Identifying the minimum amplicon sequence depth to adequately predict classes in eDNA-based marine biomonitoring using supervised machine learning

Environmental DNA metabarcoding is a powerful approach for use in biomonitoring and impact assessments. Amplicon-based eDNA sequence data are characteristically highly divergent in sequencing depth (total reads per sample) as influenced inter alia by the number of samples simultaneously analyzed per...

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Detalles Bibliográficos
Autores principales: Dully, Verena, Wilding, Thomas A., Mühlhaus, Timo, Stoeck, Thorsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093828/
https://www.ncbi.nlm.nih.gov/pubmed/33995917
http://dx.doi.org/10.1016/j.csbj.2021.04.005

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093828/
https://www.ncbi.nlm.nih.gov/pubmed/33995917
http://dx.doi.org/10.1016/j.csbj.2021.04.005

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