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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
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 |
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