Clinical Analysis and Interpretation of Cancer Genome Data

摘要: The scale of tumor genomic profiling is rapidly outpacing human cognitive capacity to make clinical decisions without the aid tools. New frameworks are needed help researchers and clinicians process information emerging from explosive growth in both number genetic variants routinely tested respective knowledge interpret their significance. We review current state, limitations, future trends methods support analysis interpretation cancer genomes. This includes processes genome-scale variant identification, including tools for sequence alignment, tumor-germline comparison, molecular annotation variants. classification effect variant, reporting results clinicians, enabling clinician a decision based on integrated with other features. describe existing bases, databases, algorithms, identification visualization actionable subsets. With decreasing cost gene mutation testing increasing therapeutics, we expect genomes continue evolve meet needs patient-centered making. science computational medicine still its infancy; however, there clear need development best practices, tools, validation experiments successful implementation oncology.