Sustainable data and metadata management at the BD2K-LINCS Data Coordination and Integration Center

TitleSustainable data and metadata management at the BD2K-LINCS Data Coordination and Integration Center
Publication TypeJournal Article
Year of Publication2018
AuthorsStathias V, Koleti A, Vidovic´ D, Cooper DJ, Jagodnik KM, Terryn R, Forlin M, Chung C, Torre D, Ayad N, Medvedovic M, Ma'ayan A, Pillai A, Schürer SC
JournalScientific Data - Nature
Volume5
Issue180117
Date PublishedJune, 2018
Abstract

The NIH-funded LINCS Consortium is creating an extensive reference library of cell-based perturbation response signatures and sophisticated informatics tools incorporating a large number of perturbagens, model systems, and assays. To date, more than 350 datasets have been generated including transcriptomics, proteomics, epigenomics, cell phenotype and competitive binding profiling assays. The large volume and variety of data necessitate rigorous data standards and effective data management including modular data processing pipelines and end-user interfaces to facilitate accurate and reliable data exchange, curation, validation, standardization, aggregation, integration, and end user access. Deep metadata annotations and the use of qualified data standards enable integration with many external resources. Here we describe the end-to-end data processing and management at the DCIC to generate a high-quality and persistent product. Our data management and stewardship solutions enable a functioning Consortium and make LINCS a valuable scientific resource that aligns with big data initiatives such as the BD2K NIH Program and concords with emerging data science best practices including the findable, accessible, interoperable, and reusable (FAIR) principles.

DOI10.1038/sdata.2018.117
Last Updated: 
Sep 14 2018 - 2:59pm