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Several automated molecular methods have emerged for distinguishing eukaryote species based on DNA sequence data. However, there are knowledge gaps around which of these single‐locus methods is more accurate for the identification of microalgal species, such as the highly diverse and ecologically relevant diatoms. We applied genetic divergence, Automatic Barcode Gap Discovery for primary species delimitation (ABGD), Assemble Species by Automatic Partitioning (ASAP), Statistical Parsimony Network Analysis (SPNA), Generalized Mixed Yule Coalescent (GMYC) and Poisson Tree Processes (PTP) using partial
- Award ID(s):
- 2015674
- NSF-PAR ID:
- 10493908
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Journal of Eukaryotic Microbiology
- Volume:
- 70
- Issue:
- 5
- ISSN:
- 1066-5234
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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