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.