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EDENetworks: A user-friendly software to build and analyse networks in biogeography, ecology and population genetics

机译:EDENetworks:一种易于使用的软件,用于建立和分析生物地理学,生态学和种群遗传学中​​的网络

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摘要

The recent application of graph-based network theory analysis to biogeography, community ecology and population genetics has created a need for user-friendly software, which would allow a wider accessibility to and adaptation of these methods. EDENetworks aims to fill this void by providing an easy-to-use interface for the whole analysis pipeline of ecological and evolutionary networks starting from matrices of species distributions, genotypes, bacterial OTUs or populations characterized genetically. The user can choose between several different ecological distance metrics, such as Bray-Curtis or Sorensen distance, or population genetic metrics such as F-ST or Goldstein distances, to turn the raw data into a distance/dissimilarity matrix. This matrix is then transformed into a network by manual or automatic thresholding based on percolation theory or by building the minimum spanning tree. The networks can be visualized along with auxiliary data and analysed with various metrics such as degree, clustering coefficient, assortativity and betweenness centrality. The statistical significance of the results can be estimated either by resampling the original biological data or by null models based on permutations of the data.
机译:基于图的网络理论分析最近在生物地理学,社区生态学和种群遗传学中​​的应用产生了对用户友好软件的需求,该软件将允许更广泛地访问和适应这些方法。 EDENetworks旨在通过为生态和进化网络的整个分析流程提供一个易于使用的界面来填补这一空白,该网络从物种分布,基因型,细菌OTU或具有遗传特征的种群开始。用户可以在几个不同的生态距离度量(例如Bray-Curtis或Sorensen距离)或群体遗传度量(例如F-ST或Goldstein距离)之间进行选择,以将原始数据转换为距离/差异矩阵。然后根据基于渗流理论的手动或自动阈值或通过构建最小生成树,将此矩阵转换为网络。可以将网络与辅助数据一起可视化,并使用各种度量标准进行分析,例如程度,聚类系数,分类性和中间性。结果的统计显着性可以通过对原始生物数据进行重采样或通过基于数据排列的空模型来估计。

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