![]() ![]() ![]() All these systems differ by the way the dependencies between jobs are encoded. ![]() Some scripting languages were also developed specifically to compose pipelines, e.g., DAGMan 8, Swift 9 (Wilde et al., 2011) and Pegasus (Deelman et al., 2005). Many extensions of existing languages have been developed for that purpose, such as matlabbatch 5 for Matlab, or Nipype 6 (Gorgolewski et al., 2011) and the Soma-workflow 7 (Laguitton et al., 2011) for Python. The composition of a pipeline is the generation of a (possibly abstract) representation of all steps of analysis and associated dependencies, including access to datasets. To contrast PSOM against alternative projects, we reviewed key features of popular packages within four areas of a pipeline life cycle (Deelman et al., 2009): (1) composition of the pipeline (2) mapping of the pipeline to the underlying resources (3) execution of the pipeline (4) recording of the metadata and provenance. To facilitate the inclusion of these computational tools in complex scientific workflows, we developed a general-purpose pipeline system in Octave and Matlab (PSOM) 4. It can also wrap heterogeneous tools implemented in a variety of languages. Matlab is a programming language for general scientific computing, well-adapted to the rapid prototyping of new algorithms. Neuroimaging pipelines can be implemented as a Matlab script, e.g., DPARSF (Chao-Gan and Yu-Feng, 2010), fMRIstat 1 (Worsley et al., 2002), SPM 2 (Ashburner, 2011), or brainstorm 3 (Tadel et al., 2011). The analysis of a neuroimaging database typically involves a large number of inter-connected processing steps, collectively referred to as a pipeline (or workflow) (Deelman et al., 2009). The rapid development of public databases in neuroimaging (e.g., Evans, 2006 Biswal et al., 2010 Burton, 2011) is opening exciting avenues for data mining. The benchmark results showed that PSOM is a powerful solution for the analysis of large databases using local or distributed computing resources. We ran several benchmark experiments on a public database including 200 subjects, using a pipeline for the preprocessing of functional magnetic resonance images (fMRI). Octave vs matlab for mac install#The package has no external dependencies besides Matlab or Octave, is straightforward to install and supports of variety of operating systems (Linux, Windows, Mac). Octave vs matlab for mac license#PSOM is distributed under an open-source MIT license and can be used without restriction for academic or commercial projects. 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. ![]() 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. PSOM does not introduce new language constructs to specify the steps and structure of the workflow. 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. The analysis of neuroimaging databases typically involves a large number of inter-connected steps called a pipeline. ![]()
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