API Reference

Models

• BayesPRSModel: A base class for all Bayesian PRS models.
• VIPRS: Implementation of VIPRS with the "spike-and-slab" prior.
  • Implementation of VIPRS with other priors:
    • VIPRSMix: VIPRS with a sparse Gaussian mixture prior.
• Hyperparameter Tuning: Models/modules for performing hyperparameter search with VIPRS models.
  • Hyperparameter grid: A utility class to help construct grids over model hyperparameters.
  • HyperparameterSearch
  • VIPRSGrid
  • grid_utils: Utilities for performing model selection/averaging.
• Baseline Models:
  • LDPredInf: Implementation of the LDPred-inf model.

Model Evaluation

• Binary metrics: Evaluation metrics for binary (case-control) phenotypes.
• Continuous metrics: Evaluation metrics for continuous phenotypes.
• Pseudo metrics: Evaluation metrics based on GWAS summary statistics.

Utilities

• Data utilities: Utilities for downloading and processing relevant data.
• Compute utilities: Utilities for computing various statistics / quantities over python data structures.
• Exceptions: Custom exceptions used in the package.
• OptimizeResult: A class to store the result of an optimization routine.

Plotting

• Diagnostic plots: Functions for plotting various quantities / results from VIPRS or other PRS models.