Process / pipelineBioinformatics / omics

Time-Series Copy Number Variation Analysis

Time-series copy number variation (CNV) analysis is a computational genomics pipeline that characterizes chromosomal gains and losses across multiple sequential samples from the same individual or tumor. By comparing copy number profiles at successive time points — such as diagnosis, mid-treatment, relapse — it reconstructs the clonal dynamics and evolutionary trajectories driving genome instability, enabling researchers to track how sub-populations expand, contract, or acquire new aberrations over time.

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Sources

  1. Dentro, S. C., et al. (2021). Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes. Cell, 184(8), 2239-2254. link
  2. Zaccaria, S., & Raphael, B. J. (2020). Accurate quantification of copy-number aberrations and whole-genome duplications in multi-sample tumor sequencing data. Nature Communications, 11(1), 4301. link

Related methods

ScholarGateTime-series copy number variation analysis (Time-Series Copy Number Variation Analysis). Retrieved 2026-06-04 from https://scholargate.app/en/bioinformatics/time-series-copy-number-variation-analysis