A fundamental challenge in clinical medicine and public health is to understand what accounts for the heterogeneity in infectious disease severity and spread through populations in order to maximize the prevention, diagnosis and treatment of each individual infection and protection of populations. Addressing this challenge will require integration of the complex dynamic interactions among hosts and pathogens. The Data Management and Analysis Core led by Dr. Steven Kleinstein will support the database, bioinformatics analysis and complex data analysis needs of Projects 1, 2 and 3. In addition, the core will collaborate with project investigators on experimental design and reporting, and provide a training environment for project personnel on software tools and principles of methods and interpretation of results. The core will also carry out metabolomics profiling experiments. Specifically, the Data Management and Analysis Core will: (1) Provide data management systems for clinical and research data. (2) Support sharing of data by submission to the NIAID ImmPort repository, the HIPC ImmuneSpace database and other relevant public repositories (e.g., SRA, dbGAP, Metabolomics Workbench). (3) Continue our efforts within HIPC towards the development and adoption of common data standards. (4) Provide biostatistical analysis support and consultation. (5) Carry out metabolomics profiling experiments and bioinformatics analysis to identify immune signatures associated with differential clinical responses. (6) Collaborate with Core C (Single Cell Phenotyping) to submit CyTOF, multispectral imaging cytometry (MuSIC), single-cell RNA-seq data into the data management system. (7) Collaborate with Core C (Single Cell Phenotyping) to integrate results from the analysis of CyTOF, multispectral imaging cytometry (MuSIC) and single-cell RNA-seq data into the systems-level analysis. (8) Integrate data across projects to detect common and unique signatures of infection
Each of the projects will be generating high-throughput data that present significant data management and analysis challenges. This core is critical to the success of the overall program to support the database, biostatistics, bioinformatics analysis, and complex data analysis needs of all three research projects and cores.
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