We present an algorithm, SComatic, that can be used to directly detect somatic mutations in single-cell data sets without using a reference sample. This method opens the possibility of studying clonal relationships among cells, mutational processes at single-cell resolution, and the impact of somatic mutations on cell function in development and disease.