Identify Individuals with Unusual Geo-Genetic Patterns R package GGoutlieR version 1.0.2 CRAN Task View: AnomalyDetection (https://CRAN.R-project.org/view=AnomalyDetection) Identify and visualize individuals with unusual association patterns of genetics and geography using the approach of Chang and Schmid (2023) <doi:10.1101/2023.04.06.535838>. It detects potential outliers that violate the isolation-by-distance assumption using the K-nearest neighbor approach. You can obtain a table of outliers with statistics and visualize unusual geo-genetic patterns on a geographical map. This is useful for landscape genomics studies to discover individuals with unusual geography and genetics associations from a large biological sample. Software Depends: R (>= 3.5.0) Imports: stats4, FastKNN, foreach, doParallel, parallel, scales, RColorBrewer, ggforce, rlang, stats, tidyr, utils, rnaturalearth, sf, ggplot2, cowplot Suggests: rnaturalearthdata Che-Wei Chang <cheweichang92@gmail.com> Comprehensive R Archive Network (CRAN) Che-Wei Chang [aut, cre] (ORCID: <https://orcid.org/0000-0001-6704-3732>), Karl Schmid [ths] (ORCID: <https://orcid.org/0000-0001-5129-895X>) MIT + file LICENSE (https://CRAN.R-project.org/package=GGoutlieR/LICENSE) 2023-10-15 application/tgz https://CRAN.R-project.org/package=GGoutlieR doi:10.32614/CRAN.package.GGoutlieR