistical analysis required for this project. This core will be critical in understanding the interplay human immune response and the gut microbiota and the consequences of the initial S. Typhi-human intestinal mucosa interactions on innate immunity and gut physiology.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
5U19AI082655-07
Application #
8835020
Study Section
Special Emphasis Panel (ZAI1)
Project Start
Project End
Budget Start
2015-06-01
Budget End
2016-05-31
Support Year
7
Fiscal Year
2015
Total Cost
Indirect Cost
Name
University of Maryland Baltimore
Department
Type
DUNS #
188435911
City
Baltimore
State
MD
Country
United States
Zip Code
21201
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