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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

14,047

Version

2.1.8

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/thibautjombart/adegenet

Maintainer

Zhian N. Kamvar

Last Published

October 2nd, 2022

Functions in adegenet (2.1.8)

Expected heterozygosity (Hs)

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

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

Test differences in expected heterozygosity (Hs)

Accessors for adegenet objects

Seasonal influenza (H3N2) HA segment data

HWE.test.genind

Hardy-Weinberg Equilibrium test for multilocus data

Genotype composition plot

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

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

Auxiliary functions

Auxiliary functions for adegenet

adegenet.package

The adegenet package

Conversion to class "SNPbin"

Conversion to class "genlight"

Function to choose a connection network

Represents a cloud of points with colors

Extract Single Nucleotide Polymorphism (SNPs) from alignments

Read large DNA alignments into R

Extended HGDP-CEPH dataset

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

Simulated data illustrating the DAPC

.internal_C_routines

Internal C routines

Genetic distances between populations

Discriminant Analysis of Principal Components (DAPC)

Graphics for Discriminant Analysis of Principal Components (DAPC)

export_to_mvmapper

Export analysis for mvmapper visualisation

Principal Component Analysis for genlight objects

Plotting genlight objects

adegenet formal class (S4) for allele counts in populations

genlight auxiliary functions

Auxiliary functions for genlight objects

Convert a genind object to a data.frame.

adegenet formal class (S4) for individual genotypes

Formal class "genlight"

Genetic transitive graphs

Conversion from a genind to a genpop object

Toy hybrid dataset

find.cluster: cluster identification using successive K-means

Importing data from several softwares to a genind object

Represents a cloud of points with colors

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

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

Simulation of simple genlight objects

Pairwise distance plots

Identify mutations between DNA sequences

Boundary detection using Monmonier algorithm

Compute allelic frequencies

Simulation of genealogies of haplotypes

Manipulate the population factor of genind objects.

Assess polymorphism in genind/genpop objects

Inbreeding estimation

Likelihood-based estimation of inbreeding

Microsatellites genotypes of 15 cattle breeds

Compute minor allele frequency

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

initialize,genind-method

genind constructor

extract.PLINKmap

Reading PLINK Single Nucleotide Polymorphism data

Reading Single Nucleotide Polymorphism data

Reading data from Fstat

Reading data from STRUCTURE

Reading data from Genepop

Reading data from GENETIX

Adegenet servers

Web servers for adegenet

propTyped-methods

Compute the proportion of typed elements

SeqTrack algorithm for reconstructing genealogies

Pool several genotypes into a single dataset

SequencesToGenind

Importing data from an alignement of sequences to a genind object

initialize,genpop-method

genpop constructor

Compute proportion of shared alleles

Convert objects with obsolete classes into new objects

Separate data per locus

Select genotypes of well-represented populations

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

When you need a break...

Compute scaled allele frequencies

Separate genotypes per population

Identification of structural SNPs

Analyse the position of polymorphic sites

snapclust.choose.k

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

Spatial principal component analysis

Restore true labels of an object

Simulated genotypes of two georeferenced populations

Global and local tests

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

Maximum-likelihood genetic clustering using EM algorithm

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

Monte Carlo test for sPCA

Virtual classes for adegenet

Simulated data illustrating the sPCA

Access allele counts or frequencies

Functions to access online resources for adegenet

DAPC cross-validation

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

Formal class "SNPbin"

Compute Akaike Information Criterion (AIC) for snapclust

Compute Bayesian Information Criterion (BIC) for snapclust