Amir Szitenberg
ReproPhylo: An Environment for Reproducible Phylogenomics
Szitenberg, Amir; John, Max; Blaxter, Mark L.; Lunt, David H.
Authors
Contributors
Paul P Gardner
Editor
Abstract
© 2015 Szitenberg et al. 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. This file, along with a Git repository, are the primary reproducibility outputs of the program. In addition, 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 or a WinPython self-sufficient package, with a Jupyter Notebook GUI, or as a slimmer version in a Galaxy distribution.
Citation
Szitenberg, A., John, M., Blaxter, M. L., & Lunt, D. H. (2015). ReproPhylo: An Environment for Reproducible Phylogenomics. PLoS Computational Biology, 11(9), Article ARTN e1004447. https://doi.org/10.1371/journal.pcbi.1004447
Journal Article Type | Article |
---|---|
Acceptance Date | Jul 13, 2015 |
Online Publication Date | Sep 3, 2015 |
Publication Date | Sep 3, 2015 |
Deposit Date | Sep 2, 2015 |
Publicly Available Date | Sep 3, 2015 |
Journal | PLoS computational biology |
Print ISSN | 1553-734X |
Publisher | Public Library of Science |
Peer Reviewed | Peer Reviewed |
Volume | 11 |
Issue | 9 |
Article Number | ARTN e1004447 |
DOI | https://doi.org/10.1371/journal.pcbi.1004447 |
Keywords | Phylogenetics, Phylogenomics, Reproducibility, Experimental parameter selection, Comparative analysis, Workflow, Provenance |
Public URL | https://hull-repository.worktribe.com/output/378621 |
Publisher URL | http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004447 |
Additional Information | Copy of article first published in: PLoS computational biology, 2015, v.11, issue 9. |
Contract Date | Sep 2, 2015 |
Files
Article.pdf
(2.3 Mb)
PDF
Copyright Statement
© 2015 Szitenberg et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
You might also like
A catalogue of chromosome counts for Phylum Nematoda
(2024)
Preprint / Working Paper
Identification of individual root-knot nematodes using low coverage long-read sequencing
(2021)
Journal Article
Using network ecology to understand and mitigate long-term insect declines
(2021)
Journal Article
Genome sequence of the root-knot nematode Meloidogyne luci
(2020)
Journal Article