This paper presents a comprehensive study of genetic analysis for the prediction of cancer. It discusses the various methods of genetic analysis, including sequencing of the whole genome, sequencing of specific genes, and using microarray data to predict cancer. It also discusses the potential sources of cancer-associated mutations, such as inherited genetic variants, environmental exposure, and epigenetic changes. Furthermore, it examines the use of machine learning algorithms to improve the accuracy of cancer prediction. Finally, it discusses the implications of genetic analysis for the prevention and detection of cancer, as well as its potential applications in personalized medicine. The paper concludes by emphasizing the importance of further research in this area.