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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021-01-01
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| Series: | Computational and Structural Biotechnology Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037021001148 |