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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

VersionRepositoryFileSize
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

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