Researchers have conducted a comprehensive benchmarking of methods for mutation calling in circulating tumor DNA. The benchmarking effort has involved various approaches, including UMI clustering tools, machine learning-based somatic variant calling, and ensemble machine learning models. These methods aim to improve the detection of tumor mutations in blood, with potential applications in cancer diagnosis, prognosis, and treatment, including immunotherapy.