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A machine learning model to determine the accuracy of variant calls in capture-based next generation sequencing
BACKGROUND: Next generation sequencing (NGS) has become a common technology for clinical genetic tests. The quality of NGS calls varies widely and is influenced by features like reference sequence characteristics, read depth, and mapping accuracy. With recent advances in NGS technology and software...
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| Publicado en: | BMC Genomics |
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| Autores principales: | , , , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
BioMed Central
2018
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5904977/ https://ncbi.nlm.nih.gov/pubmed/29665779 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12864-018-4659-0 |
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