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This is a Preprint and has not been peer reviewed.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: https://doi.org/10.1093/database/baac032. This is version 3 of this Preprint.

Add a Comment

You must log in to post a comment.


Comments

There are no comments or no comments have been made public for this article.

Downloads

Download Preprint

Supplementary Files
Authors

David Molik 

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.

DOI

https://doi.org/10.32942/osf.io/rwnd3

Subjects

Bioinformatics, Computational Biology, Genetics and Genomics, Life Sciences

Keywords

Database, genomics, metabarcode, metagenetic, metagenomic

Dates

Published: 2021-04-27 23:11

Last Updated: 2022-03-21 22:26

Older Versions
License

CC-BY Attribution-NonCommercial 4.0 International