Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.06.240754v1?rss=1 Authors: Ward, C. M., Ludington, A. J., Breen, J., Baxter, S. W. Abstract: 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. dXY, {pi}, FST) and admixture (f4, fd) 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. Copy rights belong to original authors. Visit the link for more info