Compute Akaike Information Criterion (AIC) for snapclust
Expected heterozygosity (Hs)
Compute Akaike Information Criterion for small samples (AICc) for snapclust
Compute Bayesian Information Criterion (BIC) for snapclust
Compute Akaike Information Criterion for small samples (AICc) for snapclust
Hardy-Weinberg Equilibrium test for multilocus data
Accessors for adegenet objects
Test differences in expected heterozygosity (Hs)
Seasonal influenza (H3N2) HA segment data
Formal class "SNPbin"
Genotype composition plot
Function to choose a connection network
Conversion to class "SNPbin"
Compute and optimize a-score for Discriminant Analysis of Principal Components (DAPC)
Auxiliary functions for adegenet
Returns original points in results paths of an object of class 'monmonier'
Represents a cloud of points with colors
Conversion to class "genlight"
Converting genind/genpop objects to other classes
The adegenet package
Genetic distances between populations
Convert a data.frame of allele data to a genind object.
Simulated data illustrating the DAPC
Internal C routines
Read large DNA alignments into R
Extended HGDP-CEPH dataset
Discriminant Analysis of Principal Components (DAPC)
Graphics for Discriminant Analysis of Principal Components (DAPC)
Export analysis for mvmapper visualisation
Extract Single Nucleotide Polymorphism (SNPs) from alignments
adegenet formal class (S4) for individual genotypes
Formal class "genlight"
adegenet formal class (S4) for allele counts in populations
Genetic transitive graphs
genlight auxiliary functions
Auxiliary functions for genlight objects
Plotting genlight objects
Principal Component Analysis for genlight objects
Conversion from a genind to a genpop object
find.cluster: cluster identification using successive K-means
Convert a genind object to a data.frame.
Represents a cloud of points with colors
Function hybridize takes two genind in inputs
and generates hybrids individuals having one parent
in both objects.
Access and manipulate the population hierarchy for genind or genlight objects.
Toy hybrid dataset
Importing data from several softwares to a genind object
Simulation of simple genlight objects
Compute allelic frequencies
Likelihood-based estimation of inbreeding
Assess polymorphism in genind/genpop objects
Simulation of genealogies of haplotypes
Microsatellites genotypes of 237 cats from 17 colonies of Nancy (France)
Identify mutations between DNA sequences
Pairwise distance plots
genind constructor
Manipulate the population factor of genind objects.
Boundary detection using Monmonier algorithm
Microsatellites genotypes of 15 cattle breeds
Compute minor allele frequency
genpop constructor
Convert objects with obsolete classes into new objects
Microsatellites genotypes of 335 chamois (Rupicapra rupicapra) from the
Bauges mountains (France)
Pool several genotypes into a single dataset
Reading Single Nucleotide Polymorphism data
Reading data from STRUCTURE
Reading data from Genepop
Reading PLINK Single Nucleotide Polymorphism data
Reading data from GENETIX
Compute proportion of shared alleles
Reading data from Fstat
Web servers for adegenet
SeqTrack algorithm for reconstructing genealogies
Compute the proportion of typed elements
Maximum-likelihood genetic clustering using EM algorithm
Importing data from an alignement of sequences to a genind object
Simulated genotypes of two georeferenced populations
Select genotypes of well-represented populations
Separate data per locus
When you need a break...
Compute scaled allele frequencies
Separate genotypes per population
Microsatellites genotypes of 781 swallowtail butterflies from 40 populations in
Alberta and British Columbia, Canada
Analyse the position of polymorphic sites
Monte Carlo test for sPCA
Choose the number of clusters for snapclust using AIC, BIC or AICc
Identification of structural SNPs
Access and manipulate the population strata for genind or genlight objects.
Spatial principal component analysis
Cross-validation for Discriminant Analysis of Principal Components (DAPC)
Functions to access online resources for adegenet
Access allele counts or frequencies
Virtual classes for adegenet
Restore true labels of an object
Global and local tests
Simulated data illustrating the sPCA