A random forest-based framework for genotyping and accuracy assessment of copy number variations

Detection of copy number variations (CNVs) is essential for uncovering genetic factors underlying human diseases. However, CNV detection by current methods is prone to error, and precisely identifying CNVs from paired-end whole genome sequencing (WGS) data is still challenging. Here, we present a fr...

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Detalles Bibliográficos
Autores principales: Zhuang, Xuehan, Ye, Rui, So, Man-Ting, Lam, Wai-Yee, Karim, Anwarul, Yu, Michelle, Ngo, Ngoc Diem, Cherny, Stacey S, Tam, Paul Kwong-Hang, Garcia-Barcelo, Maria-Mercè, Tang, Clara Sze-man, Sham, Pak Chung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Methart
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671382/
https://www.ncbi.nlm.nih.gov/pubmed/33575619
http://dx.doi.org/10.1093/nargab/lqaa071

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671382/
https://www.ncbi.nlm.nih.gov/pubmed/33575619
http://dx.doi.org/10.1093/nargab/lqaa071

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