Frontiers in Neuroinformatics (Apr 2012)

The pipeline system for Octave and Matlab (PSOM): a lightweight scripting framework and execution engine for scientific workflows

  • Pierre eBellec,
  • Pierre eBellec,
  • Sébastien eLavoie-Courchesne,
  • Sébastien eLavoie-Courchesne,
  • Phil eDickinson,
  • Phil eDickinson,
  • Jason eLerch,
  • Jason eLerch,
  • Alex eZijdenbos,
  • Alan C Evans

DOI
https://doi.org/10.3389/fninf.2012.00007
Journal volume & issue
Vol. 6

Abstract

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The analysis of neuroimaging databases typically involves a large number of inter-connected steps called a pipeline. The pipeline system for Octave and Matlab (PSOM) is a flexible framework for the implementation of pipelines in the form of Octave or Matlab scripts. PSOM does not introduce new language constructs to specify the steps and structure of the workflow. All steps of analysis are instead described by a regular Matlab data structure, documenting their associated command and options, as well as their input, output and cleaned-up files. The PSOM execution engine provides a number of automated services: (1) it executes jobs in parallel on a local computing facility as long as the dependencies between jobs allow for it and sufficient resources are available; (2) it generates a comprehensive record of the pipeline stages and the history of execution, which is detailed enough to fully reproduce the analysis; (3) if an analysis is started multiple times, it executes only the parts of the pipeline that need to be reprocessed. PSOM is distributed under an opensource MIT license and can be used without restriction for academic or commercial projects. The package has no external dependencies besides Matlab or Octave, is straightforward to install and supports of variety of operating systems (Linux, Windows, Mac). We ran several benchmark experiments on a public database including 200 subjects, using a pipeline for the preprocessing of functional magnetic resonance images. The benchmark results showed that PSOM is a powerful solution for the analysis of large databases using local or distributed computing resources.

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