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
Author: Che-Wei Chang ORCID iD [aut, cre], Karl Schmid ORCID iD [ths]
Maintainer: Che-Wei Chang <cheweichang92 at gmail.com>
License: MIT + file LICENSE
NeedsCompilation: no
CRAN checks: GGoutlieR results

Documentation:

Reference manual: GGoutlieR.pdf

Downloads:

Package source: GGoutlieR_1.0.2.tar.gz
Windows binaries: r-devel: GGoutlieR_1.0.2.zip, r-release: GGoutlieR_1.0.2.zip, r-oldrel: GGoutlieR_1.0.2.zip
macOS binaries: r-release (arm64): GGoutlieR_1.0.2.tgz, r-oldrel (arm64): GGoutlieR_1.0.2.tgz, r-release (x86_64): GGoutlieR_1.0.2.tgz
Old sources: GGoutlieR archive

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