A curated benchmark dataset for molecular identification based on genome skimming
Abstract Genome skimming is a promising sequencing strategy for DNA-based taxonomic identification. However, the lack of standardized datasets for benchmarking genome skimming tools presents a challenge in comparing new methods to existing ones. As part of the development of varKoder, a new tool for...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-05-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05230-2 |
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| author | Renata C. Asprino Liming Cai Yujing Yan Peter J. Flynn Lucas C. Marinho Xiaoshan Duan Christiane Anderson Goia M. Lyra Charles C. Davis Bruno A. S. de Medeiros |
| author_facet | Renata C. Asprino Liming Cai Yujing Yan Peter J. Flynn Lucas C. Marinho Xiaoshan Duan Christiane Anderson Goia M. Lyra Charles C. Davis Bruno A. S. de Medeiros |
| author_sort | Renata C. Asprino |
| collection | DOAJ |
| description | Abstract Genome skimming is a promising sequencing strategy for DNA-based taxonomic identification. However, the lack of standardized datasets for benchmarking genome skimming tools presents a challenge in comparing new methods to existing ones. As part of the development of varKoder, a new tool for DNA-based identification, we curated four datasets designed for comparing molecular identification tools using low-coverage genomes. These datasets comprise vast phylogenetic and taxonomic diversity from closely related species to all taxa currently represented on NCBI SRA. One of them consists of novel sequences from taxonomically verified samples in the plant clade Malpighiales, while the other three datasets compile publicly available data. All include raw genome skim sequences to enable comprehensive testing and validation of a variety molecular species identification methods. We also provide the two-dimensional graphical representations of genomic data used in varKoder. These datasets represent a reliable resource for researchers to assess the accuracy, efficiency, and robustness of new tools to varKoder and other methods in a consistent and reproducible manner. |
| format | Article |
| id | doaj-art-bedf6ad82f6e4bd3b7ecbb8e8501e5cc |
| institution | OA Journals |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-bedf6ad82f6e4bd3b7ecbb8e8501e5cc2025-08-20T02:39:02ZengNature PortfolioScientific Data2052-44632025-05-011211910.1038/s41597-025-05230-2A curated benchmark dataset for molecular identification based on genome skimmingRenata C. Asprino0Liming Cai1Yujing Yan2Peter J. Flynn3Lucas C. Marinho4Xiaoshan Duan5Christiane Anderson6Goia M. Lyra7Charles C. Davis8Bruno A. S. de Medeiros9Programa de Pós-Graduação em Botânica, Universidade Estadual de Feira de SantanaDepartment of Organismic and Evolutionary Biology, Harvard University Herbaria, Harvard UniversityDepartment of Organismic and Evolutionary Biology, Harvard University Herbaria, Harvard UniversityDepartment of Organismic and Evolutionary Biology, Harvard University Herbaria, Harvard UniversityPrograma de Pós-Graduação em Botânica, Universidade Estadual de Feira de SantanaDepartment of Organismic and Evolutionary Biology, Harvard University Herbaria, Harvard UniversityUniversity of Michigan HerbariumDepartamento de Biologia Vegetal, Universidade do Estado do Rio de JaneiroDepartment of Organismic and Evolutionary Biology, Harvard University Herbaria, Harvard UniversityField Museum of Natural HistoryAbstract Genome skimming is a promising sequencing strategy for DNA-based taxonomic identification. However, the lack of standardized datasets for benchmarking genome skimming tools presents a challenge in comparing new methods to existing ones. As part of the development of varKoder, a new tool for DNA-based identification, we curated four datasets designed for comparing molecular identification tools using low-coverage genomes. These datasets comprise vast phylogenetic and taxonomic diversity from closely related species to all taxa currently represented on NCBI SRA. One of them consists of novel sequences from taxonomically verified samples in the plant clade Malpighiales, while the other three datasets compile publicly available data. All include raw genome skim sequences to enable comprehensive testing and validation of a variety molecular species identification methods. We also provide the two-dimensional graphical representations of genomic data used in varKoder. These datasets represent a reliable resource for researchers to assess the accuracy, efficiency, and robustness of new tools to varKoder and other methods in a consistent and reproducible manner.https://doi.org/10.1038/s41597-025-05230-2 |
| spellingShingle | Renata C. Asprino Liming Cai Yujing Yan Peter J. Flynn Lucas C. Marinho Xiaoshan Duan Christiane Anderson Goia M. Lyra Charles C. Davis Bruno A. S. de Medeiros A curated benchmark dataset for molecular identification based on genome skimming Scientific Data |
| title | A curated benchmark dataset for molecular identification based on genome skimming |
| title_full | A curated benchmark dataset for molecular identification based on genome skimming |
| title_fullStr | A curated benchmark dataset for molecular identification based on genome skimming |
| title_full_unstemmed | A curated benchmark dataset for molecular identification based on genome skimming |
| title_short | A curated benchmark dataset for molecular identification based on genome skimming |
| title_sort | curated benchmark dataset for molecular identification based on genome skimming |
| url | https://doi.org/10.1038/s41597-025-05230-2 |
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