↓ Skip to main content

Developing educational resources for population genetics in R: an open and collaborative approach

Overview of attention for article published in Molecular Ecology Resources, July 2016
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

twitter
18 X users

Readers on

mendeley
249 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Article details
Title
Developing educational resources for population genetics in R: an open and collaborative approach
Published in
Molecular Ecology Resources, July 2016
DOI 10.1111/1755-0998.12558
Pubmed ID
Authors
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. This article is protected by copyright. All rights reserved.

Login to access the Attention Digest and the Sentiment Analysis related to this output.

Timeline Attention over time Attention Score history
Login to access the full charts related to this output.
Activity
Login to access the full charts related to this output.
X Demographics

X Demographics

The data shown below were collected from the profiles of 18 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 249 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Login to view Mendeley reader trends over time.

Geographical breakdown

Geographical breakdown
Country Count As %
United States 4 2%
Brazil 2 <1%
Netherlands 1 <1%
Finland 1 <1%
Germany 1 <1%
Czechia 1 <1%
Chile 1 <1%
Canada 1 <1%
Unknown 237 95%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 54 22%
Student > Ph. D. Student 51 20%
Student > Master 37 15%
Student > Bachelor 18 7%
Student > Doctoral Student 16 6%
Other 45 18%
Unknown 28 11%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 129 52%
Biochemistry, Genetics and Molecular Biology 45 18%
Environmental Science 13 5%
Computer Science 7 3%
Medicine and Dentistry 5 2%
Other 15 6%
Unknown 35 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 July 2017.
All research outputs
#4,460,401
of 34,567,073 outputs
Outputs from Molecular Ecology Resources
#513
of 2,137 outputs
Outputs of similar age
#51,888
of 336,438 outputs
Outputs of similar age from Molecular Ecology Resources
#9
of 39 outputs
Altmetric has tracked 34,567,073 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,137 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 10.0. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 336,438 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.