Several tools and platforms are used for cancer data analysis. Bioinformatics tools like R and Python libraries (e.g., Bioconductor, Pandas), and specialized software such as GATK, TCGA, and cBioPortal are widely used. Additionally, machine learning and artificial intelligence (AI) techniques are increasingly being applied to analyze large datasets, predict patient outcomes, and identify new biomarkers for cancer.
