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Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows

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TLDR
The main innovations of the new version of the Arlequin program include enhanced outputs in XML format, the possibility to embed graphics displaying computation results directly into output files, and the implementation of a new method to detect loci under selection from genome scans.
Abstract
We present here a new version of the Arlequin program available under three different forms: a Windows graphical version (Winarl35), a console version of Arlequin (arlecore), and a specific console version to compute summary statistics (arlsumstat). The command-line versions run under both Linux and Windows. The main innovations of the new version include enhanced outputs in XML format, the possibility to embed graphics displaying computation results directly into output files, and the implementation of a new method to detect loci under selection from genome scans. Command-line versions are designed to handle large series of files, and arlsumstat can be used to generate summary statistics from simulated data sets within an Approximate Bayesian Computation framework.

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Citations
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Journal ArticleDOI

Phylogeography of Quercus glauca (Fagaceae), a dominant tree of East Asian subtropical evergreen forests, based on three chloroplast DNA interspace sequences

TL;DR: Haplotype spatial distribution, ENM, mismatch distribution, and neutrality tests suggest that Q. glauca in Southeast China experiences expansion, and the current distribution in region III might be shaped by southward expansion from regions I and II after last glacial maximum (LGM).
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Spatially explicit models of dynamic histories: examination of the genetic consequences of Pleistocene glaciation and recent climate change on the American Pika

TL;DR: The results support that the inclusion of a spatiotemporal dynamic is an important factor when studying the impact of distributional shifts on patterns of genetic data and demonstrate the utility of SDMs to generate species‐specific predictions about patterns of Genetic variation that account for varying degrees of habitat specialization and life history characteristics of taxa.
References
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Journal ArticleDOI

PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses

TL;DR: This work introduces PLINK, an open-source C/C++ WGAS tool set, and describes the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation, which focuses on the estimation and use of identity- by-state and identity/descent information in the context of population-based whole-genome studies.
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Arlequin (version 3.0): An integrated software package for population genetics data analysis

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.
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Sequencing technologies-the next generation

TL;DR: A technical review of template preparation, sequencing and imaging, genome alignment and assembly approaches, and recent advances in current and near-term commercially available NGS instruments is presented.
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Evaluating Loci for Use in the Genetic Analysis of Population Structure

TL;DR: It is suggested that genetic variation at a discrepant locus, Identified under these conditions, is likely to have been influenced by natural selection, either acting on the locus itself or at a closely linked locus.
Journal ArticleDOI

Detection of reduction in population size using data from microsatellite loci.

TL;DR: It is demonstrated that the mean ratio of the number of alleles to the range in allele size, which is calculated from a population sample of microsatellite loci, can be used to detect reductions in population size and that the value of M consistently predicts the reported demographic history for these populations.
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