bioRxiv preprint doi: https://doi.org/10.1101/437061; this version posted October 8, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Genomic characterization of additional cancer-driver genes using a weighted iterative regression accurately modelling background mutation rate Lin Jiang1,2,#, Jingjing Zheng1, #, Johnny Sheung Him Kwan9,10,11,#, Sheng Dai1, Cong Li1, Ka Fai TO9,10,11, Pak Chung Sham5,6,7,8,*, Yonghong Zhu1,2,* and Miaoxin Li1,2,3,4,5,6,7* 1Zhongshan School of Medicine,2First Affiliated Hospital, 3Center for Genome Research, 4Center for Precision Medicine, Sun Yat-sen University, Guangzhou 510080, China; 5Key Laboratory of Tropical Disease Control (SYSU), Ministry of Education, Guangzhou 510080, China; 6The Centre for Genomic Sciences, 7Department of Psychiatry, 8State Key Laboratory for Cognitive and Brain Sciences, the University of Hong Kong, Pokfulam, Hong Kong; 9Department of Anatomical and Cellular Pathology, 10State Key Laboratory in Oncology in South China, 11Li Ka-Shing Institute of Health Sciences, The Chinese University of Hong Kong, New Territories, Hong Kong Short title: a powerful approach to detect cancer-driver genes * To whom correspondence should be addressed to Miaoxin Li. Tel: +86-2087335080; Email:
[email protected] Medical Science and Technology Building, Zhongshan School of Medicine, Sun Yat-sen University, China. Yonghong Zhu. Tel: +86-20 87331451; Email:
[email protected] Medical Science and Technology Building, Zhongshan School of Medicine, Sun Yat-sen University, China. Pak-Chung Sham. Tel: +852-28315425; Fax: +852-28185653; Email:
[email protected]; The University of Hong Kong, 5 Sassoon Road, Pokfulam Hong Kong SAR”.