The gstudio package provides a comprehensive set of tools for the spatial analysis of genetic marker data in R. Originally developed to support research in landscape genetics and population genomics, it offers a unified framework for estimating genetic diversity, population structure, inter-individual and inter-population distances, relatedness, and population graph topology.
At the core of the package is the locus S3 class, a flexible representation of genotypes that supports codominant markers, SNPs, AFLPs, and allozymes. Built around this data type, gstudio provides four main analytical entry points — genetic_diversity(), genetic_structure(), genetic_distance(), and genetic_relatedness() — each dispatching to a range of estimators. Population Graphs, a graph-theoretic approach to understanding among-population connectivity (Dyer & Nason 2004), are fully integrated with construction, analysis, and visualization tools.
Who This Book Is For
This book is intended for population geneticists, landscape ecologists, and conservation biologists who want to analyze genetic marker data in R. It assumes basic familiarity with R and introductory population genetics concepts.
How to Use This Book
Each chapter is self-contained and can be read independently, though they build on each other sequentially. Code examples use live R execution, so you can follow along by running the code in your own R session.
The arapat dataset contains multilocus microsatellite genotypes from the cactus beetle Araptus attenuatus and will serve as the primary example dataset throughout this book.
# Preface {.unnumbered}The `gstudio` package provides a comprehensive set of tools for the spatial analysis of genetic marker data in R. Originally developed to support research in landscape genetics and population genomics, it offers a unified framework for estimating genetic diversity, population structure, inter-individual and inter-population distances, relatedness, and population graph topology.At the core of the package is the `locus` S3 class, a flexible representation of genotypes that supports codominant markers, SNPs, AFLPs, and allozymes. Built around this data type, `gstudio` provides four main analytical entry points --- `genetic_diversity()`, `genetic_structure()`, `genetic_distance()`, and `genetic_relatedness()` --- each dispatching to a range of estimators. Population Graphs, a graph-theoretic approach to understanding among-population connectivity (Dyer & Nason 2004), are fully integrated with construction, analysis, and visualization tools.## Who This Book Is ForThis book is intended for population geneticists, landscape ecologists, and conservation biologists who want to analyze genetic marker data in R. It assumes basic familiarity with R and introductory population genetics concepts.## How to Use This BookEach chapter is self-contained and can be read independently, though they build on each other sequentially. Code examples use live R execution, so you can follow along by running the code in your own R session.## Quick Start```{r}library(gstudio)data(arapat)str(arapat, max.level =1)```The `arapat` dataset contains multilocus microsatellite genotypes from the cactus beetle *Araptus attenuatus* and will serve as the primary example dataset throughout this book.```{r}head(arapat)```## CitationIf you use `gstudio` in your research, please cite:> Dyer, R.J. 2009. GStudio: a suite of tools for the spatial analysis of genetic marker data. Molecular Ecology Resources 9(1): 110-113.## Source CodeThe source code for `gstudio` is available on GitHub at <https://github.com/dyerlab/gstudio>.