Navari Family Center for Digital Scholarship, Hesburgh Library, University of Notre Dame, Notre Dame, IN 46556, USA.
Department of Biological Sciences, Galvin Life Science Center, University of Notre Dame, Notre Dame, IN 46556, USA.
Database (Oxford). 2022 May 11;2022. doi: 10.1093/database/baac032.
A long-standing problem in environmental DNA has been the inability to compute across large number of datasets. Here we introduce an open-source software framework that can store a large number of environmental DNA datasets, as well as provide a platform for analysis, in an easily customizable way. We show the utility of such an approach by analyzing over 1400 arthropod metabarcode datasets. This article introduces a new software framework, met, which utilizes large numbers of metabarcode datasets to draw conclusions about patterns of diversity at large spatial scales. Given more accurate estimations on the distribution of variance in metabarcode datasets, this software framework could facilitate novel analyses that are outside the scope of currently available similar platforms. Database URL https://osf.io/spb8v/.
环境 DNA 长期存在的一个问题是无法跨大量数据集进行计算。在这里，我们引入了一个开源软件框架，该框架可以以一种易于定制的方式存储大量环境 DNA 数据集，并为分析提供一个平台。我们通过分析超过 1400 个节肢动物代谢条形码数据集来展示这种方法的实用性。本文介绍了一个新的软件框架 met，它利用大量代谢条形码数据集来得出关于大空间尺度多样性模式的结论。如果对代谢条形码数据集的方差分布有更准确的估计，那么这个软件框架可以促进目前类似平台无法实现的新分析。数据库网址：https://osf.io/spb8v/。
