Objective
To provide an accessible, comprehensive resource that highlights key population genetics methods and software, offering insights into their applications, strengths, limitations, and practical use.
Description
We invite developers of both widely used and new population genetics software to contribute concise, accessible summaries of their methods. These articles will serve as a practical guide, including clear explanations of the software's purpose, applications, advantages, and potential biases, alongside tips and tricks for effective use. Scripts and example analyses will be shared in a public repository linked to the publication, ensuring transparency and reproducibility.
To encourage collaboration and mentorship, we welcome authors to co-write their submissions with PhD students, postdocs, or even master's students as first authors. This provides an excellent opportunity for early-career researchers to contribute an article, especially for software that has been previously published, subject to peer review. This additional platform will promote these tools further and provide users with clear benchmarks using shared test datasets, such as HGDP or KGP.
This issue will also feature new and emerging population genetics methods, creating a valuable reference for both seasoned researchers and newcomers to the field.
Core Elements
1. Accessible Summaries by Method Developers
Invite authors of widely used population genetics software to contribute short and clear summaries.
Include:
- A brief overview of the method and its main purpose.
- Practical applications and scenarios where the method excels.
- Clear, easy-to-understand explanations of how the method works.
2. Practical Resources
- Share example scripts in a dedicated and publicly accessible repository linked to the publication.
- Provide "Tips and Tricks" sections for running each software effectively.
3. Balanced Discussion
Authors to address:
- Strengths and unique features of their methods.
- Potential biases, limitations, and cautions.
- Suggestions for complementary analyses to mitigate these limitations.
4. Comparative Analyses
- Standardize comparisons by running the software on shared reference datasets, such as HGDP or KGP, or widely used and accessible ancient DNA data.
- Generate a consistent benchmark for users to reference, ensuring clarity in results across tools.
5. Inclusion of Novel Tools
- Invite contributions from developers of new population genetics tools and methods.
- Focus on cutting-edge approaches and innovations.
Benefits of the Issue
- Enhances accessibility to key software and methods for both new and experienced researchers.
- Facilitates best practices in population genetics analysis by providing practical guidance.
- Promotes reproducibility and transparency through shared resources and scripts.
- Encourages interdisciplinary collaboration and integration of emerging tools into broader research contexts.
This special issue aims to serve as both an educational resource and a bridge between method developers and users in the population genetics community.
Submitted manuscripts should not have been published previously, nor been under consideration for publication elsewhere (except conference proceedings). All manuscripts will be thoroughly refereed through a single-blinded peer-review process. A guide for manuscript submission is available at Submission Instructions.
