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Qiime2 classifiers (rbcl, Mollusc 18s) for testing the validity of using eDNA for carbon origin analysis from sediment cores

<p>Qiime2 formatted classifiers that were created for a Natural England funded project by researchers at the James Hutton Institute. The pilot project aims to test the validity of using eDNA for carbon origin analysis from sediment cores. These classifiers for the rbcl and 18 Mollusc genes were made using RESCRIPt and Qiime2.&nbsp;</p> <p>The scripts used to created these classifiers are available at the James Hutton ICS GitHub <a href="https://github.com/HuttonICS/blue-carbon-db">blue-carbon-db</a> . The files are as follows:</p> <p><a href="../api/records/10046481/draft/files/mollusc-espineira-classifier.qza/content" target="_blank" rel="noopener noreferrer">mollusc-espineira-classifier.qza</a> is a classifer built from ncbi 18s Mollusc sequences, trained on the primer set from Espi&ntilde;eira et al (2009).</p> <div>rbcl-vasselon-zimmerman-F3-R1-classifier.qza is a classifer built from ncbi rbcl sequences, trained on the F3 and R1 primer set fromVasselon et al (2017).</div> <p>&nbsp;</p> <p>&nbsp;</p> <p><strong>Important: </strong>If you use these classifiers please be aware of the process used to create them and be sure to review the methods. These databases were created by downloading data from the NCBI in October 2023, sequence data available at the NCBI changes over time. To create the most up to date database a fresh download and re-evaluations of the databases would be preferable. All method and scripts can be found at <a href="https://github.com/HuttonICS/blue-carbon-db">blue-carbon-db&nbsp;</a></p> <p>If you use these database please reference this repository along with RESCRIPt and Qiime2&nbsp;</p> <p>&nbsp;</p> <p>Espi&ntilde;eira, M., Gonz&aacute;lez-Lav&iacute;n, N., Vieites, J. M. and Santaclara, F. J. 2009 Development of a method for the genetic identification of commercial bivalve species based on mitochondrial 18S rRNA sequences. J Agric Food Chem, 28, 495-502 https://doi.org/10.1021/jf802787d</p> <p>&nbsp;</p> <p>Vasselon, V., Rimet, F., Tapolczai, K. and Bouchez, A. 2017. Assessing ecological status with diatoms DNA metabarcoding: Scaling-up on a WFD monitoring network (Mayotte island, France). Ecological Indicators, 82, 1-12 <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.ecolind.2017.06.024" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.ecolind.2017.06.024</a></p>

ShareScore

44/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
12
Harmonization
4
Access
16
Reuse readiness
8
Engagement
4

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