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adegenet

adegenet: a R Package for the Multivariate Analysis of Genetic Markers

This wiki is dedicated to the development of adegenet. It is relevant for developers of the package, developers of other packages depending on adegenet, and for users who want to be using the latest features as well.

The adegenet website is available at http://adegenet.r-forge.r-project.org/.

The following sections are available:

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Version

Install

install.packages('adegenet')

Monthly Downloads

9,262

Version

2.1.11

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/thibautjombart/adegenet

Maintainer

Zhian N. Kamvar

Last Published

February 6th, 2025

Functions in adegenet (2.1.11)

Conversion to class "SNPbin"

Genotype composition plot

Compute and optimize a-score for Discriminant Analysis of Principal Components (DAPC)

Conversion to class "genlight"

coords.monmonier

Returns original points in results paths of an object of class 'monmonier'

as methods in adegenet

Converting genind/genpop objects to other classes

adegenet.package

The adegenet package

Auxiliary functions

Auxiliary functions for adegenet

Represents a cloud of points with colors

Function to choose a connection network

Genetic distances between populations

Simulated data illustrating the DAPC

export_to_mvmapper

Export analysis for mvmapper visualisation

Extended HGDP-CEPH dataset

Discriminant Analysis of Principal Components (DAPC)

.internal_C_routines

Internal C routines

Convert a data.frame of allele data to a genind object.

Read large DNA alignments into R

Extract Single Nucleotide Polymorphism (SNPs) from alignments

Graphics for Discriminant Analysis of Principal Components (DAPC)

Conversion from a genind to a genpop object

Plotting genlight objects

find.cluster: cluster identification using successive K-means

Principal Component Analysis for genlight objects

Genetic transitive graphs

adegenet formal class (S4) for individual genotypes

adegenet formal class (S4) for allele counts in populations

Formal class "genlight"

genlight auxiliary functions

Auxiliary functions for genlight objects

Toy hybrid dataset

Convert a genind object to a data.frame.

Inbreeding estimation

Likelihood-based estimation of inbreeding

Access and manipulate the population hierarchy for genind or genlight objects.

Represents a cloud of points with colors

Importing data from several softwares to a genind object

Simulation of simple genlight objects

Assess polymorphism in genind/genpop objects

Function hybridize takes two genind in inputs and generates hybrids individuals having one parent in both objects.

Compute allelic frequencies

Simulation of genealogies of haplotypes

initialize,genpop-method

genpop constructor

Boundary detection using Monmonier algorithm

Convert objects with obsolete classes into new objects

Microsatellites genotypes of 237 cats from 17 colonies of Nancy (France)

initialize,genind-method

genind constructor

Pairwise distance plots

Manipulate the population factor of genind objects.

Microsatellites genotypes of 15 cattle breeds

Identify mutations between DNA sequences

Reading Single Nucleotide Polymorphism data

Compute minor allele frequency

extract.PLINKmap

Reading PLINK Single Nucleotide Polymorphism data

Compute proportion of shared alleles

Reading data from STRUCTURE

propTyped-methods

Compute the proportion of typed elements

Pool several genotypes into a single dataset

Reading data from Fstat

SequencesToGenind

Importing data from an alignement of sequences to a genind object

SeqTrack algorithm for reconstructing genealogies

Reading data from Genepop

Reading data from GENETIX

Separate data per locus

Select genotypes of well-represented populations

Separate genotypes per population

Compute scaled allele frequencies

Simulated genotypes of two georeferenced populations

Maximum-likelihood genetic clustering using EM algorithm

Microsatellites genotypes of 335 chamois (Rupicapra rupicapra) from the Bauges mountains (France)

Identification of structural SNPs

Spatial principal component analysis

Simulated data illustrating the sPCA

Analyse the position of polymorphic sites

snapclust.choose.k

Choose the number of clusters for snapclust using AIC, BIC or AICc

Monte Carlo test for sPCA

Access and manipulate the population strata for genind or genlight objects.

Global and local tests

Adegenet servers

Web servers for adegenet

When you need a break...

Microsatellites genotypes of 781 swallowtail butterflies from 40 populations in Alberta and British Columbia, Canada

Functions to access online resources for adegenet

DAPC cross-validation

Cross-validation for Discriminant Analysis of Principal Components (DAPC)

Access allele counts or frequencies

Restore true labels of an object

Virtual classes for adegenet

Compute Akaike Information Criterion (AIC) for snapclust

Formal class "SNPbin"

Compute Akaike Information Criterion for small samples (AICc) for snapclust

Expected heterozygosity (Hs)

Compute Akaike Information Criterion for small samples (AICc) for snapclust

Test differences in expected heterozygosity (Hs)

Compute Bayesian Information Criterion (BIC) for snapclust

Seasonal influenza (H3N2) HA segment data

Accessors for adegenet objects

HWE.test.genind

Hardy-Weinberg Equilibrium test for multilocus data