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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Detalles Bibliográficos
Autores principales: van den Akker, Jeroen, Mishne, Gilad, Zimmer, Anjali D., Zhou, Alicia Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5904977/
https://www.ncbi.nlm.nih.gov/pubmed/29665779
http://dx.doi.org/10.1186/s12864-018-4659-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5904977/
https://www.ncbi.nlm.nih.gov/pubmed/29665779
http://dx.doi.org/10.1186/s12864-018-4659-0

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