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.
Version: 1.0.2 Depends: R (≥ 3.5.0) Imports: stats4, FastKNN, foreach, doParallel, parallel, scales, RColorBrewer, ggforce, rlang, stats, tidyr, utils, rnaturalearth, sf, ggplot2, cowplot Suggests: rnaturalearthdata Published: 2023-10-15 DOI: 10.32614/CRAN.package.GGoutlieR Author: Che-Wei Chang [aut, cre], Karl Schmid [ths] Maintainer: Che-Wei Chang <cheweichang92 at gmail.com> License: MIT + file LICENSE NeedsCompilation: no CRAN checks: GGoutlieR results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=GGoutlieR to link to this page.
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