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?)