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CARE 2.0: reducing false-positive sequencing error corrections using machine learning
BACKGROUND: Next-generation sequencing pipelines often perform error correction as a preprocessing step to obtain cleaned input data. State-of-the-art error correction programs are able to reliably detect and correct the majority of sequencing errors. However, they also introduce new errors by makin...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9195321/ https://www.ncbi.nlm.nih.gov/pubmed/35698033 http://dx.doi.org/10.1186/s12859-022-04754-3 |