CEGA: a method for inferring natural selection by comparative population genomic analysis across species

作者：Shilei Zhao, Lianjiang Chi, Hua Chen · 发表于：Genome biology · 年份：2023 · DOI：10.1186/s13059-023-03068-8 · 被引用次数：7 · 研究领域：Genetic Mapping and Diversity in Plants and Animals、Genetic and phenotypic traits in livestock、Genetic diversity and population structure

We developed maximum likelihood method for detecting positive selection or balancing selection using multilocus or genomic polymorphism and divergence data from two species. The method is especially useful for investigating natural selection in noncoding regions. Simulations demonstrate that the method outperforms existing methods in detecting both positive and balancing selection. We apply the method to population genomic data from human and chimpanzee. The list of genes identified under selection in the noncoding regions is prominently enriched in pathways related to the brain and nervous system. Therefore, our method will serve as a useful tool for comparative population genomic analysis.