ArticleJournal of microbiology (Seoul, Korea)2025
FunVIP: Fungal Validation and Identification Pipeline based on phylogenetic analysis.
Article in Journal of microbiology (Seoul, Korea), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- The contribution of environmental DNA to exploring hypogeous fungal diversity and vulnerability.BMC microbiology · 2026Article
- Hidden diversity of crust-likeIMA fungus · 2026Article
- Exploring Macrofungal Biodiversity and Distribution on Kyodong Island, Republic of Korea.Mycobiology · 2025Article
- Expanding the Inventory of Seven Unrecorded MarineMycobiology · 2025Article
- Exploring Fungal Diversity in Marine Plastic (PET) Wastes and Seafoam in Udo Island, South Korea, with Reports of Two New Species (Mycobiology · 2025Article
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Authors and funding
6 authors.
Funding
Abstract
The increase of sequence data in public nucleotide databases has made DNA sequence-based identification an indispensable tool for fungal identification. However, the large proportion of mislabeled sequence data in public databases leads to frequent misidentifications. Inaccurate identification is causing severe problems, especially for industrial and clinical fungi, and edible mushrooms. Existing species identification pipelines require separate validation of a dataset obtained from public databases containing mislabeled taxonomic identifications. To address this issue, we developed FunVIP, a fully automated phylogeny-based fungal validation and identification pipeline (https://github.com/Changwanseo/FunVIP). FunVIP employs phylogeny-based identification with validation, where the result is achievable only with a query, database, and a single command. FunVIP command comprises nine steps within a workflow: input management, sequence-set organization, alignment, trimming, concatenation, model selection, tree inference, tree interpretation, and report generation. Users may acquire identification results, phylogenetic tree evidence, and reports of conflicts and issues detected in multiple checkpoints during the analysis. The conflicting sample validation performance of FunVIP was demonstrated by re-iterating the manual revision of a fungal genus with a database with mislabeled sequences, Fuscoporia. We also compared the identification performance of FunVIP with BLAST and q2-feature-classifier with two mass double-revised fungal datasets, Sanghuangporus and Aspergillus section Terrei. Therefore, with its automatic validation ability and high identification performance, FunVIP proves to be a highly promising tool for achieving easy and accurate fungal identification.
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