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Progress Reports: University of North Carolina-Chapel Hill: Data Management and Analysis Core (DMAC)

Superfund Research Program

Data Management and Analysis Core (DMAC)

Project Leader: Stanley Carlton Ahalt
Co-Investigators: Fei Zou, Julia E. Rager, Kimberly Joan Robasky, Haibo Zhou
Grant Number: P42ES031007
Funding Period: 2020-2025
View this project in the NIH Research Portfolio Online Reporting Tools (RePORT)

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Progress Reports

Year:   2020 

The Data Management and Analysis Core (DMAC) has drafted and continuously updated data management plan templates (DMTs). Each project has continued to build upon and update their individual DMTs as projects have started and made progress. They have launched internal mechanisms and associated Standard Operating Procedures through which projects can share data between each other and the DMAC. In relation to designing and launching the Data Sharing Warehouse to share data methods and results, they have launched internal mechanisms through which projects can share data using flexible formats. They have also identified platforms for more permanent data deposition. They have created a few R scripts and SAS programs for performing adequate sample size and power calculation. In addition, they developed an experimental design algorithm for assigning genetically related samples, including the Collaborative Cross mice and the Diversity Outbred mice to experimental arms for optimal detection power. In relative to implementing geostatistical modeling and visualization tools, the group has leveraged their geospatial modeling and associated statistical techniques toward COVID-19 disease risk through the acquisition of supplemental funding. They are using these findings for the launch of a web portal that will include these visualizations and associated tools. In relation to integrating data across Projects, they worked towards this goal by ensuring there is frequent communication across Projects, including the prioritization of data records and experimentation that could lead to cross-project data integration.

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