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 + file LICENSE |
| NeedsCompilation: |
no |
| In views: |
AnomalyDetection |
| CRAN checks: |
GGoutlieR results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=GGoutlieR
to link to this page.