WU-SN-TMC Data Analysis Core

Data Analysis Core Summary/Abstract Our group has a well-established history of large-scale omics and imaging data management, processing, analysis, and interpretation in the context of consortium projects. We have built, used, and maintained data warehouses and the associated tracking, meta-data, and QC machinery for specimens and raw data and have

developed a large number of computational tools for processing, analyzing, and interpreting such data. The primary mission of the Data Analysis Core at the Washington University Cellular Senescence Network Tissue Mapping Center (WU-SN-TMC) will take place along 4 primary dimensions: 1) providing data support to the

Biospecimen and Biological Analysis Cores, 2) processing raw assay data from the Biological Analysis Core and marrying these with data from other SN-TMCs using cutting-edge informatics pipeline and integrated approaches, 3) applying processed data to build organ-specific cellular senescence atlases, with a focus on

differences/evolution among demographic groups (especially by age) and within the individual (between organs and longitudinally), and 4) finally managing delivery of data and research products to the Consortium Organization and Data Coordinating Center (CODCC) and coordinating further activities toward amalgamation

of findings across the SenNet project. Data Analysis Core will promote cooperation through development of common formats and interoperable tools for advanced omics and imaging technologies within the SenNet program, harmonize tools in larger, scalable, user-friendly pipelines and distribute tools to the larger scientific

community under open-source licensing, develop senescence signatures and models using integrated data, and investigate how nascent technologies will be brought into the research infrastructure to improve processes and results for senescence research. In conclusion, Data Analysis Core will be a crucial cog within WU-SN-

TMC and serve as a strong link between WU-SN-TMC, CODCC, and other TMCs within SenNet.