Linking big biomedical datasets to modular analysis with Portable Encapsulated Projects

Author:

Sheffield Nathan C1234ORCID,Stolarczyk Michał1ORCID,Reuter Vincent P15ORCID,Rendeiro André F67ORCID

Affiliation:

1. Center for Public Health Genomics, University of Virginia, VA 22908, USA

2. Department of Public Health Sciences, University of Virginia, VA 22908, USA

3. Department of Biomedical Engineering, University of Virginia, VA 22908, USA

4. Department of Biochemistry and Molecular Genetics, University of Virginia, VA 22908, USA

5. Genomics and Computational Biology Graduate Group, University of Pennsylvania, PA 19087, USA

6. Institute for Computational Biomedicine, Weill Cornell Medical College, NY 10021, USA

7. Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medical College, NY 10021, USA

Abstract

Abstract Background Organizing and annotating biological sample data is critical in data-intensive bioinformatics. Unfortunately, metadata formats from a data provider are often incompatible with requirements of 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. Results To address this, we present the Portable Encapsulated Project (PEP) specification, a formal specification for biological sample metadata structure. The PEP specification accommodates typical features of data-intensive bioinformatics projects with many biological samples. In addition to standardization, the PEP specification provides descriptors and modifiers for project-level and sample-level metadata, which improve portability across both computing environments and data processing tools. PEPs include a schema validator framework, allowing formal definition of required metadata attributes for data analysis broadly. We have implemented packages for reading PEPs in both Python and R to provide a language-agnostic interface for organizing project metadata. Conclusions The PEP specification is an important step toward unifying data annotation and processing tools in data-intensive biological research projects. Links to tools and documentation are available at http://pep.databio.org/.

Funder

National Institute of General Medical Sciences

Publisher

Oxford University Press (OUP)

Subject

Computer Science Applications,Health Informatics

Reference31 articles.

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