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
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, r-oldrel (x86_64): GGoutlieR_1.0.2.tgz
Old sources:	GGoutlieR archive

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