Scientific Data (Nov 2022)

pISA-tree - a data management framework for life science research projects using a standardised directory tree

  • Marko Petek,
  • Maja Zagorščak,
  • Andrej Blejec,
  • Živa Ramšak,
  • Anna Coll,
  • Špela Baebler,
  • Kristina Gruden

DOI
https://doi.org/10.1038/s41597-022-01805-5
Journal volume & issue
Vol. 9, no. 1
pp. 1 – 9

Abstract

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Abstract We developed pISA-tree, a straightforward and flexible data management solution for organisation of life science project-associated research data and metadata. pISA-tree was initiated by end-user requirements thus its strong points are practicality and low maintenance cost. It enables on-the-fly creation of enriched directory tree structure (project/Investigation/Study/Assay) based on the ISA model, in a standardised manner via consecutive batch files. Templates-based metadata is generated in parallel at each level enabling guided submission of experiment metadata. pISA-tree is complemented by two R packages, pisar and seekr. pisar facilitates integration of pISA-tree datasets into bioinformatic pipelines and generation of ISA-Tab exports. seekr enables synchronisation with the FAIRDOMHub repository. Applicability of pISA-tree was demonstrated in several national and international multi-partner projects. The system thus supports findable, accessible, interoperable and reusable (FAIR) research and is in accordance with the Open Science initiative. Source code and documentation of pISA-tree are available at https://github.com/NIB-SI/pISA-tree .