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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.2 |
rolling source/ R- | GGoutlieR_1.0.2.tar.gz |
284.0 KiB |
1.0.2 |
rolling linux/jammy R-4.5 | GGoutlieR_1.0.2.tar.gz |
469.3 KiB |
1.0.2 |
rolling linux/noble R-4.5 | GGoutlieR_1.0.2.tar.gz |
469.3 KiB |
1.0.2 |
latest source/ R- | GGoutlieR_1.0.2.tar.gz |
284.0 KiB |
1.0.2 |
latest linux/jammy R-4.5 | GGoutlieR_1.0.2.tar.gz |
469.3 KiB |
1.0.2 |
latest linux/noble R-4.5 | GGoutlieR_1.0.2.tar.gz |
469.3 KiB |
1.0.2 |
2026-04-23 source/ R- | GGoutlieR_1.0.2.tar.gz |
284.0 KiB |
1.0.2 |
2026-04-09 windows/windows R-4.5 | GGoutlieR_1.0.2.zip |
472.4 KiB |
1.0.2 |
2025-04-20 source/ R- | GGoutlieR_1.0.2.tar.gz |
284.0 KiB |