Simulation Data on Family Mapping Design and Resource Allocation

Dryad hosts simulation data from a study on optimum design and resource allocation for family-based association mapping. The research used simulation, resample model averaging, and cross-validation to analyze factors like population size and phenotyping intensity. Results indicate predictive power and QTL detection accuracy depend heavily on these design parameters.

Use Cases

• Analyze the relationship between population size and the accuracy of QTL detection in family mapping simulations.
• Model the impact of phenotyping intensity and test environment count on the bias of estimated genotypic variance.
• Simulate the effect of marker density on result quality to inform future sequencing study designs.
• Apply resample model averaging techniques to simulation outputs for robust parameter estimation.

Strengths

• Data originates from a peer-reviewed methodological study published in 2020.
• Simulation approach allows controlled investigation of design factors like population size and marker density.
• Analysis incorporates advanced statistical methods including cross-validation and resample model averaging.

Limitations

• The dataset consists of simulation outputs, not empirical genetic or phenotypic measurements.
• Specific sample sizes, row counts, and data formats are not provided in the metadata.
• Findings are based on simulated conditions which may not fully capture real-world biological complexity.

Provenance

Source

Dryad digital repository.

Collection Method

Generated via simulation study, resample model averaging, and cross-validation.

Freshness

Last updated in June 2020.