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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
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 |
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