Computer Network Information Center, Chinese Academy of Sciences, Beijing 100083, China;University of Chinese Academy of Sciences, Beijing, 100049, China 在期刊界中查找 在百度中查找 在本站中查找
Computer Network Information Center, Chinese Academy of Sciences, Beijing 100083, China;University of Chinese Academy of Sciences, Beijing, 100049, China 在期刊界中查找 在百度中查找 在本站中查找
Computer Network Information Center, Chinese Academy of Sciences, Beijing 100083, China;University of Chinese Academy of Sciences, Beijing, 100049, China 在期刊界中查找 在百度中查找 在本站中查找
Mutations are induced when cells are stimulated by carcinogens. The mutational process causes a certain pattern of changes in the genome, which are called mutational signatures. Mutational signature analysis is an important task in clarifying the carcinogenic mechanism of carcinogens and driving the development of cancer research, and it will provide new insights and options for early tumor diagnosis and individualized treatment. The breakthroughs and developments of next-generation sequencing have led to the identification of massive somatic mutations, making it possible to mine mutational signatures from large-scale genomes. This study elaborates the mathematical model for mutational signature identification and introduces alternative methods and important parameters. It systematically and comprehensively compares mainstream algorithms and software and specifies the precautions for mutational signature extraction. Finally, it forecasts the future development trend of this field.