met v1: Expanding on old estimations of biodiversityfrom eDNA with a new software framework

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: This is version 3 of this Preprint.

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Supplementary Files

David Molik 


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.



Bioinformatics, Computational Biology, Genetics and Genomics, Life Sciences


Database, genomics, metabarcode, metagenetic, metagenomic


Published: 2021-04-28 06:11

Last Updated: 2022-03-22 06:26

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CC-BY Attribution-NonCommercial 4.0 International