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Refphase: Multi-sample phasing reveals haplotype-specific copy number heterogeneity.

Thomas B K WatkinsEmma C ColliverMatthew R HuskaTom L KaufmannEmilia L LimCody B DuncanKerstin HaasePeter Van LooCharles SwantonNicholas McGranahanRoland F Schwarz
Published in: PLoS computational biology (2023)
Most computational methods that infer somatic copy number alterations (SCNAs) from bulk sequencing of DNA analyse tumour samples individually. However, the sequencing of multiple tumour samples from a patient's disease is an increasingly common practice. We introduce Refphase, an algorithm that leverages this multi-sampling approach to infer haplotype-specific copy numbers through multi-sample phasing. We demonstrate Refphase's ability to infer haplotype-specific SCNAs and characterise their intra-tumour heterogeneity, to uncover previously undetected allelic imbalance in low purity samples, and to identify parallel evolution in the context of whole genome doubling in a pan-cancer cohort of 336 samples from 99 tumours.
Keyphrases
  • copy number
  • mitochondrial dna
  • single cell
  • genome wide
  • dna methylation
  • primary care
  • papillary thyroid
  • healthcare
  • machine learning
  • case report
  • gene expression
  • deep learning
  • cell free
  • young adults
  • quality improvement