GGoutlieR: Identify Individuals with Unusual Geo-Genetic Patterns
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 + fileLICENSE |
| NeedsCompilation: | no |
| In views: | AnomalyDetection |
| CRAN checks: | GGoutlieR results |
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