GGoutlieR: an R package to identify and visualize unusual geo-genetic patterns of biological samples

Landscape genomics is an emerging field of research that integrates genomic and environmental information to explore the drivers of evolution. Reliable data on the geographical origin of biological samples is a prerequisite for accurate landscape genomics studies. Traditionally, researchers discover potentially questionable samples using visualization-based tools. However, such approaches cannot handle large sample sizes due to overlapping data points on a graph and can hinder reproducible research. To address this shortcoming, we developed Geo-Genetic outlier (GGoutlieR), an R package of a heuristic framework for detecting and visualizing samples with unusual geo-genetic patterns. Outliers are identified by calculating empirical p-values for each sample, allowing users to identify them in data sets with thousands of samples. The package also provides a plotting function to display the geo-genetic patterns of outliers on a geographical map. GGoutlieR could significantly reduce the amount of data cleaning that researchers need to do before carrying out landscape genomics analyses.