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Computational analysis of cancer genome sequencing data.

Isidro Cortés-CirianoDoga C GulhanJake June-Koo LeeGiorgio E M MelloniPeter J Park
Published in: Nature reviews. Genetics (2021)
Distilling biologically meaningful information from cancer genome sequencing data requires comprehensive identification of somatic alterations using rigorous computational methods. As the amount and complexity of sequencing data have increased, so has the number of tools for analysing them. Here, we describe the main steps involved in the bioinformatic analysis of cancer genomes, review key algorithmic developments and highlight popular tools and emerging technologies. These tools include those that identify point mutations, copy number alterations, structural variations and mutational signatures in cancer genomes. We also discuss issues in experimental design, the strengths and limitations of sequencing modalities and methodological challenges for the future.
Keyphrases
  • papillary thyroid
  • copy number
  • squamous cell
  • single cell
  • genome wide
  • electronic health record
  • big data
  • lymph node metastasis
  • artificial intelligence
  • current status