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: |
1.0.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
geosphere, stats4, FastKNN, foreach, doParallel, iterators, parallel, rworldmap, scales, plotrix, mapplots, RColorBrewer, rworldxtra, dichromat, sp |
| Published: |
2023-06-09 |
| 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 |
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