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Review
. 2022 May;23(5):298-314.
doi: 10.1038/s41576-021-00431-y. Epub 2021 Dec 8.

Computational analysis of cancer genome sequencing data

Isidro Cortés-Ciriano  1 , Doga C Gulhan  2 , Jake June-Koo Lee  2 , Giorgio E M Melloni  2 , Peter J Park  3
Affiliations
Review

Computational analysis of cancer genome sequencing data

Isidro Cortés-Ciriano et al. Nat Rev Genet. 2022 May.

Abstract

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.

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References

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