Data and Statistical Core
- Institution
- JACKSON LABORATORY, ME
- Principal investigator
- Gary A Churchill
- Funding
- $141K
- Duration
- 2010–2030
Moonbase score
Still being scored
Abstract
PROJECT SUMMARY / ABSTRACT DATA AND STATISTICAL CORE Studies conducted by The Jackson Laboratory Nathan Shock Center (JAX NSC) produce an enormous amount of data, including phenotypic, genetic, molecular profiling, and microbiome data. Our aging studies have produced extensive cross-sectional and longitudinal data across thousands of mice. With new phenotyping technologies constantly being developed, the scope of our data collection and analysis needs continues to grow. Thus, a well-functioning and efficient data management and statistical analysis operation is necessary. The JAX NSC Data and Statistical Core is responsible for all aspects of the management, quality control, analysis, and dissemination of data from JAX NSC projects. The Specific Aims of the Data and Statistical Core are as follows: Aim 1. Develop and maintain the data management, quality control, and analysis infrastructure to support JAX NSC projects. We will expand the capabilities of our Laboratory Information Management System, CLIMB LIMS (Rockstep, Inc.), to implement automated data collection and quality control procedures for our growing portfolio of studies, pilot projects, and collaborations. Aim 2. Disseminate JAX NSC data to the geroscience community. We will make data available to the geroscience community with protocols and metadata necessary to ensure that all JAX NSC data are findable, accessible, interoperable, and reproducible (FAIR). Aim 3. Develop and disseminate new data analysis methods and tools to support aging research. We will analyze data from JAX NSC and other sources to address important biological questions in aging research, including evaluating the effects of co-housing on mouse aging studies and estimating genotype x treatment effects in intervention studies. In summary, the Data and Statistical Core will provide comprehensive data management, FAIR dissemination of data, and sophisticated data analysis to support aging mouse studies. These activities are key to translating data into a deeper understanding of lifespan and healthy aging and to accelerating the pace of aging research.
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