3 Matching Annotations
  1. Jul 2018
    1. Fully reproducible code is available in the form of jupyter notebooks (https://jupyter.org) with instructions to install all necessary software, download sequence data, assemble it, and run genomic analyses (https://github.com/dereneaton/Canarium-GBS) (DOI 10.5281/zenodo.1273357). For all genomic analyses in this study we used the ipyrad Python API and the ipyrad-analysis toolkit (https://github.com/dereneaton/ipyrad) which provides a set of wrappers around common genomic analysis tools to run highly parallelized analyses using simple Python scripts.

      Example of author sharing all code via jupyter notebooks in a github repo. They have archived to Zenodo and include both URLs in the text. Their analysis relies on an existing toolkit - it is not obvious from the manuscript whether this toolkit has been deposited anywhere.

      Journal: PLOS ONE Subject area: plant biology, ecology (check?)

    1. Source code of the model presented here is available on GitHub (https://github.com/lukasgeyrhofer/phagegrowth) (Payne et al., 2018) and its archived version is accessible through Zenodo: https://dx.doi.org/10.5281/zenodo.1038582 and https://github.com/elifesciences-publications/phagegrowth.

      Example of authors archiving their own code. The eLife process is to fork the author's repo to the eLife github repo to save a snapshot of the repo at the time of acceptance. The authors here have also chosen to archive to Zenodo (via the Github release --> Zenodo mechanism?). Both the Zenodo DOI and the eLife fork are included in the text as archive/snapshot copies of the original (also cited).

      Note the author's original repo is included in the references.

      Journal: eLife Subject area: ecology, evolutionary biology

    2. doi: 10.5281/zenodo.1038582RRID:SCR_004129Zenodo repository

      In this example, the archived code repository has been listed in the eLife Key Resources Table