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Designing gene panels for tumor mutational burden estimation: the need to shift from ‘correlation’ to ‘accuracy’

Authors

  • Hao-Xiang Wu Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineSun Yat-Sen University Cancer Center 510060 Guangzhou People’s Republic of China PubMed articlesGoogle scholar articles
  • Zi-Xian Wang Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineSun Yat-Sen University Cancer Center 510060 Guangzhou People’s Republic of China PubMed articlesGoogle scholar articles
  • Qi Zhao Bioinformatics Platform, Department of Experimental Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineSun Yat-Sen University Cancer Center 510060 Guangzhou People’s Republic of China PubMed articlesGoogle scholar articles
  • Feng Wang Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineSun Yat-Sen University Cancer Center 510060 Guangzhou People’s Republic of China PubMed articlesGoogle scholar articles
  • Rui-Hua Xu Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineSun Yat-Sen University Cancer Center 510060 Guangzhou People’s Republic of China PubMed articlesGoogle scholar articles
  1. ↵d +86-20-8734 3795 wangfeng{at}sysucc.org.cn
  2. ↵e +86-20-8734 3333 xurh{at}sysucc.org.cn
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Citation

Wu H, Wang Z, Zhao Q, et al
Designing gene panels for tumor mutational burden estimation: the need to shift from ‘correlation’ to ‘accuracy’
Journal for ImmunoTherapy of Cancer 2019;7:206. doi: 10.1186/s40425-019-0681-2

Publication history

  • Received April 11, 2019
  • Accepted July 16, 2019
  • First published August 6, 2019.
Online issue publication 
January 08, 2022

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© The Author(s). Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.