The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.

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Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study.

Arlequin ver 3.0 is a software package integrating several basic and advanced methods for population genetics data analysis, like the computation of standard genetic diversity indices, the estimation of allele and haplotype frequencies, tests of departure from linkage equilibrium, departure from selective neutrality and demographic equilibrium, estimation or parameters from past population expansions, and thorough analyses of population subdivision under the AMOVA framework. Arlequin 3 introduces a completely new graphical interface written in C++, a more robust semantic analysis of input files, and two new methods: a Bayesian estimation of gametic phase from multi-locus genotypes, and an estimation of the parameters of an instantaneous spatial expansion from DNA sequence polymorphism. Arlequin can handle several data types like DNA sequences, microsatellite data, or standard multi-locus genotypes. A Windows version of the software is freely available on http://cmpg.unibe.ch/software/arlequin3.

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Arlequin (version 3.0): An integrated software package for population genetics data analysis

Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

The Theory of Island Biogeography

Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.

We present STRUCTURE HARVESTER (available at http://taylor0.biology.ucla.edu/structureHarvester/
 ), a web-based program for collating results generated by the program STRUCTURE. The program provides a fast way to assess and visualize likelihood values across multiple values of K and hundreds of iterations for easier detection of the number of genetic groups that best fit the data. In addition, STRUCTURE HARVESTER will reformat data for use in downstream programs, such as CLUMPP.

STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method

/pdf/fstat-version-1-2-a-computer-program-to-calculate-f-2fjvw732br.pdf

FSTAT (Version 1.2): A Computer Program to Calculate F-Statistics

FSTAT, a Program to Estimate and Test Gene Diversities and Fixation Indices (Version 2.9. 3)

The package hierfstat for the statistical software r , created by the R Development Core Team, allows the estimate of hierarchical F -statistics from a hierarchy with any numbers of levels. In addition, it allows testing the statistical significance of population differentiation for these different levels, using a generalized likelihood-ratio test. The package hierfstat is available at http://www.unil.ch/popgen/softwares/hierfstat.htm.

/pdf/hierfstat-a-package-for-r-to-compute-and-test-hierarchical-f-104qnz7usk.pdf

HIERFSTAT , a package for R to compute and test hierarchical F -statistics

We examine the power of different exact tests of differentiation for diploid populations. Since there is not necessarily random mating within populations, the appropriate hypothesis to construct exact tests is that of independent sampling of genotypes. There are two categories of tests, Fsrestimator tests and goodness of fit tests. In this latter category, we distinguish “allelic statistics”, which account for the nature of alleles within genotypes, from “genotypic statistics” that do not. We show that the power of Fs+stimator tests and of allelic goodness of fit tests are similar when sampling is balanced, and higher than the power of genotypic goodness of fit tests. When sampling is unbalanced, the most powerful tests are shown to belong to the allelic goodness of fit group.

/pdf/testing-differentiation-in-diploid-populations-55lztpn7nt.pdf

Jérôme Goudet

Papers

Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study.

FSTAT (Version 1.2): A Computer Program to Calculate F-Statistics

FSTAT, a Program to Estimate and Test Gene Diversities and Fixation Indices (Version 2.9. 3)

HIERFSTAT , a package for R to compute and test hierarchical F -statistics

Testing differentiation in diploid populations