WITER: a powerful method for estimation of cancer-driver genes using a weighted iterative regression modelling background mutation counts

Genomic identification of driver mutations and genes in cancer cells are critical for precision medicine. Due to difficulty in modelling distribution of background mutation counts, existing statistical methods are often underpowered to discriminate cancer-driver genes from passenger genes. Here we p...

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Detalles Bibliográficos
Autores principales: Jiang, Lin, Zheng, Jingjing, Kwan, Johnny S H, Dai, Sheng, Li, Cong, Li, Mulin Jun, Yu, Bolan, TO, Ka F, Sham, Pak C, Zhu, Yonghong, Li, Miaoxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Methods Online
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6895256/
https://www.ncbi.nlm.nih.gov/pubmed/31287869
http://dx.doi.org/10.1093/nar/gkz566

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6895256/
https://www.ncbi.nlm.nih.gov/pubmed/31287869
http://dx.doi.org/10.1093/nar/gkz566

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