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multi‐dice: r package for comparative population genomic inference under hierarchical co‐demographic models of independent single‐population size changes

机译:多骰子:在独立的单人口规模变化的分层共人口模型下用于比较人群基因组推断的r包

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摘要

Population genetic data from multiple taxa can address comparative phylogeographic questions about community‐scale response to environmental shifts, and a useful strategy to this end is to employ hierarchical co‐demographic models that directly test multi‐taxa hypotheses within a single, unified analysis. This approach has been applied to classical phylogeographic data sets such as mitochondrial barcodes as well as reduced‐genome polymorphism data sets that can yield 10,000s of SNPs, produced by emergent technologies such as RAD‐seq and GBS. A strategy for the latter had been accomplished by adapting the site frequency spectrum to a novel summarization of population genomic data across multiple taxa called the aggregate site frequency spectrum (aSFS), which potentially can be deployed under various inferential frameworks including approximate Bayesian computation, random forest and composite likelihood optimization. Here, we introduce the r package multi‐dice, a wrapper program that exploits existing simulation software for flexible execution of hierarchical model‐based inference using the aSFS, which is derived from reduced genome data, as well as mitochondrial data. We validate several novel software features such as applying alternative inferential frameworks, enforcing a minimal threshold of time surrounding co‐demographic pulses and specifying flexible hyperprior distributions. In sum, multi‐dice provides comparative analysis within the familiar R environment while allowing a high degree of user customization, and will thus serve as a tool for comparative phylogeography and population genomics.
机译:来自多个分类单元的种群遗传数据可以解决有关社区规模对环境变化的反应的比较系统地理学问题,为此,一种有用的策略是采用分层的共同人口统计学模型在单个统一分析中直接测试多分类单元假设。该方法已应用于经典的地理学数据集(例如线粒体条形码)以及可产生10,000个SNP的简化基因组多态性数据集,这些数据集是由RAD-seq和GBS等新兴技术产生的。后者的策略是通过使站点频谱适应跨多个类群的种群基因组数据的新颖汇总而完成的,称为汇总站点频谱(aSFS),可以潜在地在各种推断框架下进行部署,包括近似贝叶斯计算,随机森林和复合似然优化。在这里,我们介绍了r包multi-dice,这是一个包装程序,该程序利用现有的仿真软件来使用aSFS灵活执行基于层次模型的推理,该aSFS源自简化的基因组数据以及线粒体数据。我们验证了几种新颖的软件功能,例如应用替代推理框架,对围绕人口统计学脉冲的时间实施最小阈值并指定灵活的超先验分布。总而言之,多骰子可在熟悉的R环境中提供比较分析,同时允许高度的用户自定义,因此将成为比较系统地理学和种群基因组学的工具。

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