Linking big biomedical datasets to modular analysis with Portable Encapsulated Projects

  1. Nathan C Sheffield
  2. Michał Stolarczyk
  3. Vincent P Reuter
  4. André F Rendeiro

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

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/.

Article activity feed

  2. Version published to 10.1093/gigascience/giab077
  3. Version published to 10.1101/2020.10.08.331322v2 on bioRxiv
  4. Version published to 10.1101/2020.10.08.331322v1 on bioRxiv