Met v1: expanding on old estimations of biodiversity from eDNA with a new database framework. (11th May 2022)

• Record Type: Journal Article
• Authors: Molik, David C
• Is Part Of: Database. Volume 2022(2022)
• Publication Date: 2022-05-11
• Subjects: Biology -- Databases -- Periodicals; Bioinformatics -- Periodicals; 570.285
• DOI: 10.1093/database/baac032
• Languages: English
• ISSNs: 1758-0463

Abstract

Abstract: 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/