Changelog

Changelog#

[1.2.2] - 2026-05-17#

  • Added support for numpy 2 and Python 3.13. Bumped minimum versions of scipy, matplotlib, pandas, seaborn, and biopython.

  • Added scale_theta() and get_neutral() methods to the Spectrum class.

  • Fixed potential race condition when the same FASTA or GFF files are unzipped simultaneously.

  • Use approximate equality instead of strict identity when looking up precomputed values for the dominance coefficient h.

[1.2.1] - 2026-01-04#

  • Don’t average likelihood over bootstraps by default as it may mitigate optimization noise but is not statistically sound (see update_likelihood).

  • Set do_bootstrap flag to false by default for methods performing nested model comparison.

[1.2.0] - 2025-12-24#

  • Adding dominance coefficient h to DFE inference. h can either be fixed or inferred jointly with the DFE parameters. We can also introduce a relationship between h and S (see h_callback). When estimating h, precomputation over a grid of dominance coefficients takes some time. Implementation was validated with SLiM.

  • By default, parameters are now fixed to infer a semidominant (h=0.5) deleterious DFE without correcting for ancestral misidentification (eps=0).

  • Improved bootstrapping. By default, 2 runs are carried out per bootstrap sample and the most likely result is taken (see n_bootstrap_retries which previously controlled the number of retries in case of optimization failure). Bootstrapping is now also carried out by default (do_bootstrap), and mean and standard deviation across bootstraps are logged.

  • Initial optimization runs are now recorded in runs dataframe.

  • Added DFE class representing a frozen Parametrization.

  • Expanded documentation on SFS parsing and DFE inference.

  • Allow to specify how the point estimate is determined when plotting discretized DFE with confidence intervals (see point_estimate).

  • Refactored InferenceResult.

  • Refactored methods returning CIs. For example, removed get_cis_params_mle(), use get_errors_params_mle() instead.

[1.1.13] - 2025-11-22#

  • Fixed bootstrap issue where seeding caused unwanted correlation between the resampled neutral and selected SFS, which could result in smaller confidence intervals.

[1.1.12] - 2025-05-26#

  • Made cyvcf2 an optional dependency via fastdfe[vcf]

  • Added support for Conda

  • Improved x-axis labels for discretized DFE plots

  • Added support for introducing ancestral misidentification in Spectrum

  • Added unnormalized Watterson’s theta property

[1.1.11] - 2025-03-30#

  • Support for passing alternative optimizer to BaseInference and JointInference.

[1.1.10] - 2025-03-25#

  • Allow for probabilistic polarization when parsing SFS by looking at ancestral allele probability VCF info tag

  • Allow the transition/transversion ratio in the K2SubstitutionModel to be fixed to the value observed in the data

  • Adjust LRTs to account for parameters near boundaries. The resulting p-values are similar but tend to be somewhat lower

  • Extend ExistingOutgroupFiltration so that number of missing outgroups can be specified

  • Add RandomStratification and ContigFiltration classes

[1.1.9] - 2025-01-01#

  • Add simulation class for simulating SFS data with known DFE

[1.1.8] - 2024-08-14#

  • Update cyvcf2 dependency to fix broken wheel for Mac ARM (see issue)

  • Fix minor problem with remote files when disabling file caching

[1.1.7] - 2024-05-31#

  • Implement serialization of maximum likelihood ancestral annotation to allow for later inspection of results

  • Improved ancestral allele info tag information for site where annotation was not possible

[1.1.6] - 2024-04-20#

  • Lazy-load some modules to allow faster initial loading

[1.1.5] - 2024-03-12#

  • Support for Python 3.12

  • Exclude large files from distribution to speed up installation in R

[1.1.4] - 2024-03-05#

  • Lazy-load some modules to allow faster initial loading

[1.1.3] - 2023-12-27#

  • Implement probabilistic subsampling for ancestral allele annotation

[1.1.2] - 2023-11-27#

  • Improved bootstrapping

  • Set allow_divergence flag to false by default which as it has the potential to bias the SFS

[1.1.1] - 2023-11-21#

  • Probabilistic parsing of SFS

  • Functionality to subsample already existing SFS to lower sample size

  • Support for number of target sites for ancestral allele annotation

  • Improved parallelization when bootstrapping

  • New plotting functionalities

  • Improved logging

[1.1.0] - 2023-10-10#

  • Improved parsing utilities

  • Ancestral allele annotation with outgroups

[1.0.0] - 2023-08-12#

  • First stable release

Contents