Sign in
BioinformaticsbioRxiv

ReproPhylo: An Environment for Reproducible Phylogenomics

Amir Szitenberg, Max John, Mark L Blaxter, David H Lunt

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.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISResl '23McTavish '15Palacios '23O’Halloran '17Pelletier '22Lee '19
71% semantic matchBioinformatics
Philipp Resl, Christoph Hahn·bioRxiv·Sep 22, 2023· 2 citations