GAMETES Heterogeneity Dataset with 20 Attributes and 0.4 Heritability

A GAMETES dataset for evaluating genetic association methods, focusing on heterogeneity. The dataset name indicates it contains 20 attributes and has a heritability parameter of 0.4.

Use Cases

• Evaluate the performance of epistasis detection algorithms on data with 20 attributes and specified heterogeneity parameters.
• Benchmark machine learning models like Random Forests or neural networks for identifying complex genetic interactions in simulated data with 0.4 heritability.
• Study the effect of heterogeneity (Het_0.4_0.2) and minor allele frequency (50) on the power of statistical tests for genetic association.

Strengths

• Dataset name specifies 20 attributes, providing a known feature count for analysis.
• Heritability parameter (0.4) and heterogeneity parameters (0.4, 0.2) are explicitly defined, allowing for controlled simulation studies.
• Part of the GAMETES suite, which is designed for generating realistic genetic models for evaluation.

Limitations

• The exact number of rows (samples) is unknown, preventing assessment of statistical power or suitability for large-scale models.
• Column names and data types are unspecified, requiring investigation before feature engineering or modeling.
• As a simulated dataset, its patterns may not fully capture the complexity of real-world biological data.

Provenance

Source

openml

Collection Method

Simulated data from the GAMETES (Genetic Architecture Model Emulator for Testing and Evaluating Software) framework.