The article introduces pegas, an R package for population genetics that integrates with existing R packages (ape and adegenet) to provide a unified framework for analyzing population genetic data. pegas is written in R, ensuring portability across operating systems and requiring a standard R installation and two additional packages. It offers functions for standard population genetic methods and low-level functions for developing new methods. The package uses R's flexible data structures, including the 'loci' class for storing genetic data and the 'haplotype' class for managing haplotype data. The 'loci' class allows for efficient computation of genotypic and allelic frequencies, while the 'haplotype' class links haplotypes to individual data. pegas handles missing data explicitly and provides tools for reading and writing data files. It includes standard population genetic analyses such as Hardy–Weinberg equilibrium, FST, analysis of molecular variance, haplotype networks, and Tajima's D and R2 tests. The package also includes functions for coalescent analysis and maximum likelihood estimation. pegas emphasizes an integrated-modular approach for population genetic data analysis, complementing adegenet and ape in providing spatial, multivariate, and basic population genetic analysis tools. The package is distributed through CRAN and includes a tutorial for data input. pegas leverages R's graphical capabilities for visualizing data, such as haplotype networks. The article highlights the importance of an integrated approach for population genetic data analysis and the potential of R as a unified framework for bioinformatics and phylogenetics.The article introduces pegas, an R package for population genetics that integrates with existing R packages (ape and adegenet) to provide a unified framework for analyzing population genetic data. pegas is written in R, ensuring portability across operating systems and requiring a standard R installation and two additional packages. It offers functions for standard population genetic methods and low-level functions for developing new methods. The package uses R's flexible data structures, including the 'loci' class for storing genetic data and the 'haplotype' class for managing haplotype data. The 'loci' class allows for efficient computation of genotypic and allelic frequencies, while the 'haplotype' class links haplotypes to individual data. pegas handles missing data explicitly and provides tools for reading and writing data files. It includes standard population genetic analyses such as Hardy–Weinberg equilibrium, FST, analysis of molecular variance, haplotype networks, and Tajima's D and R2 tests. The package also includes functions for coalescent analysis and maximum likelihood estimation. pegas emphasizes an integrated-modular approach for population genetic data analysis, complementing adegenet and ape in providing spatial, multivariate, and basic population genetic analysis tools. The package is distributed through CRAN and includes a tutorial for data input. pegas leverages R's graphical capabilities for visualizing data, such as haplotype networks. The article highlights the importance of an integrated approach for population genetic data analysis and the potential of R as a unified framework for bioinformatics and phylogenetics.