Phylogenetic Model Simulations Linking dN/dS and Scaled Selection Coefficients

Stephanie J. Spielman's 2020 research data elucidates the mathematical relationship between dN/dS and mutation-selection (MutSel) models for analyzing natural selection in protein-coding sequences. It provides simulation results used to benchmark dN/dS inferences, revealing biases in Goldman-Yang-style models and better performance in Muse-Gaut-style models. The dataset supports the study's conclusion that model fit does not guarantee accurate parameter estimation.

Use Cases

• Benchmark dN/dS inference methods against MutSel model simulations to evaluate estimation bias.
• Analyze the relationship between scaled selection coefficients and dN/dS values under different assumptions of synonymous codon fitness.
• Compare the performance of Goldman-Yang-style and Muse-Gaut-style dN/dS models using the proposed simulation framework.
• Investigate conditions where dN/dS can indicate positive selection despite underlying purifying selection, as derived from the mathematical model.

Strengths

• Data originates from a peer-reviewed scientific study published in 2020, providing a clear academic context.
• The research establishes a novel mathematical link between two major phylogenetic modeling frameworks (dN/dS and MutSel).
• Includes simulation results that demonstrate specific biases in widely-used dN/dS models.

Limitations

• The specific data format, size, and structure (e.g., rows, columns) are not described in the provided input.
• The dataset is likely specialized for evolutionary biology research, limiting its applicability to other fields.
• As a static research output from 2020, it does not receive updates or expansions.

Provenance

Source

Dryad digital repository.

Collection Method

Generated from computational simulations and mathematical derivations for a published research study.

Freshness

Last updated 2020-06-24.