The analysis and interpretation of datasets generated through sequencing large numbers of individual genomes is becoming commonplace in population and evolutionary genetic studies. Here we introduce geaR, a modular R package for evolutionary analysis of genome-wide genotype data. The package leverages the Genomic Data Structure (GDS) format, which enables memory and time efficient querying of genotype datasets compared to standard VCF genotype files. geaR utilizes GRange object classes to partition an analysis based on features from GFF annotation files, select codons based on position or degeneracy, and construct both positional and coordinate genomic windows. Tests of genetic diversity (eg. d_XY, π, F_ST) and admixture (f₄, f_d) along with tree building and sequence output, can be carried out on partitions using a single function regardless of sample ploidy or number of observed alleles. The package and associated documentation are available on GitHub at https://github.com/CMWbio/geaR.

中文翻译：

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使用geaR在R中进行基因组进化分析。

通过对大量单个基因组进行测序而生成的数据集的分析和解释在人口和进化遗传研究中变得司空见惯。在这里，我们介绍geaR，这是一种模块化R包，用于对全基因组基因型数据进行进化分析。该软件包利用了基因组数据结构（GDS）格式，与标准VCF基因型文件相比，该格式能够对基因型数据集进行内存和时间高效的查询。geaR利用GRange对象类基于GFF批注文件中的特征对分析进行分区，根据位置或简并性选择密码子，并构建位置和坐标基因组窗口。遗传多样性（例如d _XY，π，F _ST）和混合物（f ₄，f _d）以及树的构建和序列输出，可以使用单个功能在分区上执行操作，而与样本倍性或观察到的等位基因数量无关。该软件包和相关文档可从GitHub上的https://github.com/CMWbio/geaR获得。