Despite its advantages, WGS also presents several challenges. The sheer volume of data generated requires robust bioinformatics tools for analysis and interpretation. Additionally, distinguishing between driver mutations (those that contribute to cancer) and passenger mutations (those that are incidental) can be difficult. Furthermore, the cost of WGS, although decreasing, remains a barrier for widespread clinical use. Ethical considerations around genetic data privacy also need to be addressed.
