Author
François Rousset
Other affiliations: Institut de recherche pour le développement, Yale University, Centre national de la recherche scientifique
Bio: François Rousset is an academic researcher from University of Montpellier. The author has contributed to research in topics: Population & Biological dispersal. The author has an hindex of 67, co-authored 166 publications receiving 43803 citations. Previous affiliations of François Rousset include Institut de recherche pour le développement & Yale University.
Papers published on a yearly basis
Papers
More filters
15,729 citations
TL;DR: This note summarizes developments of the genepop software since its first description in 1995, and in particular those new to version 4.0: an extended input format, several estimators of neighbourhood size under isolation by distance, new estimators and confidence intervals for null allele frequency, and less important extensions to previous options.
Abstract: This note summarizes developments of the genepop software since its first description in 1995, and in particular those new to version 4.0: an extended input format, several estimators of neighbourhood size under isolation by distance, new estimators and confidence intervals for null allele frequency, and less important extensions to previous options. genepop now runs under Linux as well as under Windows, and can be entirely controlled by batch calls.
8,171 citations
TL;DR: In this paper, the use of isolation by distance models as a basis for the estimation of demographic parameters from measures of population subdivision was re-examined, and the results for values of F-statistics in one-dimensional models and coalescence times in 2D models were provided.
Abstract: I reexamine the use of isolation by distance models as a basis for the estimation of demographic parameters from measures of population subdivision. To that aim, I first provide results for values of F-statistics in one-dimensional models and coalescence times in two-dimensional models, and make more precise earlier results for F-statistics in two-dimensional models and coalescence times in one-dimensional models. Based on these results, I propose a method of data analysis involving the regression of F(ST)/(1 - F(ST)) estimates for pairs of subpopulations on geographic distance for populations along linear habitats or logarithm of distance for populations in two-dimensional habitats. This regression provides in principle an estimate of the product of population density and second moment of parental axial distance. In two cases where comparison to direct estimates is possible, the method proposed here is more satisfactory than previous indirect methods.
3,331 citations
3,026 citations
TL;DR: The power of FST-estimator tests and of allelic goodness offit tests are similar when sampling is balanced, and higher than the power of genotypic goodness of fit tests.
Abstract: 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.
1,293 citations
Cited by
More filters
TL;DR: Arlequin ver 3.0 as discussed by the authors 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.
Abstract: 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.
14,271 citations
Journal Article•
TL;DR: It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.
11,521 citations
TL;DR: MICRO - CHECKER estimates the frequency of null alleles and, importantly, can adjust the allele and genotype frequencies of the amplified alleles, permitting their use in further population genetic analysis.
Abstract: DNA degradation, low DNA concentrations and primer-site mutations may result in the incorrect assignment of microsatellite genotypes, potentially biasing population genetic analyses. MICRO - CHECKER is WINDOWS ®-based software that tests the genotyping of microsatellites from diploid populations. The program aids identification of genotyping errors due to nonamplified alleles (null alleles), short allele dominance (large allele dropout) and the scoring of stutter peaks, and also detects typographic errors. MICRO - CHECKER estimates the frequency of null alleles and, importantly, can adjust the allele and genotype frequencies of the amplified alleles, permitting their use in further population genetic analysis. MICRO CHECKER can be freely downloaded from http://www.microchecker.hull.ac.uk/.
9,953 citations
Journal Article•
TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to
9,847 citations
[...]
TL;DR: GenAlEx: Genetic Analysis in Excel is a cross-platform package for population genetic analyses that runs within Microsoft Excel that offers analysis of diploid codominant, haploid and binary genetic loci and DNA sequences.
Abstract: Summary: GenAlEx: Genetic Analysis in Excel is a cross-platform package for population genetic analyses that runs within Microsoft Excel. GenAlEx offers analysis of diploid codominant, haploid and binary genetic loci and DNA sequences. Both frequency-based (F-statistics, heterozygosity, HWE, population assignment, relatedness) and distance-based (AMOVA, PCoA, Mantel tests, multivariate spatial autocorrelation) analyses are provided. New features include calculation of new estimators of population structure: G′ST, G′′ST, Jost’s Dest and F′ST through AMOVA, Shannon Information analysis, linkage disequilibrium analysis for biallelic data and novel heterogeneity tests for spatial autocorrelation analysis. Export to more than 30 other data formats is provided. Teaching tutorials and expanded step-by-step output options are included. The comprehensive guide has been fully revised.
Availability and implementation: GenAlEx is written in VBA and provided as a Microsoft Excel Add-in (compatible with Excel 2003, 2007, 2010 on PC; Excel 2004, 2011 on Macintosh). GenAlEx, and supporting documentation and tutorials are freely available at: http://biology.anu.edu.au/GenAlEx.
Contact: rod.peakall@anu.edu.au
9,564 citations