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DiveRsity: An R package for the estimation and exploration of population genetics parameters and their associated errors

TLDR
A new R package, diveRsity, for the calculation of various diversity statistics, including common diversity partitioning statistics (θ, GST) and population differentiation statistics (DJost, GST ' , χ2 test for population heterogeneity), among others.
Abstract
Summary We present a new R package, diveRsity, for the calculation of various diversity statistics, including common diversity partitioning statistics (θ, GST) and population differentiation statistics (DJost, GST ', χ2 test for population heterogeneity), among others. The package calculates these estimators along with their respective bootstrapped confidence intervals for loci, sample population pairwise and global levels. Various plotting tools are also provided for a visual evaluation of estimated values, allowing users to critically assess the validity and significance of statistical tests from a biological perspective. diveRsity has a set of unique features, which facilitate the use of an informed framework for assessing the validity of the use of traditional F-statistics for the inference of demography, with reference to specific marker types, particularly focusing on highly polymorphic microsatellite loci. However, the package can be readily used for other co-dominant marker types (e.g. allozymes, SNPs). Detailed examples of usage and descriptions of package capabilities are provided. The examples demonstrate useful strategies for the exploration of data and interpretation of results generated by diveRsity. Additional online resources for the package are also described, including a GUI web app version intended for those with more limited experience using R for statistical analysis.

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References
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Journal ArticleDOI

Estimating F-statistics for the analysis of population structure.

TL;DR: The purpose of this discussion is to offer some unity to various estimation formulae and to point out that correlations of genes in structured populations, with which F-statistics are concerned, are expressed very conveniently with a set of parameters treated by Cockerham (1 969, 1973).
Journal ArticleDOI

G(ST) and its relatives do not measure differentiation.

Lou Jost
- 01 Sep 2008 - 
TL;DR: G ST and its relatives are often interpreted as measures of differentiation between subpopulations, with values near zero supposedly indicating low differentiation, but GST necessarily approaches zero when gene diversity is high, and it is not monotonic with increasing differentiation.
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A practical solution to the pervasive problems of p values.

TL;DR: The BIC provides an approximation to a Bayesian hypothesis test, does not require the specification of priors, and can be easily calculated from SPSS output.
Journal ArticleDOI

genotype and genodive: two programs for the analysis of genetic diversity of asexual organisms

TL;DR: Two programs, GENOTYPE and GENODIVE, developed for analyses of clonal diversity in asexually reproducing organisms, show that genotype can be used for detecting genotyping errors in studies of sexual organisms.
Related Papers (5)
Trending Questions (1)
How can pairwise differences be used to estimate genetic diversity in loci?

Pairwise differences can be used to calculate diversity statistics such as θ and GST, and to assess population differentiation using statistics like DJost and χ2 test.