The advent of next-generation sequencing has opened the door to widespread identification of somatic mutations in tumor genomes. These somatic mutations can be utilized to identify “true clonal mutations”, or those that are responsible for driving tumor growth in an individual, and therefore could be useful in the identification of therapeutic targets. The primary issue in the identification of potential targets is that it is often very difficult to distinguish which mutations are “passenger mutations” (non-causative) and those that are true clonal. Mayo Clinic investigators have developed a method which utilizes multi-region sequencing data to rapidly narrow down the list of mutations that are likely to be true clonal mutations and provides an approach to maximize the confidence with which to call such mutations. This method also eliminates the need for additional sequencing in scenarios where the information gain from additional sampling is low, either due to a high confidence that the relevant genes have been identified, or by showing that the information that will be gained from additional sampling is likely to be of very limited value. This technology has the potential to enhance the development of personalized cancer treatments by transforming a large amount of data into a narrowed, clinically-relevant subset.