Segmenting and Genotyping Large, Polymorphic Inversions

Abstract

Large, polymorphic inversions can contribute to population structure and enable mutually-exclusive adaptations to survive in the same population. Current methods for detecting inversions from single-nucleotide polymorphisms (SNPs) called from population genomics data require an experienced, human user to prepare the data and interpret the results. Ideally, these methods would be completely automated yet robust to allow usage by inexperienced users. Towards this goal, automated approaches for segmentation of inversions and inference of sample genotypes are introduced and evaluated on chromosomes from flies, mosquitoes, and prairie sunflowers.