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SciPipe - A workflow library for agile development of complex and dynamic bioinformatics pipelines

View ORCID ProfileSamuel Lampa, View ORCID ProfileMartin Dahlö, View ORCID ProfileJonathan Alvarsson, View ORCID ProfileOla Spjuth
doi: https://doi.org/10.1101/380808
Samuel Lampa
1Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
2Department of Biochemistry and Biophysics, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
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Martin Dahlö
1Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
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Jonathan Alvarsson
1Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
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Ola Spjuth
1Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
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Abstract

Background The complex nature of biological data has driven the development of specialized software tools. Scientific workflow management systems simplify the assembly of such tools into pipelines, assist with job automation and aid reproducibility of analyses. Many contemporary workflow tools are specialized and not designed for highly complex workflows, such as with nested loops, dynamic scheduling and parametriza-tion, which is common in e.g. machine learning.

Findings SciPipe is a workflow programming library implemented in the programming language Go, for managing complex and dynamic pipelines in bioinformatics, cheminformatics and other fields. SciPipe helps in particular with workflow constructs common in machine learning, such as extensive branching, parameter sweeps and dynamic scheduling and parametrization of downstream tasks. SciPipe builds on Flow-based programming principles to support agile development of workflows based on a library of self-contained, reusable components. It supports running subsets of workflows for improved iterative development, and provides a data-centric audit logging feature that saves a full audit trace for every output file of a workflow, which can be converted to other formats such as HTML, TeX and PDF on-demand. The utility of SciPipe is demonstrated with a machine learning pipeline, a genomics, and a transcriptomics pipeline.

Conclusions SciPipe provides a solution for agile development of complex and dynamic pipelines, espe-cially in machine leaning, through a flexible programming API suitable for scientists used to programming or scripting.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted October 06, 2018.
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SciPipe - A workflow library for agile development of complex and dynamic bioinformatics pipelines
Samuel Lampa, Martin Dahlö, Jonathan Alvarsson, Ola Spjuth
bioRxiv 380808; doi: https://doi.org/10.1101/380808
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SciPipe - A workflow library for agile development of complex and dynamic bioinformatics pipelines
Samuel Lampa, Martin Dahlö, Jonathan Alvarsson, Ola Spjuth
bioRxiv 380808; doi: https://doi.org/10.1101/380808

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