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CHANGELOG.md

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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[0.1.2] - 2024-06-03

Changed

  • Fixed bug in implementation of .fit method of VIPRS models. Specifically, there was an issue with the continued=True flag not working because the OptimizeResult object wasn't refreshed.
  • Replaced print statements with logging where appropriate (still needs some more work).
  • Updated way we measure peak memory in viprs_fit
  • Updated dict_concat to just return the element if there's a single entry.
  • Refactored pars of VIPRS to cache some recurring computations.
  • Updated VIPRSBMA & VIPRSGridSearch to only consider models that successfully converged.
  • Fixed bug in psuedo_metrics when extracting summary statistics data.
  • Streamlined evaluation code.
  • Refactored code to slightly reduce import/load time.

Added

  • Added SNP position to output table from VIPRS objects.
  • Added measure of time taken to prepare data in viprs_fit.
  • Added option to keep long-range LD regions in viprs_fit.
  • Added convergence check based on parameter values.
  • Added min_iter parameter to .fit methods to ensure CAVI is run for at least min_iter iterations.
  • Added separate method for initializing optimization-related objects.

[0.1.1] - 2024-04-24

Changed

  • Fixed bugs in the E-Step benchmarking script.
  • Re-wrote the logic for finding BLAS libraries in the setup.py script. 🤞
  • Fixed bugs in CI / GitHub Actions scripts.

Added

  • Dockerfiles for both cli and jupyter modes.

[0.1.0] - 2024-04-05

A large scale restructuring of the code base to improve efficiency and usability.

Changed

  • Moved plotting script to its own separate module.
  • Updated some method names / commandline flags to be consistent throughout.
  • Updated the VIPRS class to allow for more flexibility in the optimization process.
  • Removed the VIPRSAlpha model for now. This will be re-implemented in the future, using better interfaces / data structures.
  • Moved all hyperparameter search classes/models to their own directory.
  • Restructured the viprs_fit commandline script to make the code cleaner, do better sanity checking, and introduce process parallelism over chromosomes.

Added

  • Basic integration testing with pytest and GitHub workflows.
  • Documentation for the entire package using mkdocs.
  • Integration testing / automating building with GitHub workflows.
  • New self-contained implementation of E-Step in Cython and C++.
    • Uses OpenMP for parallelism across chunks of variants.
    • Allows for de-quantization on the fly of the LD matrix.
    • Uses BLAS linear algebra operations where possible.
    • Allows model fitting with only
  • Benchmarking scripts (benchmark_e_step.py) to compare computational performance of different implementations.
  • Added functionality to allow the user to track time / memory utilization in viprs_fit.
  • Added OptimizeResult class to keep track of the info/parameters of EM optimization.
  • New evaluation metrics
    • pseudo_metrics has been moved to its own module to allow for more flexibility in evaluation.
    • New evaluation metrics for binary traits: nagelkerke_r2, mcfadden_r2, cox_snell_r2 liability_r2, liability_probit_r2, liability_logit_r2.
    • New function to compute standard errors / test statistics for all R-Squared metrics.

[0.0.4] - 2022-09-07

Changed

  • Removed the --fast-math compiler flag due to concerns about numerical precision (e.g. Beware of fast-math).

[0.0.3] - 2022-09-06

Added

  • New implementation for the e-step in VIPRS, where we multiply with the rows of the LD matrix only once.
  • Added support for deterministic annealing in the VIPRS optimization.
  • Added support for pseudo_validation as a metric for choosing models. Now, the VIPRS class has a method called pseudo_validate.
  • New implementations for grid-based models: VIPRSGrid, VIPRSGridSearch, VIPRSBMA.
  • New python implementation of the LDPredinf model, using the viprs/magenpy data structures.
  • MIT license for the software.

Changed

  • Corrected implementation of Mean Squared Error (MSE) metric.
  • Changed the c_utils.pyx script to be math_utils.pyx.
  • Updated documentation in README to follow latest APIs.

[0.0.2] - 2022-06-28

Changed

  • Updating the dependency structure between viprs and magenpy.

[0.0.1] - 2022-06-28

Added

  • Refactoring the code in the viprs repository and re-organizing it into a python package.
  • Added a module to compute predictive performance metrics.
  • Added commandline scripts to allow users to access some of the functionalities of viprs without necessarily having to write python code.
  • Added the estimate of the posterior variance to the output from the module.

Changed

  • Updated plotting script.
  • Updated implementation of VIPRSMix, VIPRSAalpha, etc. to inherit most of their functionalities from the base VIPRS class.
  • Cleaned up implementation of hyperparameter search modules.