BalLeRMix +: mixture model approaches for robust joint identification of both positive selection and long-term balancing selection

Abstract

Summary: The growing availability of genomewide polymorphism data has fueled interest in detecting diverse selective processes affecting population diversity. However, no model-based approaches exist to jointly detect and distinguish the two complementary processes of balancing and positive selection. We extend the BalLeRMix B-statistic framework described in Cheng and DeGiorgio (2020) for detecting balancing selection and present BalLeRMix+, which implements five B statistic extensions based on mixture models to robustly identify both types of selection. BalLeRMix+ is implemented in Python and computes the composite likelihood ratios and associated model parameters for each genomic test position.

Availability and implementation: BalLeRMix+ is freely available at https://github.com/bioXiaoheng/BallerMixPlus.

Supplementary information: Supplementary data are available at Bioinformatics online.