Bayesian Phylogenetic Branch-Length Prior Analysis Data

Data from a 2020 study by Bradley J. Nelson exploring the effect of informed prior distributions on Bayesian phylogenetic branch-length estimates. The dataset supports comparisons between default and informed settings for exponential and compound Dirichlet priors. It is intended for researchers investigating prior sensitivity in phylogenetics.

Use Cases

• Compare branch-length estimates derived from exponential priors versus compound Dirichlet priors using the provided data.
• Analyze the sensitivity of tree-length inferences to different prior settings as explored in the study.
• Replicate the methodology for setting informed branch-length priors based on outside information described in the paper.

Strengths

• Data originates from a peer-reviewed study specifically focused on prior choice in Bayesian phylogenetics.
• The dataset is associated with a clear publication date of 2020-06-24.
• Released under a permissive CC0-1.0 license for open use.

Limitations

• The specific data structure, row count, column names, and file formats are unknown.
• The dataset's scope is narrowly focused on methodological comparisons for prior distributions, limiting broader biological inference.
• Sample data is unavailable, hindering immediate inspection of data format and quality.

Provenance

Source

Dryad digital repository.

Collection Method

Data generated or compiled for the associated research publication on Bayesian branch-length priors.

Freshness

Last updated 2020-06-24.