Software 📦

Releases



Software Review ✔

We accept community contributed packages via our onboarding system - an open software review system, sorta like scholarly paper review, but way better. We’ll highlight newly onboarded packages here. A huge thanks to our reviewers, who do a lot of work reviewing (see the blog post on our review system), and the authors of the packages!

If you want to be a reviewer fill out this short form, and we’ll ping you when there’s a submission that fits in your area of expertise.

The following four packages recently went through our onboarding process and has been approved!

The following two packages were recently submitted:



On the blog

main blog

Steffi LaZerte wrote about her package weathercan recently onboarded with rOpenSci: Integrating data from weathercan

Charles Gray wrote about her experience in reviewing her first R package: An Ode to Testing, my first review.

The rOpenSci Editors wrote a post Thanking Your Reviewers: Gratitude through Semantic Metadata announcing that we can now include reviewers in the Authors section of an R package’s DESCRIPTION file. Yay!

David Winter wrote a post (A rentrez paper, and how to use the NCBI’s new API keys) about his package rentrez for interacting with NCBI data. He discussed a recently published paper on rentrez and support for API keys for NCBI.



Use cases

If you’ve used rOpenSci software in a blog post or a paper, tell us on the discussion forum and we’ll share it with our community here.

The following 15 works use/cite rOpenSci software:



In the news

David Clark shared a screenshot of packages he was using for a project, including rOpenSci’s geojsonio package to do GeoJSON I/O (input/output):


Ciera Martinez and Caryn Johansen describe in a blog post how to use our neotoma package to access and explore mammal bone records





Keep up with rOpenSci


Footnotes

  1. Borcard D., Gillet F., Legendre P. (2018) Community Diversity. In: Numerical Ecology with R. Use R! Springer, Cham https://doi.org/10.1007/978-3-319-71404-2_8 ↩

  2. Cho, H., & Yu, Y. (2018). Link prediction for interdisciplinary collaboration via co-authorship network. arXiv preprint arXiv:1803.06249. https://arxiv.org/pdf/1803.06249.pdf ↩

  3. Nabout, J. C., Teresa, F. B., Machado, K. B., do Prado, V. H. M., Bini, L. M., & Diniz-Filho, J. A. F. (2018). Do traditional scientometric indicators predict social media activity on scientific knowledge? An analysis of the ecological literature. Scientometrics. https://doi.org/10.1007/s11192-018-2678-x ↩

  4. Sanyal, A., Lenoir, J., O’Neill, C., Dubois, F., & Decocq, G. (2018). Intraspecific and interspecific adaptive latitudinal cline in Brassicaceae seed oil traits. American Journal of Botany, 105(1), 85–94. https://doi.org/10.1002/ajb2.1014 ↩

  5. Lakiotaki, K., Vorniotakis, N., Tsagris, M., Georgakopoulos, G., & Tsamardinos, I. (2018). BioDataome: a collection of uniformly preprocessed and automatically annotated datasets for data-driven biology. Database, 2018. https://doi.org/10.1093/database/bay011 ↩

  6. Vieilledent, G., Fischer, F. J., Chave, J., Guibal, D., Langbour, P., & Gérard, J. (2018). New formula and conversion factor to compute tree species basic wood density from a global wood technology database. bioRxiv, 274068. https://doi.org/10.1101/274068 ↩

  7. Foster, Z. S. L., Chamberlain, S., & Grünwald, N. J. (2018). Taxa: An R package implementing data standards and methods for taxonomic data. F1000Research, 7, 272. https://doi.org/10.12688/f1000research.14013.1 ↩

  8. Farquharson, K. A., Hogg, C. J., & Grueber, C. E. (2018). A meta-analysis of birth-origin effects on reproduction in diverse captive environments. Nature Communications, 9(1). https://doi.org/10.1038/s41467-018-03500-9 ↩

  9. Bemmels, J. B., Wright, S. J., Garwood, N. C., Queenborough, S. A., Valencia, R., & Dick, C. W. (2018). Filter-dispersal assembly of lowland Neotropical rainforests across the Andes. Ecography. https://doi.org/10.1111/ecog.03473 ↩

  10. Ng, P. K.-S., Li, J., Jeong, K. J., Shao, S., Chen, H., Tsang, Y. H., … Mills, G. B. (2018). Systematic Functional Annotation of Somatic Mutations in Cancer. Cancer Cell, 33(3), 450–462.e10. https://doi.org/10.1016/j.ccell.2018.01.021 ↩

  11. Bennett, J. M., Calosi, P., Clusella-Trullas, S., Martínez, B., Sunday, J., Algar, A. C., … Morales-Castilla, I. (2018). GlobTherm, a global database on thermal tolerances for aquatic and terrestrial organisms. Scientific Data, 5, 180022. https://doi.org/10.1038/sdata.2018.22 ↩

  12. Correia, R. A., Jarić, I., Jepson, P., Malhado, A. C. M., Alves, J. A., & Ladle, R. J. (2018). Nomenclature instability in species culturomic assessments: Why synonyms matter. Ecological Indicators, 90, 74–78. https://doi.org/10.1016/j.ecolind.2018.02.059 ↩

  13. Reibe, S., Hjorth, M., Febbraio, M. A., & Whitham, M. (2018). GeneXX: An online tool for the exploration of transcript changes in skeletal muscle associated with exercise. Physiological genomics. https://doi.org/10.1152/physiolgenomics.00127.2017 ↩

  14. Sinval, J., Pasian, S., Queirós, C., & Marôco, J. (2018). Brazil-Portugal Transcultural Adaptation of the UWES-9: Internal Consistency, Dimensionality, and Measurement Invariance. Frontiers in Psychology, 9. https://doi.org/10.3389/fpsyg.2018.00353 ↩

  15. Bergmann, A. J., Scott, R. P., Wilson, G., & Anderson, K. A. (2018). Development of quantitative screen for 1550 chemicals with GC-MS. Analytical and Bioanalytical Chemistry, 1-10. https://link.springer.com/article/10.1007/s00216-018-0997-7 ↩