Research has focused on improving methods for variant calling and mutation burden estimation in tumor samples. Various studies have explored different approaches, including the use of machine learning and RNA sequencing, to enhance accuracy and reduce bias in tumor mutational burden calculation. The development of new algorithms and platforms, such as VarNet-T, aims to improve the estimation of tumor mutational burden and its implications for clinical decision-making.