TY - JOUR T1 - Linking big biomedical datasets to modular analysis with Portable Encapsulated Projects JF - bioRxiv DO - 10.1101/2020.10.08.331322 SP - 2020.10.08.331322 AU - Nathan C. Sheffield AU - Michał Stolarczyk AU - Vincent P. Reuter AU - André F. Rendeiro Y1 - 2020/01/01 UR - http://biorxiv.org/content/early/2020/10/08/2020.10.08.331322.abstract N2 - Organizing and annotating biological sample data is critical in data-intensive bioinformatics. Unfortunately, incompatibility is common between metadata format of a data source and that required by a processing tool. There is no broadly accepted standard to organize metadata across biological projects and bioinformatics tools, restricting the portability and reusability of both annotated datasets and analysis software. To address this, we present Portable Encapsulated Projects (PEP), a formal specification for biological sample metadata structure. The PEP specification accommodates typical features of data-intensive bioinformatics projects with many samples, whether from individual experiments, organisms, or single cells. In addition to standardization, the PEP specification provides descriptors and modifiers for different organizational layers of a project, which improve portability among computing environments and facilitate use of different processing tools. PEP includes a schema validator framework, allowing formal definition of required metadata attributes for any type of biomedical data analysis. We have implemented packages for reading PEPs in both Python and R to provide a language-agnostic interface for organizing project metadata. PEP therefore presents an important step toward unifying data annotation and processing tools in data-intensive biological research projects.Competing Interest StatementThe authors have declared no competing interest. ER -