Don’t make genetic data disposable: Best practices for genetic and genomic data archiving

This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.

Downloads

Download Preprint

Authors

Deborah M Leigh, Amy Vandergast, Maggie Hunter, Eric Crandall, W. Chris Funk, Collin J Garroway, Sean Hoban, Sara J Oyler-McCance, Christian Rellstab, Gernot Segelbacher, Chloe Schmidt, Ella Vázquez-Domínguez, Ivan Paz-Vinas

Abstract

In ecology and evolution, genetic and genomic data are commonly collected for a vast array of scientific and applied purposes. Despite mandates for public archiving, such data are typically used only once by the data-generating authors. The repurposing of genetic and genomic datasets remains uncommon because it is often difficult, if not impossible, due to non-standard archiving practices and lack of contextual metadata. But as the new research field of macrogenetics is demonstrating, if genetic data and their metadata were more accessible, they could be reused for many additional purposes, far beyond their initial intended impact. In this review, we outline the main challenges with existing genetic and genomic data archives, factors underlying the challenges, and current best practices for archiving genetic and genomic data. Recognising that this is a longstanding issue due to an absence of formal data management training within the research field of ecology and evolution, we highlight key steps that universities, funding bodies, and scientific publishers could take to ensure timely change towards good data archiving.

DOI

https://doi.org/10.32942/X29025

Subjects

Bioinformatics, Biology, Ecology and Evolutionary Biology, Genetics and Genomics, Life Sciences

Keywords

genetics, genomics, data archiving, Best practices, standardisation, ecology, evolution, open data

Dates

Published: 2023-09-25 20:29

Last Updated: 2023-09-26 00:29

License

CC-By Attribution-NonCommercial-NoDerivatives 4.0 International

Additional Metadata

Language:
English

Conflict of interest statement:
None

Data and Code Availability Statement:
Open data/code are not available before publication

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.