{ "info": { "author": "Bo Peng", "author_email": "bpeng@mdanderson.org", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Environment :: Console", "Intended Audience :: Information Technology", "Intended Audience :: Science/Research", "License :: OSI Approved :: GNU General Public License (GPL)", "Natural Language :: English", "Operating System :: MacOS :: MacOS X", "Operating System :: Microsoft :: Windows", "Operating System :: POSIX :: Linux", "Programming Language :: Python :: 3 :: Only", "Programming Language :: Python :: Implementation :: CPython" ], "description": "Computationally intensive disciplines such as computational biology often \nrequires one to exploit a variety of tools implemented in different programming\nlanguages, and to analyze large datasets on high performance computing systems.\nAlthough scientific workflow systems are powerful in organizing and executing\nlarge-scale data analysis processes, there are usually non-trivial learning\ncurve and engineering overhead in creating and maintaining such workflows,\nmaking them unsuitable for data exploration and prototyping. To bridge the\ngap between interactive analysis and workflow systems, we developed Script\nof Scripts (SoS), a system with strong emphases on readability, practicality,\nand reproducibility for daily computational research. For exploratory analysis\nSoS provides a multi-language file format and scripting engine that centralizes\nall computations, and creates dynamic report documents for publishing and\nsharing. As a workflow engine, SoS provides an intuitive syntax to create\nworkflows in process-oriented, outcome-oriented and mixed styles, as well as\na unified interface to executing and managing tasks on a variety of computing\nplatforms with automatic synchronization of files between isolated systems.\nIn this paper we illustrate with real-world examples the use of SoS as both\ninteractive analysis tool and pipeline platform for all stages of methods\ndevelopment and data analysis projects. 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