Using generative adversarial networks for genome variant calling from low depth ONT sequencing data

Genome variant calling is a challenging yet critical task for subsequent studies. Existing methods almost rely on high depth DNA sequencing data. Performance on low depth data drops a lot. Using public Oxford Nanopore (ONT) data of human being from the Genome in a Bottle (GIAB) Consortium, we traine...

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Detalles Bibliográficos
Autores principales: Yang, Han, Gu, Fei, Zhang, Lei, Hua, Xian-Sheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9151722/
https://www.ncbi.nlm.nih.gov/pubmed/35637238
http://dx.doi.org/10.1038/s41598-022-12346-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9151722/
https://www.ncbi.nlm.nih.gov/pubmed/35637238
http://dx.doi.org/10.1038/s41598-022-12346-7

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