BioLite, a lightweight bioinformatics framework with automated tracking of diagnostics and provenance

  • Authors:
  • Mark Howison;Nicholas A. Sinnott-Armstrong;Casey W. Dunn

  • Affiliations:
  • Brown University;Brown University;Brown University

  • Venue:
  • TaPP'12 Proceedings of the 4th USENIX conference on Theory and Practice of Provenance
  • Year:
  • 2012

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Abstract

We present a new Python/C++ framework, BioLite, for implementing bioinformatics pipelines for Next-Generation Sequencing (NGS) data. BioLite tracks provenance of analyses, automates the collection and reporting of diagnostics (such as summary statistics and plots at intermediate stages), and profiles computational requirements. These diagnostics can be accessed across multiple stages of a pipeline, from other pipelines, and in HTML reports. Finally, we describe several use cases for diagnostics in our own analyses.