SoloDel

SoloDel is a computational method that accurately detects somatic deletions from germline deletions even when there are no matched control samples available. It uses a probabilistic, somatic mutation progression model and a Gaussian mixture model to estimate the parameters of the mixed population of somatic and germline deletions. The accuracy of SoloDel in classifying somatic mutations is greatly improved when combined with conventional structural variation caller, and it can successfully recall experimentally validated somatic deletions.