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ARS Home » Pacific West Area » Corvallis, Oregon » Horticultural Crops Research Unit » Research » Publications at this Location » Publication #327771
Title: Developing educational resources for population genetics in R: An open and collaborative approach

Author
item KAMVAR, Z - Oregon State University
item LOPEZ-URIBE, M - North Carolina State University
item COUGHLAN, S - National University Of Ireland
item Grunwald, Niklaus - Nik
item LAPP, H - Duke University
item MANEL, S - Institut National De La Recherche Agronomique (INRA)

Submitted to: Molecular Ecology Resources
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/2/2016
Publication Date: 7/12/2016
Citation: Kamvar, Z.N., Lopez-Uribe, M.M., Coughlan, S., Grunwald, N.J., Lapp, H., Manel, S. 2016. Developing educational resources for population genetics in R: An open and collaborative approach. Molecular Ecology Resources. 17(1):120-128. doi: 10.1111/1755-0998.12558.

Interpretive Summary: The R computing and statistical language community has developed a myriad of resources for conducting populations genetic analyses. However, resources for learning how to carry out population genetic analyses in R are scattered and often incomplete, which can make acquiring this skill unnecessarily difficult and time-consuming. We developed an online community resource with guidance and working demonstrations for conducting population genetic analyses in R. We invite the community of population geneticists working in R to contribute to this resource, by contributing their own primers.

Technical Abstract: The R computing and statistical language community has developed a myriad of resources for conducting populations genetic analyses. However, resources for learning how to carry out population genetic analyses in R are scattered and often incomplete, which can make acquiring this skill unnecessarily difficult and time-consuming. To address this gap, we developed an online community resource with guidance and working demonstrations for conducting population genetic analyses in R. The resource is freely available at http://popgen.nescent.org, and includes material for both novices and advanced users of R for population genetics. To facilitate continued maintenance and growth of this resource, we developed a toolchain, process, and conventions designed to (1) minimize financial and labor costs of upkeep; (2) to provide a low barrier to contribution; and (3) to ensure strong quality assurance. The toolchain includes automatic integration testing of every change and rebuilding of the website when new vignettes or edits are accepted. The process and conventions largely follow a common, distributed version control-based contribution workflow, which is used to provide and manage open peer review by designated website editors. The online resources include detailed documentation of this process, including video tutorials. We invite the community of population geneticists working in R to contribute to this resource, whether for a new use-case of their own, or as one of the vignettes from the “wish list” we maintain, or by improving existing vignettes.