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ReproPhylo: An Environment for Reproducible Phylogenomics

Amir Szitenberg, Max John, Mark L. Blaxter, David H. Lunt
doi: https://doi.org/10.1101/019349
Amir Szitenberg
1Evolutionary Biology Group, School of Biological, Biomedical & Environmental Sciences, The University of Hull, Hull, UK,
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Max John
1Evolutionary Biology Group, School of Biological, Biomedical & Environmental Sciences, The University of Hull, Hull, UK,
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Mark L. Blaxter
2Institute of Evolutionary Biology, The University of Edinburgh, Edinburgh, UK
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David H. Lunt
1Evolutionary Biology Group, School of Biological, Biomedical & Environmental Sciences, The University of Hull, Hull, UK,
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Abstract

The reproducibility of experiments is key to the scientific process, and particularly necessary for accurate reporting of analyses in data-rich fields such as phylogenomics. We present ReproPhylo, a phylogenomic analysis environment developed to ensure experimental reproducibility, to facilitate the handling of large-scale data, and to assist methodological experimentation. Reproducibility, and instantaneous repeatability, is built in to the ReproPhylo system, and does not require user intervention or configuration because it stores the experimental workflow as a single, serialized Python object containing explicit provenance and environment information. This ‘single file’ approach ensures the persistence of provenance across iterations of the analysis, with changes automatically managed by the version control program Git. ReproPhylo produces an extensive human-readable report, and generates a comprehensive experimental archive file, both of which are suitable for submission with publications. The system facilitates thorough experimental exploration of both parameters and data. ReproPhylo is a platform independent CC0 python module, and is easily installed as a Docker image, with an Jupyter GUI, or as a slimmer version in a Galaxy distribution.

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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 May 15, 2015.
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ReproPhylo: An Environment for Reproducible Phylogenomics
Amir Szitenberg, Max John, Mark L. Blaxter, David H. Lunt
bioRxiv 019349; doi: https://doi.org/10.1101/019349
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ReproPhylo: An Environment for Reproducible Phylogenomics
Amir Szitenberg, Max John, Mark L. Blaxter, David H. Lunt
bioRxiv 019349; doi: https://doi.org/10.1101/019349

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