Statistical Approaches for Analyzing Cancer Somatic Mutation Data
Somatic mutations play critical roles in tumor development, and recent advances in genome technology have made it feasible to evaluate the association between somatic mutations and cancer-related traits in large sample sizes. However, despite increasingly large sample sizes, it remains challenging to conduct statistical analysis for somatic mutations, because the vast majority of somatic mutations occur at very low frequencies. In this talk, I will review the challenges and issues associated with somatic mutation analysis, and describe available methods for analyzing the data. I will also introduce a new approach that we recently developed, and show that this approach can improve power in detecting somatic mutations that are involved in cancer etiology.